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TORONTO — The countdown to a possible Ontario election started Thursday, as the minority Liberals tabled a spring budget and gave the New Democrats a week to decide whether they'll support it or send voters to the polls.
Premier Kathleen Wynne asked to meet with NDP Leader Andrea Horwath by May 8 to discuss whether the NDP will support the $130.4-billion spending blueprint.
"I recognize that you and your colleagues may want to spend some time reviewing the budget,'' Wynne wrote Thursday in a letter to Horwath.
"But, given that much of the budget's content has been discussed for several months and that the budget bill is in front of the House, I believe one week is a sufficient amount of time for you to complete your review.''
If Horwath agrees to support the budget, Wynne said she wants a plan to pass it before the legislature rises in June. But the premier didn't say whether she would dissolve the legislature and ask for an election if Horwath declined.
The Liberals need the support of at least one of the opposition parties to pass their budget and avoid an election. The New Democrats have propped them up for the past two years, but Horwath won't say whether they'll do it again.
"I'll be talking to all of you in the morning,'' Horwath said as she breezed past reporters waiting for her outside the legislative chamber.
The NDP leader did not show up to comment before reporters in the budget lockup, a stunning move unheard of in recent memory.
The time-honoured tradition allows journalists to pour over the top-secret document behind locked doors before it's tabled in the legislature and pose questions to the finance minister and opposition leaders.
But Horwath skipped the hot seat, heightening speculation that the province was headed to the polls.
She let Ontarians down, said Finance Minister Charles Sousa.
"It's not about the well-being of any political party or the fortunes of any political party,'' he said. "It's about the fortunes of Ontarians and they deserve to know where it is that they're at, because this is the right budget, it's the right plan.''
Horwath has insisted that she must see the budget before making up her mind, but most of it had already trickled out in recent weeks through campaign-style official announcements and unauthorized leaks.
Thursday's document included ambitious promises for a provincial pension plan, levies to raise billions of dollars for public transit, roads and bridges, billions more for corporate grants, a minimum wage hike and higher taxes for individuals earning more than $150,000.
The Liberals are expecting to spend $12.5 billion more than they take in this year, up from $11.3 billion last year and the $10.1 billion projected in their 2013 budget, but they still plan to slay the deficit in 2017-18.
Last year's revenues came in $1.2 billion short to $115.6 billion, largely due to a sharp $1.5-billion drop in sales tax revenue.
Total spending, including interest on the debt, came in $636 million less than expected, mainly from clamping down on public service retiree benefits and pensions as well as "constraint measures'' from ministries.
But spending is forecast to jump by $3.4 billion this year, $900 million more than projected in the 2013 budget, with program spending expected to climb by nearly $3 billion to $119.4 billion.
That's going to help push up the province's net debt by $20.1 billion to $289.3 billion this year, a staggering 40 per cent of gross domestic product.
Ontario's current ratio of nearly 39 per cent is almost 50 per cent higher than it was just six years ago, "a longer-term vulnerability'' for the province, said TD Bank deputy chief economist Derek Burleton.
"The government still faces an enormous fiscal challenge,'' he said in an interview.
"After four years of restraint, getting operating spending down and implementing a lot of the Drummond commission (austerity report) proposals, they still have four more years ahead to get back to balance.''
The Liberals beat their budget targets five years in a row and are planning to hold program spending growth to one percentage point below revenues until the debt returns to pre-recession levels of 27 per cent of GDP, he said. They also have the lowest program spending per capital among the provinces.
Many of their spending promises are spread out over many years, such as $11 billion to repair and build new schools and $11.4 billion to expand and improve hospitals over a decade.
Some of their shiny new programs, such as the Ontario Retirement Pension Plan, won't cost them a thing since it will come out of the pockets of workers and employers. They're also looking to "unlock the full value'' of their assets, including Ontario Power Generation and the Liquor Control Board of Ontario.
But ratcheting down that key debt-to-GDP figure that debt rating agencies watch closely won't be easy, Burleton said. The province would likely have to hold spending at three per cent for the next decade, given the current economic growth projections.
The Liberals say they're aiming to save $250 million in their programs this year and double it over the following two years, with public servants squarely in their crosshairs.
With compensation accounting for over half of Ontario's program spending, the budget said any wage increases must be absorbed within existing budgets through "efficiency and productivity gains, or other tradeoffs.'' They're also planning to find $1.4 billion in savings by 2017-18 from public-service retirement benefits.
The Liberals are already headed for a showdown with AMAPCEO, the union that represents many managers and professionals in the civil service, with a possible strike or lockout looming in mid-May.
But other public-sector workers in the education and health-care sectors _ groups that have traditionally supported the Liberals _ will see their paychecks increase.
The budget proposed raises for personal support workers, early childhood educators and other licensed child-care workers, leaving the impression that the Liberals may be circling the wagons before a possible election.
"It's a plan to secure Liberal seats,'' said Progressive Conservative Leader Tim Hudak, whose party wants to force an election.
"I want to have a plan to get our province moving again, to secure more jobs for real Ontarians, not politicians.''
Also on HuffPost


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For the second consecutive day, Fort Lewis College soccer signed a younger sibling a younger sibling that also happens to be a 2012 New Mexico 5A Player of the Year from La Cueva High School.
FLC mens soccer followed in the FLC womens soccer programs footsteps by signing Luke Lawrence on Friday to a national letter of intent. Lawrence is the younger brother of Skyhawks soccer player Zac Lawrence.
Luke Lawrence is a reigning N.M. Player of the Year.
On Thursday, the FLC womens program signed Courtney Riley, the younger sister of Skyhawks soccer player Lauren Riley. Courtney Riley, too, is the reigning N.M. 5A Player of the Year.
We are very committed to get the best U.S. talent that we can, and his signing shows our commitment to that process, Skyhawks head coach Oige Kennedy said in a news release to The Durango Herald.
Lawrence, a 6-1, 175-pound forward, is a four-year letterwinner, three-year starter and two-time state champion (2009, 2012). He led La Cueva to a runner-up finish in 2011 and the state semifinals in 2010. Hes a three-time all-state performer.
Lawrence also led his club side, Rio SC 95 (2012-13) and New Mexico Rush 95 (2007-12) to five state championships. He was the camp MVP at the Skyhawks Academy.
Luke is a player that we began tracking a long time ago, and we are extremely proud to be adding a player of his quality to our 2013 squad, Kennedy said. He has a very high technical ability, a knack of scoring goals and is also a good physical presence in the attack.
He is a natural fit for the type of soccer we are trying to produce here, and we feel there is no limit to what he can achieve at our program. Luke has shown that he can score goals at the club and high school level, and we are confident that he can continue that trend in the college game.
Earlier in the day, FLC signed a Nordic skier and a track and field star.
Garrett Bullough from Park City, Utah, also is pretty good at soccer, too.
The FLC mens soccer program announced the signing Friday afternoon, two days after national signing day.
Garrett is a player that we feel can really develop over the next few years and become a strong player for the program, Kennedy said.
Bullough is a 5-10, 155-pound defender/midfielder. Hes skied at the regional, state and national levels, and he won back-to-back state titles in the 400-meter dash. Two years ago, he finished runner-up at the Utah state meet in the long jump.
Bullough was a four-year letterwinner and two-year starter for Park City High School, earning a pair of regional championships. He played club soccer for the elite Juventus Premier and was a four-year member of Utahs Olympic Development Program.
He works very hard at his game and displays a real drive and desire to continue his improvement at the college level, Kennedy said. He has great pace and is a natural athlete that will develop quickly in this learning environment. Pace is a hugely important component of a college soccer player, and Garretts speed and athleticism are two things that he has displayed to us when we have seen him play.
Bullough is smart, too. He was attracted to FLC not only for its national championships but its science program; he plans to study chemistry, math and physics at FLC.
Ive always been interested in science since I was a little, tiny kid, Bullough told the Park City Record earlier this week. Its hard, but its rewarding as well.
Theyre a powerful program. Ive always dreamed about lifting that college trophy, and their program is just as prestigious as any DI program.
FLC has won three DII national championships, two under Kennedy in four years, and have finished runner-up twice.
Bullough and Lawrence are the second and third of a handful of recruits that FLC plans to sign in the coming weeks. They join Malik Badawi, a 6-3, 170-pound forward/midfielder, in the Skyhawks 2013 recruiting class to date.

subset: commoncrawl


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Rare Daws Butler, Volume 2
Sintesi dell'editore
As heard on Sirius XM Radio and NPR stations, here is volume two of Rare Daws Butler. Daws Butler was the voice magician behind such classic cartoon characters as Yogi Bear, Huckleberry Hound, and Quick Draw McGraw. Daws also co-wrote and voiced many of Stan Freberg's greatest comedy records, including Saint George and the Dragonet.
Host Joe Bevilacqua presents an hour of rare Daws Butler comedy recordings, featuring the voices of Stan Freberg, June Foray and others, including "The 64 Million Dollar Question", "Bingo Ringo", "This Is Hawthorne", "Mr. Jinks Had a Little Lamb", "Clementine", "Yogi Tells All", "Confidgetyential", and "Peppy Possum".
Altri titoli dello stesso
Cosa ne pensano gli iscritti
- Robert
- 18/12/2012
More great, rare Daws!
Joe Bev did another fine job in bringing us rare Daws Butler. Features an interview with Yogi Bear, an pilot for an ABC radio show, and two songs--one called "Bingo Ringo" (given the popularity of the Beatles and Lorne Greene's single at the time, not a surprise) and a rocked up version of Oh My Darling Clementine, in his Huckleberry Hound voice. Daws was the Voice Magician we loved in so many cartoons and comedy bits (his work with Stan
Freberg, for example) and years later he worked with many aspiring voice artists. Fans of Daws, cartoons, Stan Freberg (a couple sketches will remind you of Stan's stuff), old time radio, etc. should enjoy this.
1 person found this helpful


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Then I found a recipe that intrigued me. It came from Madhur Jaffrey's fabulous cookbook "World Vegetarian," and, surprise of surprises, it was a recipe for a Kashmiri-style preparation.
This recipe takes a long time to cook: almost 2 hours. But all the ingredients go into the pot right at the beginning and you don't have to babysit them. So after I get back from work, I can throw together the ingredients into the pot, slap on a lid, go out and water the garden and then walk my dogs without a care in the world. Meanwhile, the collards cook themselves. The most you might need to do is check a couple of times to make sure not all the water's evaporated before its time.
The collards are hefty, so although the long cooking tenderizes them, it doesn't reduce them to a mush. They retain a wonderful texture and bite, and absorb all the myriad flavors of the spices and tomatoes.
I loved this recipe, and I know it's one I will be making again and again. Here goes!
Kashmiri Collard Greens
- 5-6 large collard leaves , stems removed, then rolled up and cut into long, skinny ribbons
- 1 tomato , dunked into boiling water for a minute, then peeled and diced
- 1 large onion , thinly sliced
- 3 large cloves of garlic , minced
- 1 tbsp grated ginger
- 1 tbsp extra virgin olive oil
- 1/2 tsp red chilli powder
- 1 1/2 cups water
- Heat the oil and add the onions. Saute on medium heat until nicely browned.
- Add the ginger and garlic and stir for a minute.
- Add the tomato and stir for another minute.
- Add the collard greens, salt, red chilli powder and water.
- When it comes to a boil, cover with a tight-fitting lid, turn the heat to low, and allow the veggies to simmer away for 1 1/2 to 2 hours.
- If there is still water remaining at the bottom of the pan, turn the heat to medium or high and let it evaporate.
- Serve hot as a side dish with rice and dal or with rotis.


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Miranda and Metaphysics
Scott Cheever, a long time user of crystal meth, shot and killed an officer while high. At trial he used the defense that in his intoxicated state he could not have formed the "intent to kill" that would get him the death penalty.
He was found guilty and sentenced to death, but during the trial in state court the prosecution called to the witness stand a psychiatrist who had earlier examined the defendant under a federal court order, before the case was transferred to state court. The Kansas Supreme Court ruled unanimously that the state violated Cheever's Fifth amendment right against self-incrimination by calling the psychiatrist to testify.
The question before the U.S. Supreme Court today, are statements made by a defendant during a court-ordered mental evaluation protected under the fifth amendment?
Several times during the argument reference was made to "peering into the defendant's mind". Does it seem fair, as Cheever's attorney, Neal Katyal, put it "that the government can peer into someone's mind and extract information . . . un-Mirandized . . . and have that used against them"? . . . After all isn't it just a little bit like cheating on your metaphysics final by looking into the soul of the boy sitting next to you ? . . . (apologies to Woody Allen)
By the end of the argument it wasn't looking good for Scott Cheever as Justice Sotomayor asked his lawyer, "Mr. Katyal, assuming the incredulity of my colleagues . . . which way would you rather lose?


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RetireVillage.com and Annuity.com have created this Privacy Policy to demonstrate our firm commitment to privacy. The following discloses our information gathering and dissemination practices our the website.
Our site uses an online secure form for customer applications. When your request is placed through our secure online server we collect confidential customer information which our secure server software (SSL) encrypts before it is sent to us. All of the customer data we collect is protected against unauthorized access.
CONSUMER INFORMATION, collected to process your request, might include contact information such as name, mailing address, telephone number and email address. All customers' information we collect is strictly confidential and maintained in electronic files in our head-office. Our participating insurance professionals, to whom this information is referred, are bound by the same terms of confidentiality, and use such information to contact the customers for purposes of providing customers with the requested quotes.
Aggregate statistics about our customers, sales, traffic patterns and related site information may be provided to reputable third parties, which will not contain personally identifying or financial information. Annuity.com may release account information when we believe, in good faith, that such release is reasonably necessary to comply with the law, enforce the terms of any of our user agreements or protect the rights, property or safety of Annuity.com, our customers or others.
By submitting your information via our website or one of our partners, and requesting information or a quote from us, you acknowledge and agree that a provider may contact you using your information to provide your requested quote or to obtain additional information needed to provide your requested quotes where permitted by law. In the event that we do not have a provider, your information may be shared with another company that will provide this same service. This company may have several providers contact you at their discretion. We are not responsible, and shall not be held liable, if a Provider or other third party to whom we have forwarded any of the information you submitted to us violates our Privacy Policy or such third party's own privacy policy (if any), or otherwise violates the law.
We use outside companies to display ads on our site. These ads may contain pieces of information that a website transfers to a hard drive for record keeping purposes while at the site.
The privacy policy of an advertiser or promotional service linked through our site may differ from ours. We encourage you to read that policy before responding to that offer.
We have no way of distinguishing the age of individuals who access our web site; however, in the event that we discover that a person under the age of 18 is providing personally-identifying information, we will not accept any such information. If a person had provided us with personally-identifying information without parental or guardian consent, the parent or guardian should contact us to remove that information and opt out of promotional opportunities.
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Monday Night Trivia at Stacy's
December 14 @ 8:00 PM - 10:00 PM
|Recurring Event (See all)
An event every week that begins at 8:00pm on Monday, repeating until December 29, 2020
Are you feelin' lucky? We've got some questions we would like you to answer! Grab a friend or a bunch of them and join us for King Trivia on Monday evenings from 8-9:30 PM. Clayton is our quiz-master and will be putting your knowledge to the test (no phone assistance permitted). Weekly prizes as well as you can compete for the high score against a national network answering the same questions! *Each team can be a maximum of 10 people


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Andreas Scholl – A Biographical Timeline
Ethereal yet visceral, Scholl's voice is the dream vehicle for Purcell . . . highly responsive to the poetic rhetoric . . .
BBC Music Magazine (London), January 2011 (CD review O Solitude)
"Andreas Scholl has the world's most cultured counter-tenor voice. And during his three Handel arias some 6,000 people scarcely dared breathe."
Richard Morrison in the Times (2005, reviewing the "Last Night of the Proms")
Born into a family of singers in Eltville on the Rhine, near Wiesbaden, Andreas Scholl's early musical training was with the Kiedricher Chorbuben. He later went on to study under Richard Levitt and René Jacobs at the renowned Schola Cantorum Basiliensis. He is a winner of the 1999 Echo Awards and Prix de l'Union de la Presse Musicale Belge ("Young Musician of the Year"), the Baroque Vocal Prize at the 1996 Gramophone Awards and the Middle Ages/Renaissance category of the 2002 Edison Awards for his recording of A Musicall Banquet.


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Carpet Cleaner Service Near Dilworth, MN
Carpet cleaning services for Fargo ND & surrounding areas
Why should you choose us to be your carpet cleaner?
- Results – Over the years we have invested a great deal of time and thousands of dollars into steam cleaning equipment and cleaning techniques to make sure we get your carpet as clean as possible.
- Pictures – For comparison purposes, we take pictures of your carpet before and after cleaning.
- Service – We Are An Owner-Operated Company located near Dilworth, MN – I am the owner and on the job site. You get an experienced, caring and friendly owner instead of an hourly wage employee. We do not try to get in and out as fast as we can.
- Easy Scheduling – Our phone is answered 24 hours a day, you can schedule anytime. If you prefer text messaging you can text us as well, or use our online system to get a quote. You do not have to worry about us missing your call
See the before and after results for yourself:
Homes, Apartments, Businesses in Dilworth, MN and the Fargo ND Surrounding Communities
Our ability to get jobs done when you need to have it done has made us an source for homeowners, renters, apartment managers and facility managers of all kinds.
What We Offer:
Our system works great with residential and light commercial air ducts and furnaces. The operator usually does not have to cut access into the duct with this method. We are able to clean the entire length of the ducts in most cases. This process can take from 3-6 hours depending on the size of the house or business.
After cleaning the ducts, we clean as much of the heating/cooling unit as possible, including the furnace. This can include:
- Cleaning and/or replacing filters
- Cleaning the "A" coil if needed
- Switch units and contact points that may collect dust
- Blower motor cleaning
Call Now For Our Current Air Duct Cleaning Promotion!
We provide a free inspection and pictures of the inside of your duct work for residents in the Fargo ND area and Moorhead MN. You can give us a call or text.


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Digital technologies—mobility, social media, analytics, cloud computing, Internet of Things, and identity and security technologies—can reinvent the work, innovation, and impact of international development organizations. When people, devices and data are connected in meaningful ways, the sky's the limit on what can be achieved. Yet true digital transformation depends on the ability to link digital technologies to one another and to the broader context—to organization and mission goals, business and operating models, cross-sector partnerships, and most importantly, to people.
Digital is an enabler. It must be designed around people, services and the local environment to extend the reach of programs, increase efficiency, and gain better insights. This is how digital technologies can transform field staff experiences; engage clients, beneficiaries and donors in new and creative ways; empower decision makers and communities themselves with real-time insights; accelerate local innovation; and touch lives across the developing world.


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FRITZ!Box 7581 Service - Knowledge Base
AVM Content
- FRITZ!Box 7590
- FRITZ!Box 7583
- FRITZ!Box 7582
- FRITZ!Box 7560
- FRITZ!Box 7530
- FRITZ!Box 7490
- FRITZ!Box 7430
- FRITZ!Box 7390
- FRITZ!Box 7369
- FRITZ!Box 7360
- FRITZ!Box 7340
- FRITZ!Box 7330
- FRITZ!Box 7272
- FRITZ!Box 6890 LTE
- FRITZ!Box 6840 LTE
- FRITZ!Box 6820 LTE
- FRITZ!Box 6810 LTE
- FRITZ!Box 6591 Cable
- FRITZ!Box 6590 Cable
- FRITZ!Box 6490 Cable
- FRITZ!Box 5491
- FRITZ!Box 5490
- FRITZ!Box 4040
- FRITZ!Box 4020
Wireless connection is only established with 195 Mbit/s instead of 450 Mbit/s
When your wireless device (for example a notebook, smartphone, game console) establishes wireless connections (WiFi) to the FRITZ!Box according to the wireless standard 802.11n, the throughput does not exceed 195 Mbit/s.
- A throughput of 450 Mbit/s can only be achieved when channels with a bandwidth of 40 MHz are used. Some wireless devices do not support channel widths of 40 MHz or only support them in the 5 GHz frequency band.
Note:All instructions on configuration and settings given in this guide refer to the latest FRITZ!OS for the FRITZ!Box.
Simply proceed as described below. After each measure, check whether the problem persists.
1 Checking the event log of the FRITZ!Box
- Click "System" in the FRITZ!Box user interface.
- Click "Event Log" in the "System" menu.
- Select "Wireless" from the drop-down list.
- If the message "Wireless LAN transmission quality increased by reduced channel bandwidth [...]" is displayed, follow the instructions in our guide FRITZ!Box reports "Wireless LAN transmission quality increased by reduced channel bandwidth".
2 Configuring the wireless device to use 40 MHz channels
Perform the following step if the computer's wireless network adapter or the wireless device supports wireless channels with bandwidths of 40 MHz:
Note:You can find information on configuring the device in its manual, or consult its manufacturer directly.
- Configure the wireless network adapter or the wireless device so that it uses wireless channels with bandwidths of 40 MHz.
Many Intel wireless network adapters can be configured for channels with bandwidths of 40 MHz by calling up the properties of the wireless network adapter in the Windows Device Manager and selecting "auto" for "802.11n Channel Width for band 2.4":
AVM Section Navigation


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Source: USDA
The U.S. Department of Agriculture today announced the availability of the final environmental impact statement (EIS) that evaluates the potential environmental effects of deregulating alfalfa genetically engineered (GE) to be resistant to the herbicide glyphosate, which is known commercially as Roundup. This GE alfalfa is commonly referred to as Roundup Ready (RR) alfalfa.
It is important to note that the EIS USDA is releasing today is not a decision document. It is an analysis of the impacts of the various alternatives with regard to their potential environmental and related economic impacts. The final EIS will be available for public review for at least 30 days before USDA will publish a record of decision on how it will proceed.
"Our goal with the EIS, first and foremost, is to recognize and consider the many concerns that we have heard from all segments of agriculture," said Secretary Vilsack. "We are equally committed to finding solutions that support not only the developers and users of biotechnology products, but growers who rely on purity in the non-genetically engineered seed supply."
USDA considered three alternatives during the preparation of the final EIS: 1) to maintain the RR alfalfa's status as a regulated article; 2) to deregulate RR alfalfa; or 3) to deregulate RR alfalfa with geographic restrictions and isolation distances for the production of RR alfalfa. USDA has thoroughly analyzed the potential environmental impacts of the proposed alternatives and has listed two preferred options: deregulation as one option and the other deregulation accompanied by a combination of isolation distances and geographic restrictions on the production of GE alfalfa seed and, in some locations, hay.
By listing both options as preferred, USDA has considered plant pest issues as well as broader environmental and economic issues related to the coexistence between genetically engineered, non-genetically engineered, and organic alfalfa production.
USDA maintains that biotechnology holds great promise for agriculture here in the United States, and around the world. There's absolutely no doubt of the safety of the many products USDA's regulatory system has approved. The examination of these issues through the EIS process, however, highlighted some of the challenges USDA faces in the area of biotechnology regulation as it aims to meet the expectations of its diverse stakeholders.
"We have seen rapid adoption of biotechnology in agriculture, along with the rise of organic and non-genetically engineered sectors over the last several decades," Vilsack said. "While the growth in all these areas is great for agriculture, it has also led, at times, to conflict or, at best, an uneasy coexistence between the different ways of growing crops. We need to address these challenges and develop a sensible path forward for strengthening coexistence of all segments of agriculture in our country. All are vital and a part of rural America's success. All should be able to thrive together."
Vilsack said that USDA will use this opportunity to begin a conversation on how to move forward and find strategies for strengthening coexistence. "We will partner with all those who want to roll up their sleeves and work with us and each other to find common sense solutions to today's challenges. And we will do so openly and transparently."
APHIS will be submitting the EIS to the Environmental Protection Agency for publication in the Federal Register, and USDA anticipates that EPA will publish a notice that the final EIS on RR alfalfa is available for public review in the Federal Register on December 23, 2010. A copy of the EIS provided to EPA can be reviewed at http://www.aphis.usda.gov/biotechnology/downloads/alfalfa/gt_alfalfa%20_feis.pdf.


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Mplus Home
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Categorical indicators
Mplus Discussion
Categorical Data Modeling
posted on Wednesday, February 21, 2001 - 3:21 am
I read that Mplus have been greatly expanded in version 2. I have the first version and
I'm very interested in it.
I would like to know if you use a full maximum likelihood approach to estimate a multilevel
structural equation modeling with binary and/or ordered categorical indicator variables and
wich type of approach. And if factor scores are available for this type of models.
Linda K. Muthen
posted on Wednesday, February 21, 2001 - 8:10 am
These analysis options are not available in Mplus Version 2. I don't know that there is any program available that estimates this type of model. We are currently doing research on this topic.
posted on Saturday, July 20, 2002 - 8:16 pm
The default estimation method for EFA with categorical indicators is ULS. However, the default for CFA is WLSMV. What are the reasons for preferring ULS as the default in an EFA over WLSMV?
Linda K. Muthen
posted on Sunday, July 21, 2002 - 6:37 am
The reason that ULS was chosen as the default for EFA is that it is much faster. It is a good way to look at a large set of categorical outcomes more quickly that using WLSMV.
posted on Thursday, December 12, 2002 - 10:27 am
For factor analysis, is it OK to have some items
that are binary and others that are polytomous in
a single analysis?
posted on Thursday, December 12, 2002 - 10:32 am
Yes. See page 180 of the Mplus User's Guide.
Kyung Kim
posted on Tuesday, April 01, 2003 - 6:07 am
Can I calculate factor scores, using M-plus program, for continuous latent variables with categorical (e.g., 5-point or 6-point Likert types) indicators? If not, are there other ways for doing this?
Linda K. Muthen
posted on Tuesday, April 01, 2003 - 6:46 am
Mplus does estimate factors scores for ordered polytomous variables. You ask for them through the SAVEDATA command.
Per Togo
posted on Tuesday, May 20, 2003 - 2:10 pm
I have used a CFA model with three factors
and categorical variables (8 categories)
x BY a b c d;
y BY e d f g;
z BY h i j k;
I could not find a description of how the program computes the factorscores for more than binary variables(using categorical, savedata, fscores). (I'm not that experienced in matrix calculations and need a description for a paper)
Can you help me out?
Linda K. Muthen
posted on Thursday, May 22, 2003 - 6:43 am
Appendix 11 of the Mplus User's Guide contains a description of how factor scores are estimated in Mplus. The description for binary variables which begins with formula 227 applies also to polytomous variables. For categorical outcomes, factor score estimation is an iterative technique.
posted on Monday, June 02, 2003 - 7:17 am
I would like to know how does Mplus estimate the thresholds?
posted on Monday, June 02, 2003 - 7:46 am
When there are no x variables (covariates) in the model, the thresholds are simply the normal z scores corresponding to the univariate probabilities. With x's, they are obtained via probit regression.
Erkki Komulainen
posted on Thursday, June 05, 2003 - 12:29 pm
Hi! Working on a problem which would require a polychotomous regression with both manifest and latent independent variables. I fail to solve how that would be written in the syntax.
Linda K. Muthen
posted on Thursday, June 05, 2003 - 12:38 pm
I'm a little confused. You say you have both manifest and observed independent variables. Are the factor indicators for the latent independent variables continuous or categorical? What is the dependent variable in the model? Is it observed or latent? If it is observed, the statement in the MODEL command would be:
y1 ON x1 f1;
where y1 is an observed binary or ordered categorical variable, x1 is an observed independent variable, and f1 is a latent independent variable. You would also need to identify the y1 variable as categorical by using the CATEGORICAL statement of the VARIABLE command.
Please let me know if this does not answer your question.
Erkki Komulainen
posted on Friday, June 06, 2003 - 12:46 am
Hi! I failed with this syntax:
CATEGORICAL ARE ammk993l ;
climate BY a3 a21 isuhde2 asuhde2;
ammk993l ON climate sesdiko ero ;
With TYPE IS LOGISTIC that obviously is impossible.
I solved it by modelling in the first step the latent variable and saved the factor score and did the logistic using the factor score. Erkki
Linda K. Muthen
posted on Friday, June 06, 2003 - 7:38 am
TYPE=LOGISTIC is for a single dependent varirable. If you do TYPE = GENERAL with the CATEGORICAL statement, you will estimate a probit regression for the categorical dependent variable. I think this is what you want to do. There is a summary of analysis types and estimators available for each analysis type on page 38 of the Mplus User's Guide.
posted on Thursday, November 06, 2003 - 4:30 pm
Hi there,
I want to create a latent trait variable with categorical indicators (same variable across 6 waves) and the WLSMV estimator and wanted to check to see if my code was correct.
sui by x1 x2 x3 x4 x5 x6;
Since these indicators do I have to specify some code for the thresholds? Also, how would I interpret the thresholds at each time point?
Linda K. Muthen
posted on Sunday, November 09, 2003 - 10:21 am
The way you are coding this does not take time into account. But you don't mention that you are interested in change over time. So then it is ok. If you are not taking time into account, then it is not necessary to include thresholds in your analysis.
posted on Tuesday, January 04, 2005 - 5:57 am
I am wondering what is the most appropriate way to handle observed (not latent) categorical covariates in a WLSMV framework. In my study X1 is an ordinal variable (6 classes) and X2 is binary.
Currently, this is how I am specifying the model:
Catategorical are p1-p7 a1-a8 d1-d6;
f1 by p1-p7;
f2 by a1-a7;
f3 by d1-d6;
f3 on f1 f2 X1 X2;
Is it alright that the independent X variables are not specified as categorical?
In addition, if I try to estimate the covariance between X variables and F1 F2 (i.e., X1 X2 with F1 F2) I get an error message about X1 being binary (the program then tells me to specify it as categorical). However, if I do not free the covariance between the X1 X2 and F1 F2 the model has a poor fit.
Linda K. Muthen
posted on Tuesday, January 04, 2005 - 6:20 am
You should not put x1 and x2 on the CATEGORICAL list. The CATEGORICAL list is only for dependent variables. You should treat your covariates as you would in regular regression. The binary variable can be left as is. The ordinal variable should be turned into five binary dummy variables. You should not specify any covariance between x1 and x2. The model is estimated conditioned on x1 and x2. If you want to know the covariance between x1 and x2, you can do a BASIC run and obtain this.
posted on Tuesday, January 04, 2005 - 6:31 am
A few follow-ups:
1) Should I specify the covariance between the observed categorical variables (either the binary, ordinal, or both) and the other latent predictors? I know that Mplus does not do this as the default, but it degrades the model fit.
2) If the observed X variables were continuous would your answer to question 1 be different?
Linda K. Muthen
posted on Tuesday, January 04, 2005 - 6:55 am
1. You should not specify the covariances among the x variables. By doing so, you bring them into the model estimation and thereby the assumption of normality applies to them. You are not estimating the model with these covariances fixed to zero. The model is estimated conditioned on the x's. Therefore, the assumption of normality does not apply to them. They are not part of the model so if the fit is poor, it is not because the covariances are zero. They are not. It's the same as regular regression. If you have ten covariates, the parameters of the regression model are an intercept and ten slopes. The model does not estimate the covariances among the x variables.
2. No.
posted on Tuesday, January 04, 2005 - 7:51 am
When I include the categorical X variables into the model (without specifying any covariance), I get the following error message:
Linda K. Muthen
posted on Tuesday, January 04, 2005 - 8:58 am
The only place the categorical x variables should be is on the right-hand side of ON. You should not mention their means, variances, or covariances.
posted on Tuesday, January 04, 2005 - 11:27 am
Last question in this vein. Please excuse my ignorance.
When observed variables are added as covariates to the right side of an ON in an SEM model, should I be concerned that their presence dramatically reduces the fit of the overall model? The modification indicies are indicating that regressing them onto other latent predictor variables in the model would improve model fit.
However, I really am only interested in examining if the latent predictors are significantly related to the latent DV after controlling for observed variables like race, ses, prior delinquency etc.
Thanks for your help.
posted on Tuesday, January 04, 2005 - 4:03 pm
Typically, other latent predictors would be regressed on the covariates since the covariates are often demographics and therefore antecedents - so such relationships should be included. Model fit can also suffer from left-out direct effects from the covariates to the indicators of endogenous factors.
posted on Wednesday, January 05, 2005 - 9:03 am
When I regress the covariates onto the latent predictor variables the model becomes extremely poor fitting. I have been racking my brain trying to figure out why this is occuring, but have made no headway. Do you have time to take a quick peek if I send you the data and syntax?
Linda K. Muthen
posted on Wednesday, January 05, 2005 - 10:03 am
Send two outputs to
. The one that fits well without the covariates. And the one with the covariates.
posted on Thursday, January 20, 2005 - 7:55 pm
I am looking at a multiple group model with a binary outcome variable. I don't have a categorical latent variable, but only persistence with no=0, yes=1 coding.
partial output:
GROUPING IS ethn69 (1=white 2=latino);
CATEGORICAL = persiste;
GROUPING IS ethn69 (1=white 2=latino);
type = general missing MEANSTRUCTURE h1;
estimator = ML;
*** ERROR in Analysis command
ALGORITHM = INTEGRATION is not available for multiple group analysis.
Try using the KNOWNCLASS option for TYPE = MIXTURE.
I have tried using the KNOWNCLASS option for TYPE=MIXTURE as recommended but I get a message telling me (correctly so) that I don't have a categorical latent variable. I have four latent variables and a binary outcome variable, how/where should I put this variable?
Linda K. Muthen
posted on Thursday, January 20, 2005 - 8:21 pm
To use KNOWNCLASS, you need to use the CLASSES and KNOWNCLASSES option:
CLASSES = cg (2);
KNOWNCLASS = cg (ethn69 = 1 ethn69 = 2);
Check KNOWNCLASS in the index of the user's guide. IT should point to an example.
posted on Saturday, January 22, 2005 - 6:26 pm
Hello again!
Thank you for your prompt reply Linda. I want to thank Thuy for his valuable help with my model as well.
I have the following questions:
I began doing a multiple group analysis and have developed group specific models using the modification indices provided by the outputs.
Now that I will be using the KNOWNCLASS option with TYPE=MIXTURE,
1) How is a group specific model developed?
2) Is it possible to analyze the measurement model first and then the structural model. I have not added covariates but I would like to at least add "primary language" and "income"
2) do I use modification indices from the multiple group analysis models or how do I determine measurement invariance?
3) how are the starting values of the variables for each group selected and for each observed factor indicator for each latent variable? I have four latent variables: GC at time 1 (five factor indicators), GC at time 2 (five factor indicators), academic integration (2 factor indicators), and social integration (2 factor indicators); and two categorical variables: persistence and performance (GPA).
4) Does MPlus analyze indirect effects with the TYPE= MIXTURE model?
in addition I am measuring one latent variable at two time points:
I know that growth mixture modeling is not appropriate since I only have two time periods, how is effect of time taken into account in measuring this model?
Pardon my MPlus illiteracy.
Thank you for your help.
posted on Sunday, January 23, 2005 - 3:43 pm
1) In the Model command you specify group-specific parameters within %c#% statements, e.g.
says that the variance of the factor f is specific to class 1.
2) I think MIs are available in this environment too, but you can also use chi-square difference testing via 2 times the logL differences of nested models.
3) Mlpus provides default starting values.
4) Pleae check with Thuy.
5) Analyze the outcomes for the 2 time points together: if you have 5 outcomes per time point you analyze 10 variables.
posted on Friday, March 25, 2005 - 6:54 am
Drs. Muthén & Muthén,
I have what I hope is a very quick question. I have been reading (and rereading) the Muthén, du Tiot, & Spisic (1997) paper on your robust methods. From what I understand, Mplus uses Equation 44 to obtain parameter estimates when WLSMV is invoked. The weight matrix in Equation 44 is the inverse of a diagonal matrix, W^-1. For WLSMV (and WLSM) I could rewrite Equation 44 by replacing W with Gamma_D where Gamma_D here is the diagonal elements from Equation 48. Is my understanding correct?
Thank you.
posted on Friday, March 25, 2005 - 9:08 am
posted on Thursday, April 28, 2005 - 1:45 am
I'm trying to construct a two-way ANOVA like interaction in MPLUS 3.11 using two observed categorical variables. The interaction is between gender (two categories) and family structure (five categories). The dependent variable is continous measure of antisocial behavior.
In the Mplus user guide (p.420) you list various ways of obtaining interactions for different variable types, but have not included the interaction between observed categorical with observed categorical. Which is the best method to use in that case ?
I have used the following method:
(1)Coded the family structure variable into four dummy codes (the omittet is the reference group) predicting antisocial behavior.
(2) Used multigroup analysis to examine if there is any significant differences between the unstandardized betas (mean values) for boys and girls.
Is this the correct way to do it ? If it is, do you know any litterature that deals with this categorical times categorical variable interaction using multigroup SEM?
Are you allowed to use multigroup analysis when you have multilevel design?
Thanks in advance.
Linda K. Muthen
posted on Thursday, April 28, 2005 - 8:42 am
You can use DEFINE or the multiple group approach as you have done above. I don't know of any reference to this. For some multilevel models, the GROUPING option can be used for multiple group analysis. If not, then the KNOWNCLASS option can be used instead.
Fred Li
posted on Friday, November 18, 2005 - 3:39 pm
Hello !
I am a new Mplus user. Is there anyone who can help me with the following Mplus program that has an error message at the end of it? My intended task was to create a polychoric correlation matrix for categorical variables for further CFA analysis.
Thanks in ADVANCE!!
TITLE: Number Sense in 2005; Note that this program has saved out
the polychoric correlation matrix in a file called test.pcm;
FILE IS "C:\Documents and Settings\USR1\�ୱ\NS2005.dat";
NAMES ARE q1 q2 q3 q4 q5 q6 q7 q8 q9 q10 q11 q12 q13 q14 q15 q16 q17
q18 q19 q20 q21 q22 q23 q24 q25 q26 q27 q28 q29 q30 q31 q32 q33 q34
q35 q36 q37 q38 q39 q40 q41 q42 q43 q44 q45 q46 q47 q48 q49 q50 q51
q52 q53 q54 q55;
USEVARIABLES ARE q2 q3 q4 q5 q6 q9 q10 q11 q12 q13 q14 q15 q16 q17
q18 q20 q21 q22 q24 q25 q26 q29 q30 q31 q32 q33 q34 q35 q36 q37 q38
q39 q40 q41 q43 q44 q45 q46 q47 q48 q49 q50 q51 q52 q53 q54 q55;
ETA1 BY q2 - q55;
*** ERROR in Savedata command
Only sample correlation matrix may be saved when there is at least
one categorical dependent variable.
Linda K. Muthen
posted on Friday, November 18, 2005 - 4:19 pm
It looks like you have not used the FILE option of the SAVEDATA command to give the name of the file in which to save the correlation matrix. Note that with categorical outcomes, you cannot analyze a correlation matrix and a weight matrix in Mplus but need raw data. You should send these types of questions to
and include your license number.
posted on Thursday, March 02, 2006 - 9:37 am
I have a SEM model using weighted data that will converge with no errors when all the variables are considered continuous but won't run when some indicators are considered categorical (binary) or count. f1 has 7 binary indicators (yes/no) and f2 has 4 count indicators (0-7 days) and one continuous indicator.
CATEGORICAL ARE x1 x2 x3 x4 x5 x6 x7;
COUNT ARE y1 y2 y3 y4;
f1 BY x1 x2 x3 x4 x5 x6 x7;
f2 BY y1 y2 y3 y4;
f2 IND x8;
f2 IND f1;
f2 IND f3;
The error message I receive is "MODEL INDIRECT is not available for analysis with ALGORITHM=INTEGRATION," which I did not specify. If I comment out either the CATEGORICAL or COUNT lines, I get the same error. If I comment out both, everything runs fine.
Linda K. Muthen
posted on Thursday, March 02, 2006 - 10:31 am
When you use MLR with either CATEGORICAL or COUNT, numerical integration is required. Therefore, MODEL INDIRECT is not available.
posted on Friday, March 03, 2006 - 5:56 am
Thanks for the quick response. The model terminated normally when CATEGORICAL was used and I commented out the COUNT and MODEL INDIRECT. However, now I get the error "MODINDICES option is not available for ALGORITHM=INTEGRATION." Could I consider all of my variables continuous in order to get MODINDICES, but use the parameter estimates derived when considering the vars categorical when reporting results?
posted on Friday, March 03, 2006 - 6:33 am
That would only be very approximate. Instead, you might want to explore model variations and do chi-square difference testing via -2*loglikelihood difference.
Stephan Golla
posted on Monday, February 19, 2007 - 4:54 am
Hello,my model contains latent factors, two dependent manifest indicator (d7; d16). However, if I put b3 (male=1) into my model I will get the following error message below:
USEVARIABLES ARE b3 d7 d16 c6 c10 c18 c20 c11 c12 c13 e1-e20 wgt;
CATEGORICAL ARE b3 d7 d16 c6 c10 c18 c20 c11 c12 c13 e1-e20;
WEIGHT IS wgt;
MO1 BY c6 c11 c10 c18 c20;
MO2 BY c11 c12 c13;
f1 BY e1-e20*
f2 BY e1-e20*
f3 BY e1-e20*
f4 BY e1-e20*
f5 BY e1-e20*
d7 d16 ON b3 MO1 MO2 f1-f5;
** ERROR in Variable command
CATEGORICAL option is used for dependent variables only.
B3 is not a dependent variable.
Thanks, Stephan
Stephan Golla
posted on Wednesday, February 21, 2007 - 6:08 am
Sorry, I've just found the answer in one of your web seminar files. We do not distinguish between scales if the variable is an IV (x). However, I guess that in spss user have to specify if they'll use a categorical variable. But this seems not to be necessary with Mplus, right?
Regards, Stephan
Linda K. Muthen
posted on Saturday, February 24, 2007 - 7:17 am
In regression analysis, independent variables (covariates) can be binary or continuous. In both cases, they are treated as continuous. In SPSS, perhaps the specification of categorical for an independent variable automatically creates a set of dummy variables for it. In Mplus, if you have a nominal independent variable, you must create a set of dummy variables.
Soyoung Lee
posted on Wednesday, March 21, 2007 - 6:17 pm
I have a question about the dimension of the weight matrix of WLS/WLSM/WLSMV with categorical indicators in factor analysis.
I understand it is [(p(p+1)/2) x (p(p+1)/2)] when p=# indicators, p(p+1)/2=# univariate & bivariate marginal proportions, in dichotomous case. I wanted to know what it would be in polytomous case. [((C-1)p+p(p-1)/2) X ((C-1)p+p(p-1)/2)] with C=# categories, (C-1)p+p(p-1)/2= (# thresholds) + (# polychorics)?
Also, I found the WLS and WLSMV estimates of thresholds are slightly different. Aren�t they the same since thresholds are the normal z scores corresponding to the univariate probabilities? Or, are these updated in the 3rd stage of the Muthen's WLS procedure? Thanks.
(estimates with WLS)
(estimates with WLSMV)
Bengt O. Muthen
posted on Wednesday, March 21, 2007 - 7:01 pm
Yes on your first question (assuming all items have the same number of categories C).
The model-estimated thresholds are different between WLS and WLSMV because in WLS it is acknowledged that the sample statistic thresholds are correlated among themselves and with the polychoric correlations, while with WLSMV a diagonal weight matrix is used (no correlations at all). The Muthen (1978) Psychometrika article details this in terms of WLS vs ULS.
Gemma vilagut
posted on Tuesday, April 17, 2007 - 10:16 am
We are trying to perform CFA with M-PLUS, including both continuous indicators and ordered polytomous indicators (likert- 5ctg).
I ran CFA indicating which variables were categorical (CATEGORICAL instr) and WLSMV estimator. Result: the continuous items have big residual variances (r-sq<0.2), small loadings (sdtYX <0.45)and not very good GOF indices.
However, when treating all the variables as continuous (and MLM estimator), I obtain better results. The results are not awesome, but the most usual GOF indices are over the recommended thresholds (CFI and TLI > 0.95, RMSEA=0.015, Standardized Root Mean Square Residual=0.049). Also, residual variances are relatively small (except for one item, FD21= 0.756).
Chi-Sq test is significant in both analysis, but sample size is 4400 indiv.
I understand that it is more appropriate to treat the variables as categorical, specially taking into account the highly skewed distributions of our items, but the fact that I obtain better results with the continuous variables approach makes me doubt.
Could you tell me which is the best approach to analyse this data? does it make sense to compare GOF indices results of both methods and use the one that provides better fit? Or is it incorrect to analyse ordered categorical items not taking into account that they are actually categorical (i.e. not using CATEGORICAL statement)?
Many Thanks!
Linda K. Muthen
posted on Tuesday, April 17, 2007 - 11:08 am
If your items have strong floor or ceiling effects, treating them as continuous results in attenuated correlations. The low correlations can result in better model fit because there is less power to reject the null hypothesis. Categorical items with strong floor or ceiling effects should be treated as categorical.
David Kerr
posted on Monday, May 28, 2007 - 9:50 am
Hello---I�m trying to test a model that has latent variables each comprised of categorical indicators (questions that can be answered agree, disagree, or don�t know).
The �don�t knows� are of interest, so I thought I would create two dummy coded variables: one coded 1 = agree, 0 = disagree/don�t know, and another coded don�t know = 1, agree/disagree = 0. My thought was that I might be able to create a �don�t know� factor that would capture this response type, and make the other factors more interpretable in terms of agree/disagree.
However, when I put these variables in the model at the same time, I got error messages indicating that correlations between variables result in empty cells (i.e., no one can have a value of 1, 1). Is such a model with dummy coded dependent variables possible?
Linda K. Muthen
posted on Monday, June 04, 2007 - 11:09 am
I think there is a literature on how to treat "don't know". You may find some suggestions there on how to treat this category.
Categorical outcome methodology uses information from bivariate tables of outcomes. A zero cell in a bivariate table implies a correlation of plus or minus zero resulting in estimation problems.
Magda M�nica Martins Rocha
posted on Thursday, April 17, 2008 - 7:01 am
F1 by A B C D;
F2 by E F G H;
F3 by I J L M;
I USED WLSMV FOR ESTIMATOR, BUT IN THE OUTPUT FOR EACH FACTOR by... IN THE FIRST INDICATOR I CAN�'T GET THE EST./S.E. AND THE TWO-TAILED P-VALUE, I GET ALWAYS 999.000.
I'M VERY NEW IN mplus, WHAT AM I DOING WRONG PLEASE?
Linda K. Muthen
posted on Thursday, April 17, 2008 - 12:28 pm
The first indicator in fixed to one as the default to fix the metric of the factor. See the BY option in Chapter 16 of the Mplus User's Guide for a description of this. A fixed parameter has no standard error.
Magda M�nica Martins Rocha
posted on Friday, April 18, 2008 - 3:00 am
What a fool i am.
Thank you Linda.
Angela Wolff
posted on Wednesday, July 23, 2008 - 7:18 am
I'm trying to specify an interaction model using MPLUS 5.1
The interaction is between age(H9AGE, continous) and perceieved diversity (C1SAGEr, six categories). The dependent variable is categorical measure of emotional exhausion, depersonalization, and personal accomplishment
In the Mplus user guide (p.522) you list various ways of obtaining interactions for different variable types.
I have specified the model as follows:
PAgeH9 = C1SAGEr*H9AGE;
EE ON C1SAGEr H9AGE PAgeH9;
DP ON C1SAGEr H9AGE PAgeH9;
PA ON C1SAGEr H9AGE PAgeH9;
1. should the IV be correlated?
2. Is this the correct way to do this? Would it be better to use multigroup analysis to examine this interaction?
Angela Wolff
posted on Wednesday, July 23, 2008 - 9:22 am
Also, I was trying to run a model with multigroup analysis to test the interaction. However, I received this warning:
Based on Group 1: Group 2 contains inconsistent categorical value for B25EE: 6
Linda K. Muthen
posted on Thursday, July 24, 2008 - 9:20 am
1. Means, variances, and covariances of exogenous observed variables should not be part of the MODEL command. The model is estimated conditioned on these variables. If you want to know these values, ask for SAMPSTAT in the OUTPUT command.
2. You cannot use multiple group analysis when one of the variables in continuous. The way you specified it is fine.
Scott J. Peters
posted on Thursday, October 16, 2008 - 6:17 pm
I have a data set for categorical CFA involving 12 categorical variables on a single factor. I keep receiving the error:
When I look at the output correlation matrix, I see that one variable is correlated 999.00 with two other variables while all of the rest are fine. There are no odd values in my data set.
Any thoughts for why this is happening?
Linda K. Muthen
posted on Thursday, October 16, 2008 - 6:31 pm
It sounds like there is a problem computing the sample statistics. Please send your input, data, output, and license number to
Maren Winkler
posted on Monday, July 27, 2009 - 1:57 am
I'm doing CFA for a new developed test. It comprises 23 items which belong to 14 testlets. Hence, testlets comprise 1 to 4 items.
Items are scored as either right (1) or wrong (0). To account for dependencies among items belonging to one testlet, testlet scores are computed (sum of correct items per testlet).
Maximum testlet scores vary between 1 (for testlets with only one item) and 4 (for testlets with four items).
I've done CFA, using the CATEGORICAL option.
Because I was not sure whether the indicators need to have the same maximum value, I rescaled all testlets scores - 12 being the maximum number (all items correct) and 0 the minimum number. For testlets with four items, the testlet score can be 0, 3, 6, 9, 12; for testlets with three items 0, 4, 8, 12; for testlets with two items 0, 6, 12; for testlets with one item 0, 12.
Re-doing CFA my results differ in magnitude with regard to chi square, fit indices, factor loadings.
Which results to trust now? Is a common scale with the same maximum score for all testlets necessary or shall I leave the data as it is?
Thank you very much for your help!
Linda K. Muthen
posted on Monday, July 27, 2009 - 9:10 am
I think the approach described in the first paragraph is most transparent. The approach described in the second paragraph makes assumptions that may not be true. I would leave the data as is.
Maren Winkler
posted on Monday, August 24, 2009 - 3:59 am
there is a paper by Browne and Du Toit from 1992 ("Automated Fitting of Nonstandard Models", Multivariate Behavioural Research, 27 (2), 269-300)where they suggest estimating "Root Deterioration per Restriction RDR" for model comparison. The formula is
RDR = square root of ((delta chi� - delta df)/(N* delta df))
I'm using the WLSMV estimator for categorical data. Am I correct in assuming I should use the delta chi� and delta df I get in my output when I do the chi-square difference test using the DIFFTEST option for the above formula?
Thanks for your help!
Linda K. Muthen
posted on Monday, August 24, 2009 - 8:31 am
I think the paper by Browne and DuToit is for WLS not WLSMV.
Maren Winkler
posted on Tuesday, August 25, 2009 - 1:39 am
Is it not possible to use RDR for WLSMV? Or is there an alteration of RDR for WLSMV?
Linda K. Muthen
posted on Tuesday, August 25, 2009 - 7:38 am
No, this is not possible. For WLSMV, the chi-square test statistic and degrees of freedom are adjusted to obtain a correct p-value. Only the p-value should be used.
Cecily Na
posted on Friday, December 03, 2010 - 2:52 pm
Dear Linda,
I read a textbook and where there is an Mplus syntax sample.
It looks like they use a * for underlying distribution of a categorical or dichotomous indicator.
For example:
f1 by q1*-q12*
where q1-q12 are categorical variables. Do we need to use *?
Do I have to write
Criminal* ON drug
where criminal is a categorical variable (but not a latent factor)?
Linda K. Muthen
posted on Friday, December 03, 2010 - 4:23 pm
No, you don't need to use an asterisk. The way Mplus knows criminal is categorical is because you put it on the CATEGORICAL list.
Sabine Spindler
posted on Tuesday, May 03, 2011 - 7:48 am
Dear Dr.s Muth�n
I am trying to do a multiple groups comparison, however, I get the following error:
Based on Group 0: Group 1 contains
inconsistent categorical value for Q61RAW: 1
What exactly does it tell me?
Thank you!
Linda K. Muthen
posted on Tuesday, May 03, 2011 - 7:54 am
It tells you that the number of categories for Q61RAW is not the same in both groups. Check your data. The groups must have the same number of categories for the categorical variables.
Sanja Franic
posted on Wednesday, November 16, 2011 - 1:32 am
Hi, I get the following warning when trying to run a multigroup analysis on categorical variables:
Based on Group 1: Group 2 contains
inconsistent categorical value for Y21: 5
The observed variables are all defined as categorical. Could you maybe give me a hint as to what this warning could indicate?
Linda K. Muthen
posted on Wednesday, November 16, 2011 - 2:16 pm
Apparently, y21 does not have the value 5 in group 2. With weighted least squares, each group must have the same categories for categorical variables. You could collapse categories in group 1. With maximum likelihood estimation, you can use the * setting of the CATEGORICAL option.
Sanja Franic
posted on Wednesday, November 16, 2011 - 10:08 pm
Thanks!! I hope I can do the same/similar with WLSMV estimation.
Sarah Ryan
posted on Friday, September 21, 2012 - 1:04 pm
I just want to confirm something and I have searched the discussion board and web, but can't find an explicit answer.
Is it correct that the output section "UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES" provides the model estimated (as opposed to observed) proportions and counts?
Linda K. Muthen
posted on Saturday, September 22, 2012 - 3:35 pm
The are not model estimated values. They are sample statistics.
Sarah Ryan
posted on Monday, September 24, 2012 - 6:13 am
Okay, I originally thought so, but I get "fractions" of people in the sample counts and a colleague was insisting these must be estimates given that the counts were not whole numbers.
So, the ".XX" on counts is just a function of the proportions also being fractional?
Thanks for indulging me on this rather basic question.
Linda K. Muthen
posted on Monday, September 24, 2012 - 11:54 am
Please send the output and your license number to
so I can exactly what you are seeing.
muhammed erko�
posted on Tuesday, October 02, 2012 - 7:12 am
I am a student in Ege University, TURKEY. I managed to generate data sets with continious indicators. But my homework is generating data sets for my friends' homework using Mplus. The programme is only available in computer labs and i usually have limited time to use. I am trying to generate data sets with ten items; 6 item for factor 1 and 4 items for factor 2 which are on 5 point likert scale. I know it sounds simple but I couldn't.
Here is my syntax:
names = y1-y10;
nobservations = 200;
nreps = 25;
seed = 2344887;
generate = y1-y10 (5 p);
categorical are y1-y10;
repsave = all;
save = odev*.dat;
f1 ON y1-y6*.65;
f2 ON y7-y10*.70;
f1 WITH f2*.2;
As you see I can't reach the solution. Would you please help on my syntax or show me a simple example.
Linda K. Muthen
posted on Tuesday, October 02, 2012 - 10:42 am
See mcex5.2.inp. It generates data for two factors with binary indicators. It is available on the website.
muhammed erko�
posted on Wednesday, October 03, 2012 - 12:54 am
Thanks for your help.
posted on Wednesday, November 14, 2012 - 7:31 am
I would like clarification regarding some issues in the interpretation of path models using WLSMV and theta parameterization. In my model:
Model indirect:
X1-X3 are binary and Y is continuous. If I'm right in my interpretation the coefficients for Y ON X1-X3 are normal linear regression coefficients and X2 ON X1 and X3 ON X2 are probits.
1. If that's right how do I interpret the indirect effect when it is the product of two probit coefficients and a linear coefficient?
2. Also if I wanted to standardize the results which solution would I use - StdYX or Std or are neither appropriate?
3. Using WLSMV (theta) can any of the normal fit statistics be used to assess model fit?
Many thanks.
Linda K. Muthen
posted on Wednesday, November 14, 2012 - 11:58 am
Yes, y is linear and the x's are probit if you are using the default estimator WLSMV.
1. Linear
2. StdY
3. Yes.
posted on Thursday, November 15, 2012 - 1:52 am
Thanks Linda (forgive me as I'm new to Mplus/SEM)
Re: 2. When asking for the standardized output it only gives me StdYX and Std. Is there a way to get StdY? If not is it sufficient to just report the unstandardized estimates?
Re: 3. Which particular fit statistics are safe to use when using WLSMV (theta) and do you know of a reference to read on this?
Linda K. Muthen
posted on Friday, November 16, 2012 - 12:12 pm
Divide StdYX by the standard deviation of x.
I know of no paper that has studied this. I would use the same fit statistics as for Delta which are the ones provided in the results section.
Trang Q. Nguyen
posted on Friday, November 30, 2012 - 1:38 pm
I am running a structural model where I have 10 3-point likert indicators that are theorized to measure 4 constructs, 3 being predictors and 1 being the outcome. I want to declare these variables as categorical ordinal. However, one of the predictor constructs has only one indicator, so if I just include it as an independent variable, it cannot be declared as an categorical ordinal. Is it OK to include a factor for it (to make it a y so I can declare in as categorical) and fix both the loading and variance of that one-indicator factor at 1? Would this be equivalent to using the underlying continuous version of the categorical variable?
Below is my input. The variable in question here is var7.
NAMES = var1-var10;
USEVARIABLES = var1-var10;
CATEGORICAL = var1-var10;
f1 BY var1* var2 var3;
f2 BY var4* var5 var6;
f3 BY var7;
f4 BY var8* var9 var10;
f4 ON f1 f2 f3;
Thanks much!
Linda K. Muthen
posted on Friday, November 30, 2012 - 3:21 pm
Yes, this would be equivalent to doing that. I'm not sure why you would want to do this given that you make unnecessary normality assumptions. I would use the observed variable as the covariate or create a set of dummy variables to represent the categories and use them as covariates.
Trang Q. Nguyen
posted on Saturday, December 01, 2012 - 8:31 am
Thank you. Yes, I need to think about whether to do this or to use dummy variables. The pro of using an assumed normal continuous version of var7 is the result will be simple -- just one regression coefficient, similar to one coefficient for each of f1 and f2. Conceptually these are three things hypothesized to influence f4, and it would be nice to have three coefficients instead of four. The con is introducing inaccuracy through normality assumption.
Var7 has three ordinal categories and there are roughly the same number of people in each category. Does this suggest that it is perhaps OK to assume normality for the underlying continuous variable? Or should I still worry that it might be skewed and the equal proportions could be just an artificial result of the thresholds?
In practice, is it something that is sometimes done, to treat an ordered categorical independent variable this way? Or is it a no no?
Thanks much for advising me on this. I am quite inexperienced in SEM.
Bengt O. Muthen
posted on Saturday, December 01, 2012 - 5:09 pm
I vote for treating the observed 3-category Var7 as a continuous variable - that is, as a regular covariate. I say that because you say its distribution is symmetric and because when you treat it as a regular covariate you don't introduce an assumption of underlying normality.
Trang Q. Nguyen
posted on Monday, December 03, 2012 - 7:27 am
Thank you so much!
So that I am crystal clear, your suggestion is to include the raw variable as a continuous variable (ie take it out of CATEGORICAL =), and not introduce that f3 factor?
Bengt O. Muthen
posted on Monday, December 03, 2012 - 1:37 pm
Trang Q. Nguyen
posted on Monday, December 03, 2012 - 2:01 pm
Thank you!
Maren Formazin
posted on Wednesday, February 13, 2013 - 8:10 am
is it possible to use the AUXILIARY (M) command with categorical data? I get an error message when trying but I seem to recall it was possible with Mplus 5? Is there a way around this problem?
Linda K. Muthen
posted on Wednesday, February 13, 2013 - 10:34 am
All variables on the AUXILIARY list are treated as continuous. There may not have been an error message in Version 5.
Maren Formazin
posted on Friday, February 15, 2013 - 1:46 am
sorry, my question was not clear: not only my auxiliary variables, but also my indicators of the latent variable are categorical; hence, I use the WLSMV estimator.
Is the AUXILIARY (M) option not possible with categorical indicators?
Linda K. Muthen
posted on Friday, February 15, 2013 - 10:46 am
AUXILIARY (m) is available only for continuous variables.
Juliana Werneburg
posted on Wednesday, March 13, 2013 - 11:55 am
I would like to model some kind of twin model: that is two latent variables, each measured by 3 binary indicators. Measurements might be parallel. I have other covariates to add.
I tried to model this by factor analysis, that is i have two continuous latent variables measured by 3 indicators each. Though i have a grouping variable. It results in very good model fit (all Chi�, RMSEA, TLI, Chi� difference tests). So i resume the indicators are good measurements of some underlying factor.
But, if I try to fit the model using LCA as a framework, that is the latent variables shall both be binary classes (with 3 the same result), model fit turns out to be awful.
Is there any reasoning why this doesn't work, although the indicators seems to be fine? Is there anything to try out or to look at as an explanation?
Thank you very much for your help,
Linda K. Muthen
posted on Wednesday, March 13, 2013 - 6:02 pm
With the LCA for twins, you should have two latent class variables, one for twin a and one for twin b. Each one should have two classes. You need to use PARAMETRIZATION = LOGLINEAR and use WITH to correlate the two categorical latent variables, for example,
c1 WITH c2;
posted on Wednesday, April 24, 2013 - 6:04 pm
Hi Dr. Muthen,
May I ask a quick question?
I know strictly speaking, we should treat Likert-type (e.g., 1-5 point) item level data as ordinal and thus in SEM we should use estimator=MLSMV.
But it seems that many people treat such scales as continuous. Thus my question is, could we still treat such items as continuous, but use WLSMV as estimator, to deal with data skewness at item level?
Thank you so much!
Linda K. Muthen
posted on Wednesday, April 24, 2013 - 6:33 pm
You can treat them as continuous as long as they don't have floor or ceiling effects. If they do, I would treat them as categorical because that methodology can handle the floor and ceiling effects.
You can't use WLSMV without having at least one categorical variable in the model.
Lois Downey
posted on Thursday, May 01, 2014 - 11:44 am
I have a situation in which the univariate proportions/counts listed in the output do not make sense.
If I run an unclustered model with the full sample, the univariate values are correct.
If I run a clustered model with the full sample, the univariate values continue to be correct.
If I select a subsample with the USEOBSERVATIONS command and run an unclustered model, the univariate values continue to be correct -- although, as expected, smaller than for the full sample.
However, if I select a subsample with the SUBPOPULATION command and run a clustered model, the univariate values are incorrect. In fact, the counts aren't even integers.
What might I be doing incorrectly?
Linda K. Muthen
posted on Thursday, May 01, 2014 - 11:51 am
Send the USEOBSERVATIONS and SUBPOPULATION outputs and your license number to
jane shen
posted on Friday, June 27, 2014 - 12:24 pm
When sampling weights added in the model, what is "UNIVARIATE PROPORTIONS AND COUNTS FOR CATEGORICAL VARIABLES"?
They are no longer sample statistics for the raw data, nor for the weighted data.
Mplus version: 7.11
Analysis: ESTIMATOR = WLSMV;
Bengt O. Muthen
posted on Sunday, June 29, 2014 - 11:10 am
Please send your input, output, and data to
Samuli Helle
posted on Wednesday, May 13, 2015 - 11:30 am
I have a question of how to interpret and to best standardize the estimates of the model below. My main interest lies on the regression coefficient of continuous time survival outcome Y on factor F, which is measured by one count (marker) indicator (X1) and two binary indicators (X2, X3).
TIMECENSORED = cens;
1) Not sure how the factor F is scaled: a count indicator X1 is used to set the scale, but based on the model output, the link function used is logit. Shouldn�t the link in count outcomes be log instead? So, in this case, how to interpret the factor scale?
2) Given the above, what�s the best way to standardize here? I know that it makes no sense to standardize the binary indicators, but should I use STDYX standardization when interpreting the regression coefficient of Y on F?
Bengt O. Muthen
posted on Thursday, May 14, 2015 - 10:53 am
Set the metric in f by fixing its variance at 1 and free the first loading.
The count link is not mentioned in the Mplus output but it is the usual elog link of counts.
So then you don't need to worry about standardizing.
Samuli Helle
posted on Saturday, May 16, 2015 - 5:01 am
Thanks Bengt. I did as suggested and the results changed a bit - the regression coefficient of Y on F had a different sign now (although non-significant in both cases). Is this what to expect?
Moreover, as someone not too familiar with latent variables, does that scaling approach change the interpretation of the latent variable (e.g. is the latent still measured with "error" although its variance is fixed)?
Bengt O. Muthen
posted on Saturday, May 16, 2015 - 8:06 am
The sign should not change if you do it right. If yuo like you can send the 2 outputs (for different metric settings) to support along with your license number.
Q2. No; same interpretation.
Samuli Helle
posted on Saturday, May 16, 2015 - 10:12 am
The code I am using is:
Bengt O. Muthen
posted on Monday, May 18, 2015 - 12:26 pm
Send the 2 outputs that show the sign change to support along with your license number.
Kristy Snyder
posted on Tuesday, January 12, 2016 - 12:57 pm
A SEM with 2 continuous latent factors measured by y (cont.), u (count), & n (nominal)
n_a & n_b have 4 categories n_c has 3
DEFINE: n_a1 = n_a == 1;
n_a2 = n_a == 2;
n_a3 = n_a == 3;
n_c2 = n_c == 2;
1) How can I evaluate the contributions of each set of dummy variables?
MODEL: f1 BY y1 - y4 u1 - u3;
f2 BY y5 (n_a set) (n_b set) (n_c set);
outcome ON f1 f2;
2) The f2 indicators measure a common construct but the (n_a set) measure a different facet of that construct than the other f2 indicators. If it is uncorrelated with the other indicators it won�t load highly on that factor but it is an important component of the construct so I want to be sure that its influence on the outcome variables isn�t underestimated. Would you suggest making an interaction term?
f2 BY y5 (n_b set) (n_c set);
f2int | (n_a set) XWITH f2;
outcome ON f1 f2int;
Would using the f2int be appropriate as a measure of the main effect of a single construct or would it be interpreted as a 3 way interaction?
Bengt O. Muthen
posted on Wednesday, January 13, 2016 - 12:33 pm
1) I don't think you should split up the nominal outcomes into dummy variables. Do the factor analysis with them declared as nominal.
2) Perhaps you want to use a bi-factor model where the "different facet" is a "specific factor" different from the "general factor".
I don't see how interactions would help.
Yanick Brice
posted on Saturday, January 16, 2016 - 5:54 am
For earlier versions of Mplus, if you have a nominal independent variable, you must create a set of dummy variables. Is this statement still true with the most recent version of Mplus (7+). A lot of my IVs are nominal (up to 6 categories), is there an efficient way of handling them in Mplus in my two-level logistic regressions? Thank you.
Bengt O. Muthen
posted on Saturday, January 16, 2016 - 6:36 am
Nominal IVs need to be turned into dummy variables.
Pia H.
posted on Thursday, March 24, 2016 - 5:52 am
I'm having a quite confusing error message:
Based on Group 2: Group 1 contains
inconsistent categorical value for SUPPORT_R: -201
I have had those ones before and got rid of them simply by collapsing categories; in this variable, however, all categories have been chosen in group 1 and group 2 (I checked); moreover, I don't understand why it says -201 instead of the categories available (1-5).
Could you give me a hint what this may mean?
Thank you very much!
Linda K. Muthen
posted on Thursday, March 24, 2016 - 8:17 am
It sounds like you are not reading the data correctly.
Owis Eilayyan
posted on Friday, November 25, 2016 - 12:43 pm
Hello Dr Muthen,
I am working on SEM model and I have many categorical indicators. I would like to ask if there is a minimum number of observations that should I have in each category.
Thank you,
Bengt O. Muthen
posted on Friday, November 25, 2016 - 3:18 pm
No, but see our FAQ:
Estimator choices with categorical outcomes
Owis Eilayyan
posted on Saturday, November 26, 2016 - 4:16 pm
Thank you,
The document was very helpful
Diane Martinez
posted on Friday, December 23, 2016 - 2:55 pm
Hi I am having a bizarre experience in MPlus not correctly recognizing binary variables. Basic univariate descriptive analysis conducted when my Stata file was converted to a .dat file showed my binary variables as being 0 minimum value (no) and 1 maximum value (yes).
However, for the code:
Basic descriptives for Instrumental construct with binary indicators WITHOUT survey weights
Data: File is youngadultPATHDec23.dat;
NAMES = flavors smell helpquit socialize alttoquit;
CATEGORICAL = flavors smell helpquit socialize alttoquit;
Missing are all (-9)
TYPE = Basic;
I keep getting the following error message:
Categorical variable FLAVORS contains 3887 categories.
This exceeds the maximum allowed of 10.
How can I get MPlus to recognize my variables as binary instead of 3887 categories (which is my total sample size)?
Linda K. Muthen
posted on Friday, December 23, 2016 - 2:59 pm
You either have more variable names in the NAMES list than columns in the data set, you have blanks in the data set which are not allowed with free format dat, or you are saying that the id variable is the categorical variable by the placement of the variable name on the NABES list. All of these will cause the data to be read incorrectly.
Diane Martinez
posted on Friday, December 23, 2016 - 3:03 pm
Thank you so much Dr. Muthen for your immediate response!! I greatly appreciate it and will troubleshoot this further.
Happy Holidays!
Kristin Gustavson
posted on Monday, October 30, 2017 - 7:55 am
Hi, I am running an analysis with categorical indicators of a latent variable (MLR, log-link). I regress this latent variable on a predictor and am wondering how to interpret the regression coefficient. Should I see it as a logistic regression since the indicators are categorical, or is it linear regression since the latent factor is not categorical? I also wondered why the STDY and the STDYX regression estimates are the same. The predictor is a dichotomous variable.
Bengt O. Muthen
posted on Monday, October 30, 2017 - 4:33 pm
A categorical indicator has a logit/probit regression on the factor. The factor has a linear regression on the predictor because the factor is continuous. In the first type of equation STDY and STDYX are the same because there is no x. In the second type of equation they are different.
Hillary Gorin
posted on Tuesday, December 19, 2017 - 11:58 am
What is the syntax for a factor mean for categorical data?
Is it this?
Bengt O. Muthen
posted on Tuesday, December 19, 2017 - 3:34 pm
Yes, so same as with cont's variables.
Sophie Potter
posted on Tuesday, May 08, 2018 - 1:56 am
I am having some trouble running a latent growth model with gender added as a predictor. I get the following error messages:
*** ERROR in MODEL command
Variances for categorical outcomes can only be specified using
PARAMETERIZATION=THETA with estimators WLS, WLSM, or WLSMV.
Variance given for: WOMEN
*** ERROR in MODEL command
Covariances for categorical, censored, count or nominal variables with other observed variables
are not allowed. For covariances between categorical variables, specify PARAMETERIZATION=RESCOV
in the ANALYSIS command. Problem with the statement:
*** ERROR in MODEL command
Covariances for categorical, censored, count or nominal variables with other observed variables
are not allowed. For covariances between categorical variables, specify PARAMETERIZATION=RESCOV
in the ANALYSIS command. Problem with the statement:
The following MODEL statements are ignored:
* Statements in the GENERAL group:
I am not able to use 'PARAMETERIZATION=RESCOV' because this can only be used with 'TYPE= MIXTURE', however, in order to implement the TSCORES in my model i need to use TYPE= random.
Linda K. Muthen
posted on Tuesday, May 08, 2018 - 6:00 am
Please send the full output and your license number to
posted on Monday, August 06, 2018 - 3:10 am
Hi Drs,
I am experiencing trouble running a measurement invariance test using categorical indicators, as I keep encountering the following error message "Based on Group 1: Group 2 contains inconsistent categorical value for SS1F05I: 1".
When looking at the data, it turns out that respondents in Group 1 did not choose the answer 1 (on a 4 points Likert scale) while some respondents in Group 2 did.
I have read previously that one of the solution would be to collapse the categories. However this not practical in my case because I have several groups and some have missing categories in other places (for instance in one group, nobody picked either answer 1 or 2, meaning that I would have to collapse the first 3 categories together to avoid this problem, which is a big loss of information).
I have also tried using a Maximum Likelihood estimator (MLMV) along with the option (*) for the CATEGORICAL command, as shown here:
However, this doesn't seem to solve the problem, and I get an error message saying that the MLMV estimator is not compatible with the DIFFTEST option asked in the OUTPUT command.
Do you know any way that would allow me to avoid the issue of non-existing categories in some cases while being able to obtain the DIFFTEST output?
Thank you !
Bengt O. Muthen
posted on Monday, August 06, 2018 - 3:27 pm
Use the * option together with MLR. Chi-square difference testing with MLR is discussed here
posted on Tuesday, August 07, 2018 - 9:41 am
Dear Dr Muthen,
Thank you for your answer. I have tried your solution, but implementing the (*) does not seem to work as I still have the following message:
Based on Group 1: Group 2 contains
inconsistent categorical value for SS1F05I: 1
Can you confirm the way I coded the (*) option is correct (previous post)? I can't seem to find applied examples of it.
Also, the ouput recommends me to use the KNOWNCLASS option once I try to use the MLR estimate, which I did:
*** ERROR in ANALYSIS command
ALGORITHM=INTEGRATION is not available for multiple group analysis.
Try using the KNOWNCLASS option for TYPE=MIXTURE.
However, I am not sure the results obtained correspond to a test of measurement invariance.
Do you know whether MI tests are possible using KNOWNCLASS ? And if so, do you have an idea of resource/reference where that has been done ?
Thanks a lot and pardon my beginner level in Mplus.
Bengt O. Muthen
posted on Tuesday, August 07, 2018 - 11:03 am
We need to see the full output - send it together with the data to Support along with your license number.
MI tests are possible using Knownclass.
Snigdha Dutta
posted on Wednesday, August 22, 2018 - 5:37 am
This is a really basic question, however, I need some clarification.
I've read that >5 Likert scale data can be considered as continuous as hence the use of MLR/FIML as estimators for non-normal and missing data.
I have 8 scales, of which 7 have >5 likert scale points but one (which is an IV) has 4-point Likert scale.
In that case does one consider the data to be categorical/ordinal and use WLMV as an estimator for non-normal and missing data?
Bengt O. Muthen
posted on Wednesday, August 22, 2018 - 4:43 pm
It's less a matter on the number of categories and more a matter of whether the variables have strong floor or ceiling effects. See e.g. Muthen & Kaplan (1985):
Snigdha Dutta
posted on Thursday, August 23, 2018 - 2:28 am
Dear Bengt,
Thanks for your reply. Unfortunately, that paper went over my head due to its purely statistical language and explanation. Could you explain it in a lay language form for an applied social science researcher?
Thank you!
Bengt O. Muthen
posted on Thursday, August 23, 2018 - 6:30 pm
Same answer - It's less a matter on the number of categories and more a matter of whether the variables have strong floor or ceiling effects. When you have say 25% or more at the lowest/highest category, you want to specify the variable as Categorical.
Javed Ashraf
posted on Thursday, March 14, 2019 - 1:29 am
I wanted to ask that can we perform simple logistic regression , with fully informative priors for categorical predictors using Bayes estimator in MPlus?
Bengt O. Muthen
posted on Friday, March 15, 2019 - 11:30 am
Yes, this is possible - assuming you are referring to the slope and intercept parameters.
Alexandra Alipan
posted on Monday, March 25, 2019 - 1:37 am
I am trying to test measurement invariance on one of my variables of interest - Brief Symptom Inventory which has 53 items. I am treating the variable as ordered-categorical (5-point likert scale) and using the WLSMV estimator. However, when running the analysis it comes up with the warning:
Based on Group 2: Group 3 contains
inconsistent categorical value for BSI4: 5
I don't want to collapse response options - is there any alternative that you suggest to be able to proceed with invariance testing?
Thank you!
GROUPING IS rec_lev (1= never 2 = target 3 = victim);
model = configural scalar;
Bengt O. Muthen
posted on Monday, March 25, 2019 - 4:57 pm
When you use ML, you have the possibility of using the * option described on pages 606-607 of the V8 UG.
Alexandra Alipan
posted on Monday, March 25, 2019 - 9:20 pm
Hi Bengt,
Thank you for your reply. What about when using WLSMV? Can the * option be used?
Thank you
Bengt O. Muthen
posted on Tuesday, March 26, 2019 - 5:29 pm
No, it's available for only ML.
Ryan Veal
posted on Monday, September 09, 2019 - 8:58 pm
Hello Professor Muthen,
In CFA using WLSMV, the Mplus Output in v8.3 provides an "Optimum Function Value for Weighted Least-Squares Estimator" alongside model fit indices.
What is this? I cannot find anything in the Mplus User's guide on this value.
Can you please direct me on where to find information on this?
Thank you,
Bengt O. Muthen
posted on Wednesday, September 11, 2019 - 11:33 am
It is the value of the fitting function we try to minimize when we have arrived at the best point in the iterations. Zero is perfect fit. See Section 4, eqn (99) of the Tech appendices for version 2 on our web site:
If you ask for TECH5, it is shown as the bottom left value.
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Bowles, D and Cooper, C L (2009) Employee Morale: Driving Performance in Challenging Times. Palgrave Macmillan, Basingstoke. ISBN 9780230579422
Bozkurt, Ödül and Clegg, Jeremy and Grugulis, Irena (2009) 'No place to hide' : the realities of leadership in UK supermarkets. In: 27th International Labour Process Conference, April 6-8 2009, Edinburgh. (Unpublished)
Cooper, C L and Lu, L and Kao, S (2009) Work resources, work-to-family conflict and its consequences: a taiwanese-british cross-cultrual comparison. International Journal of Stress Management, 16 (1). pp. 25-44. ISSN 1072-5245
Cooper, C L and Lu, L and Kao, S and Chang, T (2009) Cross cultrual differences on work-to-family conflict and role satisfaction: a Taiwanese-British comparison. Human Resource Management Journal, 49 (1). pp. 67-85. ISSN 0954-5395
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Parsons, M C and Rose, M B (2009) Lead User Innovation and the UK Outdoor Trade since 1850. Working Paper. Institute for Entrepreneurship and Enterprise Development, Lancaster University.
Richard, P J and Devinney, T and Yip, G and Johnson, G (2009) Measuring organizational performance: towards methodological best practice. Journal of Management, 35 (3). pp. 718-804. ISSN 0149-2063
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Never Give Up On Your Dreams: Big Boy Tries To Run The 100 Meter Dash & Gets Smoked!
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Kristen Stewart swears a lot. This instantly makes her a human being rather than the tabloid icon she's unwillingly become at age 22 thanks to the Twilight saga and its constant media presence.
Stewart's at the Toronto Film Festival with On The Road, an adaptation of Jack Kerouac's classic beat novel in which she plays Marylou, the sexually adventurous child bride of the charismatic Dean Moriarty. (Yes, there are nude scenes. No, they aren't explicit.) She's been paired with Garrett Hedlund, who plays Moriarty, and the two of them are at their most animated when discussing the freewheeling, improvisational style director Walter Salles encouraged during the rehearsal process.
"I tortured myself in the most amazing, wonderful way for four weeks," she says, "and then as soon as the four weeks were done it was like, 'You need to stop thinking, because if you don't you're gonna regret this entire experience. You're gonna look back and say: I fucked up. I thought too much.'"
"We'd gotten so many wonderful stories," Hedlund says. "From real-life characters like Al Hinkle, who was in the book as Ed Dunkel; Neal [Cassady]'s son told me a lot of wonderful stories, we'd read plenty of stories from Carolyn Cassady's Off The Road, wonderful stories from LuAnne Henderson's audiotapes. We always had stories to go for if there was space for improvisational infusion."
Stewart says the fact that she was playing a real person – the aforementioned Henderson, who was the basis for Kerouac's fictional Marylou – made her a little more careful about her own improvisations.
"It's always fun to have freedom and have, like, happy accidents where you go, 'Wow, that's cool, I didn't expect that,'" she says. "But when you're playing somebody who's [actually] existed, you know.…" And she stops herself, rethinking her position on the fly.
"I don't want to discredit what it feels like to play a character who's been written by somebody," she continues. "You feel just as responsible to the writer and to everyone who's been affected by that character."
There is no doubt in my mind that she's referring to Bella Swan. And I have to respect her instincts; given how many millions of people worship the Twilight movies and could turn on her in a second for a valid observation taken out of context, it's the savvy thing to do. But it's also crap, and she knows it, because as soon as she's finished that statement, Stewart returns to her real point and her energy shoots right back up.
"I've played Joan Jett," she says, "and because she was on set every day I couldn't improv. I couldn't. Everything I said, I spoke to her about it. You know – you can't put words in their mouths unless you know. Unless you really feel it, and it's coming from the right place."
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Saturday, June 30, 2007
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"The modern conservative is engaged in one of man's oldest exercises in moral philosophy; that is, the search for a superior moral justification for selfishness." - John Kenneth Galbraith.
Posted by Kel at 9:51 AM
Labels: Democracy in the US, Fox News, US Election 2008
That is why the greatest danger of all is to allow new walls to divide us from one another.
The walls between old allies on either side of the Atlantic cannot stand. The walls between the countries with the most and those with the least cannot stand. The walls between races and tribes; natives and immigrants; Christian and Muslim and Jew cannot stand. These now are the walls we must tear down.
This work is licensed under a Creative Commons License.
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