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Growth Models with Censored Data?
Mplus Discussion
Growth Modeling of Longitudinal Data
Dan Bauer
posted on Tuesday, July 11, 2000 - 10:18 am
I am hoping to use MPlus to do some growth modeling with censored data. The data cover credit debt over 4 time points. The censoring is on the low end of the distribution, at $500. The censoring threshold is invariant across the four time points.
It seems like a growth model of these data would be a relatively straight-forward extension of the case where data are categorical. That is, both analyses would proceed from a polychoric correlation matrix and incorporate information on thresholds.
My question is whether I am correct that growth modeling can be done with censored variables, and, if so, whether MPlus can do it. References to relevant texts or examples would also be appreciated.
Bengt O. Muthen
posted on Tuesday, July 11, 2000 - 3:23 pm
LISCOMP, the precursor to Mplus, allowed censored variables by Tobit modeling but we felt that this used too strong assumptions and did not include it in Mplus. Although not optimal, I would suggest treating your variables as ordered polytomous, categorizing debts above $500 into a couple of categories. A reference related to this is (although not in a longitudinal context):
Muthén, B., & Speckart, G. (1983). Categorizing skewed, limited dependent variables:Using multivariate probit regression to evaluate the California Civil Addict Program. Evaluation
Review, 7, 257-269. (#3)
Future developments will probably handle these kinds of variables in a better way.
Dan Bauer
posted on Tuesday, July 18, 2000 - 5:22 am
Thank you for responding so promptly to my question about censored data. I wonder if you would not mind expanding your comments. My colleagues here feel that rendering censored data into polytomous categories is losing valuable information. Further, either treatment of the variable (ordinal or censored) requires the assumption that there is an underlying normal distribution. Is there an assumption peculiar to censored data that is particularly suspect?
posted on Tuesday, July 18, 2000 - 7:43 am
The assumption of censored-normal Tobit that I find limiting is that the coefficients for the covariates' influence on the probability of censoring are proportional to the coefficients of the covariates' influence on the amount observed when not censored. The ordered polytomous model would seem to share this limitation in this application. An alternative approach has been taken using two-part (semicontinuous) modeling. You may find it useful to read a recent paper on this by Olsen and Schafer at Penn State. It can be found on the web site
This paper is being revised for JASA.
posted on Friday, August 06, 2004 - 8:49 pm
Great bulletin board here! I have a growth modelling question with some survival aspect involved.
I have a continuous variable (say a functional disability score) which is supposed to have been measured at three times, say times 0, 2 and 6. However, some individuals die in between times 2 and 6, and therefore have no measurement. These deaths occurred while there was still function, so I am unwilling to plug in a zero score for them, as has been suggested elsewhere.
I am interested in primarily the traditional growth modelling aspect, in which I would like to characterise the latent growth curves (ie linear slopes) across people. My question is, how do I handle the deaths in this analysis?
I guess one way is to assume their time 6 measurements are missing at random (conditional on observed trajectories), and therefore "automatically" accounted for in a likelihood based analysis?
Or is there a more elegant method in Mplus which can somehow jointly model both the longitudinal measurements and the survival process? With this,survivors would be censored at time 6, but those dying would have their time of death recorded (exactly) but would have no functional disability measurement at that exact death time.
Many thanks in advance.
posted on Sunday, August 08, 2004 - 11:57 am
MAR would seem a good first step, letting the scores from the first 2 time points predict the time 6 missingness.
You could try more advanced, non-ignorable missing data modeling in line with the movie of my Spring 2004 UCLA course:
- see the Lecture 17 handout (under handouts). For instance, you can try to use the growth slope as a predictor of time 6 missingness.
There have been several recent articles on joint survival modeling and growth modeling in the biostatistics literature. Mplus can not yet do continuous-time survival, but can do very general discrete-time survival modeling.
Michael J. Zyphur
posted on Saturday, November 19, 2005 - 8:03 pm
Hi Linda (sorry for two posts, but I want to keep things organized under the right categories),
Running a censored LGM with values censored (above) at 4.0, I am having problems running a model with freely estimated slope-factor loadings. I.e.,
i s |
3@* 4@*
I am thinking this kind of a model might be difficult to estimate with censored data. Is this true?
Thanks again!
Linda K. Muthen
posted on Sunday, November 20, 2005 - 9:59 am
The way you specify free time scores is as follows:
i s |
3* 4*;
I am not sure how the program would interpret @*
This type of model should not be difficult with censored data unless the data are perhaps not truly censored and therefore that model is not appropriate for the data.
Xuecheng, Liu
posted on Monday, March 06, 2006 - 12:40 pm
Hi, Muthén and Muthén,
Is it possible (with command "CENSORED" in ANALYSIS: TYPE=MIXTURE) that we specify some variables to be censored from below and above SIMULTANEOUSLY?
Many thanks!
Linda K. Muthen
posted on Monday, March 06, 2006 - 1:29 pm
Variables can be censored from above or below but not both.
Richard Gibson
posted on Tuesday, March 25, 2008 - 4:11 am
Is the model unstable? N = 88 facilities; t = 4 (collapsed over 24 months to 6 month blocks) ; measure y is rate of event per 100 beds; event is rare so lots of zeros => censor inflated.
Model 5
i s |
i2 s2 | y1#
i s on StudyG bt1 bt2;
Model 6
i s s2 on StudyG bt1 bt2;
i2*0.757; s2*0.121;
Model 7
i s i2 s2 on StudyG bt1 bt2;
i2*0.757; s2*0.121;
I am puzzled by the changes in the estimates and standard errors between the three models and would appreciate direction in understanding why they change sufficient to change the inference with the intercept and slope on StudyG. I am worried that the instability suggests more than one maxima.
Linda K. Muthen
posted on Tuesday, March 25, 2008 - 9:14 am
When you leave out paths that are not zero, your model may be misspecified. I would trust Model 7.
Richard Gibson
posted on Tuesday, March 25, 2008 - 3:56 pm
Thanks. The earlier models were just steps along the way towards model 7 and the results of model 7 make sense so I am glad that it is the trustworthy one!
Misspecification can certainly have a powerful effect!
Mariam Dum
posted on Monday, April 21, 2008 - 1:55 pm
I was wondering if you can provide me wtih a good reference on censored data for growth mixture modeling?
Linda K. Muthen
posted on Monday, April 21, 2008 - 4:50 pm
When you say censored, do you mean censored normal data or right censoring as seen in survival models?
Tabitha McKinley
posted on Friday, January 02, 2009 - 5:12 pm
I am working on a dissertation regarding special education student populations and am using data censored from below in order to show ways to display the students' growth (or lack thereof) when they are not adequately answering standardized test items. I have looked at both the censored and censored-inflated models in the Mplus manual, but am having some trouble conceptually comprehending the real expected differences in path values between the two models.
Any help please??? Thanks!
Bengt O. Muthen
posted on Friday, January 02, 2009 - 5:39 pm
Before I answer that, have you considered two-part growth modeling? See the Mplus web site for references (under Papers and under Growth). The Olsen-Schafer article argues for two-part over censored growth modeling.
Tabitha McKinley
posted on Saturday, January 03, 2009 - 5:15 am
I have read the paper, and from what I can determine, it seems that X variables with negative measurement error scores are treated as censored, while those with positive measurement error are treated as noncensored. In addition, their model is estimated using categorical variables, and I am analyzing continuous observations.
Bengt O. Muthen
posted on Sunday, January 04, 2009 - 4:55 pm
I don't think you are reading Olsen-Schafer correctly. Their article is about a continuous outcome which has a strong floor effect (piling up at zero). They turn that into what amounts to a parallel process model for the binary part and the continuous part. See how we describe it in the handout for the short course Topic 4 on our web site. See also the 2 two-part papers under Papers, Two-Part... on our web site.
Linda K. Muthen
posted on Tuesday, February 03, 2009 - 4:28 pm
When you change the zeros to ones, there is more censoring because there were already some ones. This changes the data and therefore the model may have convergence problems.
Tabitha McKinley
posted on Tuesday, February 03, 2009 - 4:53 pm
Thanks for the rapid response. I will be sure to change the entire structure of the data for the next time I run the model.
I am also preparing to create a dataset which mimics the one in the example you provided. Is there a threshold for the amount of censored observations that can be included before I experience convergence problems?
Linda K. Muthen
posted on Tuesday, February 03, 2009 - 5:42 pm
Each example in the user's guide has a Monte Carlo counterpart. This would be a good place to start if you are generating data. You can try various amounts of censoring in this way to see when it becomes problematic.
Tabitha McKinley
posted on Wednesday, February 04, 2009 - 8:32 am
In yout first post you stated that changing the zeros to ones adds to the amount of censoring and causes convergence problems.
Is there a specified amount of censoring that is preferrable when trying to run this model? I was trying to find something about this in the manual and saw nothing specific about how much censoring is "too much" for the model.
Linda K. Muthen
posted on Wednesday, February 04, 2009 - 9:31 am
I don't know how much censoring is too much.
Tabitha McKinley
posted on Wednesday, February 04, 2009 - 10:08 am
Ok thanks. One last question (for today at least), does zero have to the be the value for the lowest observation in a floor effect model? Can other "low" values work in this format?
Linda K. Muthen
posted on Wednesday, February 04, 2009 - 11:17 am
The lowest value does not need to be zero.
Tabitha McKinley
posted on Wednesday, February 11, 2009 - 2:47 pm
I have another set of questions as I've been working with the censored-inflated model, and I can't find the answers in the manual. I'm working on this with Debbi Bandalos and she couldn't answer my questions so I decided to come back here:
1) Is the intercept of the model fixed to zero by default of the program?
2) Is the "censored" part of the model due to censoring at specific time points, or censored across time?
3) How does this model select which values are censored? From what I can see, it looks like the model just selects based on the lowest value in the data, but I've not read anything that supports that.
4) Does the censored part have to be an integer, or can it also be a decimal?
Thanks so much for all of your help. I promise to send you the paper when I'm finished with this :-)
Bengt O. Muthen
posted on Wednesday, February 11, 2009 - 6:28 pm
1) No, it is free by default.
2) You have different censoring for different time points
3) It takes the lowest value unless you give it another value.
4) It can be a real number with decimals.
Nicholas Bishop
posted on Monday, June 01, 2009 - 5:45 pm
I have a similar question as to the one posted "Anonymous posted on Friday, August 06, 2004 - 8:49 pm". I am using a growth curve model that estimates BMI baseline and change over 14 years in an older adult population. The outcomes of interest are BMI slope and intercept but I need to control for mortality selection in this population. Is there a way I can incorporate a discrete time survival analysis into the latent growth model to control for mortality selection? Thanks.
Bengt O. Muthen
posted on Monday, June 01, 2009 - 6:47 pm
If I understand you correctly, you are raising an interesting point about possible non-ignorable missingness due to dropout in the form of mortality. That is, the usual MAR assumption that past observed outcome values predict missingness may not hold. There is a whole set of possibilities for handling such modeling in Mplus. Ironically, I am just preparing a talk on this topic for the UK Mplus Users Group to be presented June 8. This talk and Mplus scripts will be posted. I will also try to record this as a Camtasia web talk.
Adding discrete-time survival modeling is one way to handle this. It is related to so called Diggle-Kenward modeling, which can be done in Mplus. Another way is to use dropout dummy variables in line with Roy (2003) in Biometrics - this is better than pattern-mixture modeling in my view. The Diggle-Kenward approach represents "selection modeling", whereas the Roy approach represents "mixture modeling".
Nicholas Bishop
posted on Friday, June 12, 2009 - 11:31 am
I look forward to the positng of the talk and the MPlus scripts. Please let me know where I can find these resources once they are posted. Thanks.
posted on Friday, June 26, 2009 - 7:28 am
Hi - Jumping here from the distal outcomes conversation. I am trying to understand missing vs censored data in a latent class growth-survival analysis model similar to example 8.15 or 8.16 in the MPlus manual or the Muthen & Masyn (2005) paper. In my case, mortality can either be measured by wave (discrete time) or continuously. We have 4 waves of data over 20 yrs. We're like to use latent classes of healthy aging (defined by a score (y1-y4)) to predict mortality (u1-u4 in the discrete-time model).
I have missing data due to non-response at various individual waves, and I don't really know how MPlus is handling this. Unlike the examples provided in Muthen & Masyn (2005), these folks are not really right-censored, as they come back into the dataset at later waves, or we have data on their deaths later. Does MPlus use the survival variable to differentiate between someone who is missing due to death vs someone who is a non-respondent for one wave? A colleague has suggested imputing the non-responses in order to reduce missingness to only one type (death) - is this an appropriate approach? Are there other ways to handle this, either in the data set up or the modeling approach?
Thanks for any guidance you can give,
Bengt O. Muthen
posted on Friday, June 26, 2009 - 9:47 am
It seems to me that intermittent missingness is more likely to obey the MAR assumption (of missingness being predicted by observed variables rather than the missing value that was not captured) than dropout (due to death) missingness. So intermittent missingness needs no special action in the modeling because Mplus does ML under MAR. Dropout missingness on the other hand may be non-ignorable (NMAR; Not Missing At Random) and may therefore need the extra information on the dropout time to obey MAR (the dropout time provides the observed variable that causes missing which MAR needs). So when you add survival modeling to the growth modeling you protect yourself against biases due to dropout missingness.
In short, no imputations are needed, just modeling.
posted on Friday, June 26, 2009 - 12:18 pm
Thanks! This is very helpful. The final question I have is, how does MPlus know which instances are intermittent missing and which are missing due to death/dropout? Should these be coded differently in the dataset?
Bengt O. Muthen
posted on Friday, June 26, 2009 - 12:31 pm
Mplus knows. They should not be coded differently. Missing due to dropout simply has missing also for all subsequent values.
In the DTSA part once an event occurs you score u=1 and subsequent u's as missing, which means that this person is no longer part of the risk set for later death. U is the DV in your run so think regression where a person is not part of the computations when missing on the DV.
posted on Monday, June 29, 2009 - 9:53 am
Thanks again! The help is much appreciated as I am very new to MPlus!
Nicholas Bishop
posted on Tuesday, August 25, 2009 - 2:32 pm
Hello, I am using a growth curve model that estimates BMI baseline and change over 14 years in an older adult population. The outcomes of interest are BMI slope and intercept but I need to control for mortality selection in this population. I am able to create the GCM and the discrete time survival analysis seperately, but I am interested in incorporating both of these into a single model. Is there a better way to control for the non-ignorable missing data caused by mortality selection? Is there syntax avaiable that would be helpful to me? Thank you.
Nicholas Bishop
posted on Tuesday, August 25, 2009 - 2:37 pm
I forgot to ask if there is example syntax available for selection modeling? Thanks again.
Bengt O. Muthen
posted on Tuesday, August 25, 2009 - 6:47 pm
To account for possibly non-ignorable missingness due to dropout, you may want to analyze the growth model and the survival model jointly. These 2 processes should be correlated. One approach to draw on is the so called Diggle-Kenward selection model. If you email me, I can send you the Mplus input for that approach. I am about to finish an overview paper on these matters.
Selection modeling in the sense of Heckman is not available in Mplus.
Tim Stump
posted on Thursday, September 24, 2009 - 8:54 am
I have a continuous outcome measured at different time points and want to specify a growth model for this process. The outcome is censored above and below. I read in previous posts that you can't specify a variable as censored both above and below. Is this still true? Also, wondering if you have other options or ideas of different approaches for these kind of data.
Bengt O. Muthen
posted on Thursday, September 24, 2009 - 9:29 am
Yes, currently Mplus does not allow censoring from both below and above. Perhaps the variable can be dichotomized? If too much information gets lost that way, perhaps you want to ask why there are these two peaks in the distribution - is this a mixture of different types of people so that mixture modeling is relevant?
In addition, perhaps a combination of censored-normal modeling and two-part modeling is possible. Or maybe we need three-part modeling.
Tim Stump
posted on Thursday, September 24, 2009 - 11:22 am
Dr. Muthen, thanks for responding. Just to provide more info, I'm analyzing the clearance of a certain antigen in urine and serum specimens of patients during a specific treatment. Measurements are taken at baseline, 1, 3, 5, 8, and 13 wks. The censoring limits are .6 at low end and 39 at the high end. Subjects scoring outside these limits from the assay are marked as <.6,>39. So, they actually have values outside the limits, but I don't know what they are. Hence, the reason for specifying a censored variable. There's piling up at either end, but the % of piling up ranges from 10% up to 50% depending on the specimen (urine or serum) and time point.
Given this information, do you think mixture modeling would be relevant? Is three part modeling the same as mixture modeling?
Bengt O. Muthen
posted on Thursday, September 24, 2009 - 2:06 pm
I wonder if your censoring shifts from one end of the scale to the other end over time? If so, you could specify censored-below/above for early/late time points.
If you have censoring from both ends at a given time point, perhaps you have a mixture of patients - for which mixture modeling might be helpful even if it doesn't allow from censoring from above for one class and from below for another.
Bengt O. Muthen
posted on Thursday, September 24, 2009 - 2:11 pm
2 and 3-part modeling is not the same as mixture modeling. We teach on 2-part modeling, mixture modeling, and their differences in our short courses - see handouts at
Nicholas Bishop
posted on Saturday, February 20, 2010 - 6:36 pm
Hello. I am using a growth curve selection model to adjust for NMAR when the y outcome is word recall scores in a sample of elderly adults. I believe the value of y at time t-1 should predict drop out at time t. I have pasted the results for the discrete time portion of the model below.
DD00 ON est s.e. est/s.e. p-value
odds ratio
Am I correct in regressing death in 2000 (DD00) on word recall scores from 1998 (totrec98) and 2000 (totrec00)? If so, am I correct interpreting the odds ratio as "with a one unit increase in word-recall in 1998, the odds of dropout in 2000 increase by 27.7%"? Thanks for your time.
Bengt O. Muthen
posted on Sunday, February 21, 2010 - 11:18 am
Yes, I think so. It sounds like you are working with the Diggle-Kenward selection model. Note, however, that the separate interpretation of the two coefficients (for y_t and y_{t-1}) is not clearcut. DK (1994) discuss an alternative parameterization which you can do using Model Constraint.
Nicholas Bishop
posted on Sunday, February 21, 2010 - 10:03 pm
Dr. Muthen,
I am using the Diggle-Kenward selection model with model constraint. I have pasted the model below. It is not intuitive that higher scores on word recall would be positively associated with mortality, so I will look more into the interpretation of those coefficients.
i s |
I S ON testfx r4agey_b black hispanic other
dd00 on totrec98 (beta2)
totrec00 (beta1);
dd02 on totrec00 (beta2)
totrec02 (beta1);
dd04 on totrec02 (beta2)
totrec04 (beta1);
dd06 on totrec04 (beta2)
totrec06 (beta1);
dd08 on totrec06 (beta2)
totrec08 (beta1);
Model constraint:
new(theta1 theta2);
theta1 = (beta1+beta2)/2;
theta2 = (beta1-beta2)/2;
Bengt O. Muthen
posted on Monday, February 22, 2010 - 6:02 pm
Are you referring to the estimates for the beta coefficients or the theta coefficients in your setup? Are the signs different for these two sets? See also Diggle-Kenward (1994) eqns (31) and (32).
Nicholas Bishop
posted on Tuesday, February 23, 2010 - 1:46 pm
Dr. Muthen,
In my previous post (2/20), the estimates and odds ratios I was referring to were the coefficients given for the logistic regression portion of the model. The coefficients for the theta parameters are as follows:
New/Additional Parameters
I am unclear if I should be interpreting the coefficients for the theta parameters or the logistic regression portion of the model. I appreciate your advice with these matters.
Nicholas Bishop
posted on Tuesday, February 23, 2010 - 2:02 pm
Dr. Muthen,
I have DK (1994) in front of me and I see how the reparameterization in eq 32 leads to more easily interpretable results. Thanks for your help with this. I enjoyed reading recently submitted work on non-ignorable data modeling. Thanks again.
Nicholas Bishop
posted on Friday, February 26, 2010 - 5:44 am
Dr. Muthen,
What would be the best method for assessing model fit for the DK mixture models?
Bengt O. Muthen
posted on Friday, February 26, 2010 - 9:36 pm
With mixture models one no longer has the mean-covariance model chi-2 testing that we are used to in SEM. There are no simple sufficient statistics less than the raw data. Typically, a model is evaluated in comparison to another more general model, often by BIC.
In Mplus you can also study the fit of the model relative to the data using TECH7. Here the model-estimated means, variances and covariances are compared to "observed" sample counterparts (the posterior-probability weighed data). When there is no missing data, TECH13 makes it possible to check against 3rd and 4th-order moments as well.
Nicholas Bishop
posted on Tuesday, March 01, 2011 - 1:23 pm
I am using the DATA MISSING command to create dropout variables for a pattern-mixture model, and have a question regarding the TYPE=DDROPOUT setting. When I look at the variables created by this function, a positive (1) dropout dummy variable is only present for the first period of dropout. For periods following the intial dropout, the dummy variable remains zero. When using the TYPE=SDROPOUT setting, the period of dropout is indicated by a 1, follwed by missing data indicators for the remaining periods (discrete-time survival indicators).
When using a pattern-mixture setup, do the DDROPOUT variables control for the fact that an indivudal remains unobserved after the intial period of dropout? A great deal of the dropout I am dealing with is caused by mortality, thus these indivudals remain unobserved after thier intial dropout.
I am currenlty using the DDROPOUT setting to create missing data indicators for pattern-mixture models and the SDROPOUT to create missing data indicators for selection models.
Bengt O. Muthen
posted on Tuesday, March 01, 2011 - 3:29 pm
DDROPOUT creates a set of dummy variables which together tells you which dropout time category an individual belongs to. So for instance dropping out after time 1 with a total of 3 time points would be scored as
0 1 0
The last zero means that the person is not in the study at the 3rd time point either. So, yes, individuals remain unobserved after their initial dropout. In contrast, you can use Mplus to code intermittent missingness.
DDROPOUT is used for exogenous indicators and SDROPOUT is used endogenous indicators.
Nicholas Bishop
posted on Monday, April 11, 2011 - 8:35 am
In using the Mplus DATA MISSING command, as I am aware, the facility produces the missing data indicators for the entire sample without distinction between causes of missingness. I have two forms of absorbing dropout in my study (mortality and institutionalization), as well as intermittent missingness. I would ideally like to create a separate dropout indicator for each of these sources of missing data, then use these to adjust the outcome trajectories separately.
Is it possible for me to use the DATA MISSING command to create these separate missing data indicators? Is there another strategy I could use to properly adjust for these separate forms of dropout and intermittent missingness? Thank you.
Bengt O. Muthen
posted on Monday, April 11, 2011 - 3:00 pm
I don't know that it would be easy to use Data Missing for this - perhaps you might just as well create that information some other way (by Define, saving the new info; or by another program). You could create dropout dummy variables like in pattern-mixture modeling, where you make a distinction between types of dropout, and then see if the growth parameters differ across those dropout times and types. I haven't seen this done, however.
Ross Larsen
posted on Friday, September 16, 2011 - 7:50 am
I have an unusual case to analyze in growth modeling with censored data.
Children were given a test at three time points. The test is administered in two parts. All children were only given the second part if they achieved a threshold score in the first part.
In time 1, the second part of the test was not administered to ANY children. Thus, the children who would have taken the second part of the test were unable to to do so. This leads to time point 1 to have artificially low scores when analyzing the total test scores (part1+part2).
Ordinarily, in SAS I would handle this by creating a censored variable that would tell the procedure which of the children made the threshold and should thus be considered censored from above. In Mplus the censored statement just looks at the highest score available and calls that censored. This is a problem as two children could have both made the the threshold but one child has a lower score and thus would not be considered censored. I thought of including my censored variable (0=did not make threshold, 1=made threshold) as a covariate on the intercept and slope, but I wanted your thoughts on this problem and how you would handle it.
Thank you.
Bengt O. Muthen
posted on Saturday, September 17, 2011 - 10:59 am
Why not view the two parts of the test as two different variables, say x and y for the first and second part? For time 1, only x1 is observed and everyone has missing on y1 so we can ignore y1. For time 2, x2 is observed and y2 is observed for those above the threshold of x1 and missing for the others. Etc for time 3. Missingness fulfills MAR due to missing on y2 being determined by the observed x1 score. So for the first 2 time points the data set has 3 variables: x1, x2, and y2. None of them is censored.
Jean-Samuel Cloutier
posted on Monday, April 02, 2012 - 2:46 pm
I want to build a Multiple indicator growth model.
All my indicators are zero inflated.
What is my best option?
Jean-Samuel Cloutier
posted on Tuesday, April 03, 2012 - 8:33 am
I understant that it'is two part modelling (one binary growth model and one continuous).
I am not sure to understant how to transform my data.
Creating a variable (u) wich take 0 or otherwise 1 is eazy.
But will the second continuous variable (y), will have missing values for zeros?
Linda K. Muthen
posted on Tuesday, April 03, 2012 - 10:29 am
See DATA TWOPART in the user's guide.
Jean-Samuel Cloutier
posted on Thursday, April 12, 2012 - 8:31 am
I have try to model a growing phenomenon but certain characteristics of the phenomenon make it hard to model as a regular growth model.
I have preponderance of 0
The structure of the data evolve:
• the first year some observation are 0 and some observation are 1
• the second year some observation are 1 some observations are 2 and some observation are 0
• the third year some observation are 1 some observations are 2 and some are 3 observation are 0
and so on...
Any advices would be welcomed.
Linda K. Muthen
posted on Thursday, April 12, 2012 - 1:38 pm
If the variable is treated as categorical, see the CATEGORICAL * option on page 489 of the user's guide.
Jean-Samuel Cloutier
posted on Thursday, April 12, 2012 - 6:09 pm
It's more a count variable.
The only binary variable in the model is the first year observation.
Maybe I should consider the variable as categorical anyway. Second year would have three categories (0,1,2). ... Seventh year observations would have 8 categories (0,1,2,3,4,5,6,7).
It's like a school with seven grade, where a majority will never finish the first grade, less that will finish the first, less that will finish the second grade etc. over seven years (A left censored final distribution with preponderence of zeros).
I wish I could model this as a growth model.
Linda K. Muthen
posted on Friday, April 13, 2012 - 8:25 am
It sounds like an ordered categorical variable. I would use CATEGORICAL with the * setting.
matteo giletta
posted on Friday, June 15, 2012 - 6:35 am
Dear Linda & Bengt,
I've seen in Topic 4 that you presented a zero-inflated Poisson latent growth curve model in which you defined the intercept and slope only for the count part of the model and not for the zero-inflated one. I would like to do the same using a censored inflated growth curve model. I've estimated a conditional model in which I only defined intercept and slope (and the effects of covariates) for the continuous part of the model. Now, I wonder whether this is allowed or I would also need to define an intercept and slope for the inflated part of the model. Considering that this is computationally demanding, if allowed, I would like to avoid it.
Linda K. Muthen
posted on Friday, June 15, 2012 - 8:09 pm
You do not need to do a growth model for the inflated part of the model.
Li Lin
posted on Friday, September 28, 2012 - 8:56 am
I have longitudinal data on sexual functioning, which was measured as a continuous score if the person had sex in the past certain period, otherwise the score is missing. At each time point, if no action, reasons for not having action was recorded as sexual functioning related or not. We are planning to use the two-part growth model for this longitudinal semicontinuous data. To evaluate possible effect of an intervention, it would be desirable to exclude the 0s from the u-part if the no action was due to a function-unrelated reason. In order to do that, where should I put this time-varied unrelated reason (1/0) in the model (u-part specifically)? How to specify the model? Any reference paper would be great. Thanks!
Linda K. Muthen
posted on Sunday, September 30, 2012 - 10:43 am
It sounds like zero represents two things for the binary variable and that you can distinguish between these two. I would turn the zeroes that you want to exclude into missing values.
Li Lin
posted on Tuesday, October 02, 2012 - 1:31 pm
Thanks! I have another question – does the newest version Mplus support Bayesian estimator in two-part model with correlated intercepts and slopes? I am using version 5.21. When I specified "ANALYSIS: ESTIMATOR = BAYES", I got an error saying "*** FATAL ERROR Internal Error Code: VARIANCE COVARIANCE MATRIX NOT SUPPORTED WITH ESTIMATOR=BAYES."
Bengt O. Muthen
posted on Tuesday, October 02, 2012 - 1:48 pm
You need at least Version 6 for Bayes, and preferably Version 7.
Two-part Bayes can be done - see
Muthén, B. (2010). Bayesian analysis in Mplus: A brief introduction. Technical Report.
which is available on our web site together with Mplus scripts.
Star David
posted on Tuesday, November 20, 2012 - 6:01 pm
I'm currently running a GMM with a censored normal data (internalizing problems, sample size 2000), and it usually will take 3-4 hours to finish the analysis, but if I treat the data as normal it run fast. I think our PC is in the top level (i7 8Gram). I noticed that in UG EX.8.3, it said "numerical integration becomes increasingly more computationally demanding as the number of factors and the sample size increase", if there are any way to reduce the time that the program take? And if it's appropriate to treat a censored normal distribution data as normal when conducting GMM, the results would have any difference?
Bengt O. Muthen
posted on Tuesday, November 20, 2012 - 6:32 pm
How many growth factors do you have?
What's the percentage of subjects at the censoring point for each time point?
Star David
posted on Wednesday, November 21, 2012 - 5:35 am
Thanks for replying so quickly!
We have 6 time points and I've tried both 4 growth factors(i s q cu) and 3 growth factors(i s q) model, the latter one take fewer time but still quite a long time(about 10000s with starts = 20 2; classes = c(3);).
Because our DV is continuous (internalizing problems), at each time point there're about 25% of the subjects score at 0.
Bengt O. Muthen
posted on Wednesday, November 21, 2012 - 4:10 pm
Often in mixture modeling with several classes you do not need all growth factors to be random but can fix the variances for some of them. So for instance if you have i s q, you can fix
(still estimating the q mean) and therefore have only 2 dimensions of integration.
With only 25% censoring you probably get a reasonable approximation by treating the outcomes as regular continuous variables. You can use this to more quickly search for which growth factors need to have free variances and thereby check my conjecture above.
Star David
posted on Wednesday, November 21, 2012 - 6:10 pm
Thanks for your advice!
matteo giletta
posted on Tuesday, September 17, 2013 - 9:10 am
Dear Drs. Muthen,
I am conducting some growth models with a censored outcome.
What is the best way to compare unconditional models (e.g., linear vs. quadratic)? Can I compare models as nested using loglikelihood difference tests?
Thank you so much!
Linda K. Muthen
posted on Tuesday, September 17, 2013 - 5:43 pm
The models are nested but because the variance of the quadratic growth factor is fixed at zero in the linear model which is on the border of the admissible parameter space, the difference may not be distributed chi-square. I would compare the models using BIC.
matteo giletta
posted on Wednesday, September 18, 2013 - 8:39 am
Thanks so much for your quick reply!
Would the sample-size adjusted BIC be more appropriate than the BIC in this case? and is there any suggested cut-off to consider a decrease in the BIC a significant indicator of model improvement?
Linda K. Muthen
posted on Wednesday, September 18, 2013 - 10:35 am
I would use BIC. There is a FAQ on the website about cutoffs and BIC.
Lisa M. Yarnell
posted on Thursday, January 23, 2014 - 9:51 pm
Hello, I want to construct a growth model for count indicators that are censored. This seems to be a blend of Examples 6.3 and 6.7 in the current Users' Guide.
Our growth data are symptom counts, which are censored at the time points for which a person is not yet a drinker (and in, fact, censored-inflated as in Ex. 6.3 for the first time point--because many people are not yet drinkers). But as the sample begins to drink over the years, they will have positive symptom counts; and the symptom counts will likely still be zero-inflated, somewhat.
The model I would like to run could thus be more similar to Ex. 6.7, where the zeros can arise from two subpopulations (those who are not yet drinkers and hence have zero symptom count, and those who ARE drinkers but are not showing symptoms). But...I do like the idea of explicitly capturing the censoring of the symptom count data at the earlier time points, as in Example 6.3. In Poisson, the two sources of zeros are thought to be latent, allowing for mixing--while we do know the source of the zeros, and thus could model this explicitly as being censored.
Yet, the indicators are specified as continuous (not count) in Ex. 6.3.
Can you give suggestions on whether our problem could/should be thought of as more similar to 6.3 or 6.7?
Or, can I run model 6.3 but specify the indicators as count?
Katherine E. Masyn
posted on Friday, January 24, 2014 - 2:30 pm
Hi, Lisa.
You might consider an onset-to-growth model (a.k.a. a launch model) where the onset of drinking marks the beginning of the growth process for a given individual (and, as such, the pre-onset zeros are not even part of the growth outcomes). Then in your growth model, you only need to deal with the pile-up of zeros among those who are drinkers but with a zero symptom count.
Check out this article--not exactly what you need for the growth portion of your model but it will give you a start on the onset-to-growth set-up.
Malone, P. S., Northrup, T. F., Masyn, K. E., Lamis, D. A., & Lamont, A. E. (2012). Initiation and persistence of alcohol use in United States Black, Hispanic, and White male and female youth. Addictive Behaviors, 37, 299-305.
Katherine Masyn
Tom Booth
posted on Monday, April 07, 2014 - 11:53 pm
Dear Bengt & Linda,
I am running a simple 4-wave linear GCM with time varying covariates. Across waves I have drop out due to death or serious illness in an ageing sample. I need to account for this. From reading above, it seems the pattern mixture approach using SDROPOUT is the way to go. Does this seem correct?
The GCM here concerns cognitive variables, so whilst cognitive decline is expected prior to death, I do not think I want to predict mortality from cognitive scores in this instance - hence I think the above would be more suitable than a joint GCM survival approach.
Linda K. Muthen
posted on Tuesday, April 08, 2014 - 9:56 am
You should use DDROPOUT not SDROPOUT. See Examples 11.2 and 11.4.
Tom Booth
posted on Wednesday, April 09, 2014 - 6:53 am
Thanks Linda.
Carlijn C
posted on Wednesday, July 02, 2014 - 3:18 pm
I'm running a latent growth model on multiple groups (2 groups: a control and an experimental group). I have a very skewed variable with a lot of zeros (range 0-13; a lower value is better).
The original means of group 1 were: (1) 1.296 (2) 0.724 (3) 0.960 and in group 2: (1) 0.894 (2) 0.599 (3) 0.361. The slope mean of group 1: -0.144, and group 2: -0.260 (significant).
Now, when I'm using the censored method, the means of group 1 are: (1) -1.147 (2) -0.999 (3) -4.157, and in group 2: (1) -0.619 (2) -0.932 (3) -1.059. The slope mean of group 1 is: -0.841, and in group 2: -0.218.
Without the censored method, it seems to me that group 2, the experimental group, did better compared to group 1, the control group. However, with the censored method, it seems this is not longer the case. So I don't understand the outcomes in the censored method. How should I interpret the outcomes in the censored method?
Bengt O. Muthen
posted on Wednesday, July 02, 2014 - 5:19 pm
With a lot of zeros I would recommend instead looking at the two-part growth modeling approach because it is a richer model that can show you separate treatment effects on the probability of zero and the amount above zero. You have a UG example to start from and we also teach on it in our short course videos and handouts.
anonymous Z
posted on Saturday, October 24, 2015 - 2:46 pm
Dear Drs. Muthen,
I am fitting a model with drug use across five time points as the outcome variable (a lot of zeros because some people don't use, and then the variable value is continuous for those who use). My independent variables are relationship status (0 as not in a relationship and 1 as being in a relationship) and relationship quality (if the participants are not in a relationship at certain time point, the value will be missing) across five time points. I prefer to use a multilevel approach rather a multivariate approach to model the growth curve.
I originally did censored growth modeling (censored from below). Below is the model. I have two questions:
1) Does the explanation for the beta coefficients I get from the censored model the same as when drug is not censored?
2) It seems that you suggest two-part modeling is a better option. Can two-part modeling be done with multilevel approach (univariate approach)? If so, what the syntax should be like?
Thanks so much!
VARIABLE: NAMES ARE drug;
CENSORED ARE drug (b);
Drug on relationship_status;
Drug on relationship_quality;
s | Drug on time;
Drug on treatment;
Drug with s;
Bengt O. Muthen
posted on Saturday, October 24, 2015 - 4:50 pm
1) Yes, beta refers to the underlying uncensored variable.
2) That should work, although I don't think I have done it. You can create the 2 variables (so a bivariate, 2-level model) the same way as we show for wide, 1-level. I think you can use DATA TWOPART to do that.
anonymous Z
posted on Monday, October 26, 2015 - 12:14 pm
Hi, Dr. Muthen,
Thanks for your advice. I ran the model as two-part modeling. Below was the syntax I added. I have two questions:
1.The analysis ran without any error message, however, the output didn't list anything about binary or continuous parts. I got pretty similar results as when I didn't use "DATA TWOPART." Is something wrong with it?
BINARY = binAL;
CONTINUOUS = conAL;
2. The second question is about censored-inflated model. From what I read, the censored-inflated model is very similar to the two-part modeling? what is the difference between them?
Thanks so much,
anonymous Z
posted on Monday, October 26, 2015 - 1:16 pm
To add to my question, when I do the censored-inflated model with the multilevel approach, I got results similar to normal multilevel approach, i.e, the output didn't show the results for binary versus the inflation part. Anything missing in my syntax?
Bengt O. Muthen
posted on Monday, October 26, 2015 - 5:50 pm
First post:
1. You need to specify a growth model for both parts - see the UG example for 2-part.
2. The censored-inflated model is a 2-class model. The 2-part model does not use 2 classes. But they often have quite similar fits.
Second post:
You need to model the inflated part as well.
anonymous Z
posted on Tuesday, October 27, 2015 - 7:17 am
Thank you so much! Could you recommend any papers doing censored-inflated models, which I can refer to to help describe the analysis?
anonymous Z
posted on Tuesday, October 27, 2015 - 11:04 am
Hi Dr. Muthen,
Below is my syntax for the censored-inflated modeling. I got the error message. How should I fix the problem?
Thanks so much,
*** ERROR in MODEL command
Unknown variable: OPi
CENSORED are OP(bi);
cluster = ID;
within = time REL_STA PARTNER;
Between = TX_2 eth;
analysis: type = twolevel random;
S| OP on time;
Si| OPi on time;
OPi ON REL_STA PARTNER;
OP ON TX_2 eth;
S ON TX_2 eth;
OPi ON TX_2 eth;
Si ON TX_2;
OPi WITH Si;
Bengt O. Muthen
posted on Tuesday, October 27, 2015 - 3:00 pm
Opi is not how the inflation part is referred to. See the UG for examples with censored-inflated.
posted on Monday, February 20, 2017 - 6:19 am
I am looking at a growth mixture model of viral load in HIV over 20 years. However, there are two types of censoring in the dataset, and I was wondering how these might be addressed in models:
1. Via death of participant
2. Participants were recruited at different timepoints (e.g., some at year 1, some at year 10, some at year 19). So some participants have the possibility of having 20 years of data, while others have the possibility of having only 1 (i.e., those recruited at year 19).
How could Mplus be used to incorporate both of these sources of censoring, as they arise from very different processes? As I am aware Mplus cannot handle when variables are censored both above and below and I wanted to ask if there was a way to handle this scenario.
This is a naturalistic study (continually recruited participants and tracked them over time) and I would like to scale the time variable as time since baseline visit unless there is a better way (all suggestions are welcome).
Bengt O. Muthen
posted on Monday, February 20, 2017 - 6:20 pm
1. You can try MAR, but see also the paper on our Missing data web page:
Muthén, B., Asparouhov, T., Hunter, A. & Leuchter, A. (2011). Growth modeling with non-ignorable dropout: Alternative analyses of the STAR*D antidepressant trial. Psychological Methods, 16, 17-33. Contact the first author. Click here to view Mplus outputs used in this paper. Paper can be downloaded from here.
2. With time since baseline, it seems that this censoring would not be a problem.
posted on Tuesday, February 21, 2017 - 8:58 am
Thank you!
Brandon Goldstein
posted on Friday, March 13, 2020 - 12:52 pm
I am trying to run a two part growth model with 4 time points (number of zeros ranges from 26% to 54%).
Following the manual for model 6.16, iu and su are the intercept and slope for the binary part and iy and sy. In model 6.16 su is held at 0.
I receive an error to look into Tech 4. This shows that the variance for sy is -0.005.
1. Is it appropriate to run a model with
as well?
2. What is the interpretation of two part growth model in which both
. Would that suggest that a growth model is not appropriate for this data?
Thank you!
Bengt O. Muthen
posted on Saturday, March 14, 2020 - 3:03 pm
1. Yes.
2. No - the growth model is fine. It just says that there is no variation across people in the growth. You still get means for the s's.
Brandon Goldstein
posted on Monday, March 16, 2020 - 6:07 am
Thank you
I had forgotten that @0 was a fix for variance. My mistake.
A follow-up question. If the there is no variation across the sample, is this akin to a "fixed" effect? Such that, if a variable is associated with the mean, it would be interpreted similar to a between subjects effect?
I guess this is really a question about how to interpret associations with the estimated mean for the slope. Thanks again!
Bengt O. Muthen
posted on Monday, March 16, 2020 - 10:25 am
Yes, a fixed effect.
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Phone: 888-889-7311
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This is not an offer for credit and should be used for estimation purposes only based on the information you provided. You should not base your decision on this estimate alone. Title, registration, tax and other fees, and personal circumstances such as employment status and personal credit history, were not considered in the calculations.
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text: The Enterprise License is the ideal solution for companies looking to maximize automation as part of their Conflict Minerals program. Containing all the features of the Basic, Premium and Premium Plus License, the Enterprise license is configurable and allows you to choose your reporting structure based on the divisional, part, or BOM level. This unique license also allows you to upgrade only those features that fit your reporting requirements.


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Do I really have todo this, Dad ?
Stan, now more than ever,
you need to understand theimportance of saving money.
But Grandma saidI could use this money
to buy whatever I want.
Okay, next please !
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The Importance of Saving Money
Margaritaville s13e03
Stan takes his $100 check and makes an investment into South Park Bank. Annndd it's gone.


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I guess I spoke too soon.I spun the handle and base and then did a 3D add. However, I am having a problem with the fillet blend Each time I try to select the intersection I get an error. Also, not familiar with the blend procedure.Would appreciate some guidance on this. I am working in TC2016.Thanks
A second question. I don't have the lightworks add-in for my TC2016 and would like to render the drawing.
TC2016 RedSDK materials, reflections and lighting setup....Very capable once setup correctly...
FYI - The hot and cold caps are embossed brass buttons that insert into the top opening via an o ring.Out of curiosity, I sense that Turbocader's are always on the lookout for geometric items that they can draw and render.When working with a real item as the Concinnity handle, how do others work out the drawing?I have been using digital calipers where I can measure and also imported photos into TC and tried to measure curves and angles to scale. The Concinnity handle was a problem because my photos were somewhat skewed and the left arm not the same TC dimensions as the right arm, etc..Just curious!
Dean,I have been trying to get a decent rendering either with my TC17 and lightworks or TC2016 with Redsdk, but cannot reach the level of sophistication that have been demonstrated here.I would appreciate any guidance the board could give me in either format. When I look at the multiple parameters I really can't get a logical approach since there are too many things to change and they all seem to be in a different language. Trying to change one parameter at a time is useless, frustrating and time consuming.I also like Darrel's background environment, but have not the proper selection.
Cool Daz Attached is my attempt to capture the "ambience" in the reference photo that K posted above. Had to adjust the physical properties some, probably due to the RSE.
Henry H.I can recommend an excellent book -- H. Hubich's, "Photorealism in Turbocad"
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text:
In the race for Nassau County Executive, Democrat Tom Suozzi of Glen Cove will attempt to retain the post he has held since 2002. He is running against longtime Republican Legislator Ed Mangano of Bethpage.
Ed Mangano
The Republican candidate for Nassau County Executive, Ed Mangano of Bethpage, has been involved in Nassau County government, having represented the 17th Legislative District for over a decade. Mangano believes the county is being led in the wrong direction and vows to put the county back on the right fiscal path, easing the tax burden on Nassau residents. He has even formed his own party line. In addition to running on the Republican line, Mangano is also running on the Tax Revolt Party line.
Concerned that the current generation is struggling to stay in the county and financial burdens are being placed on future generations, Mangano vows to help county taxpayers by repealing a 2.5 percent Home Energy Tax that was placed this year on all forms of residential energy including electric, oil, gas and even firewood, fix a broken assessment system that is costing the county millions each year and rid the county of patronage positions.
"Nassau County has been significantly mismanaged over the last eight years with respect to finances. This budget does nothing more than kick the can down the road and it's a real problem. While it claims it's a 'no tax increase' budget, it's more sleight of hand because it contains a Home Energy Tax. The independent budget review office said that tax is equivalent to a 4.5 percent property tax increase," said Mangano of the 2010 county budget, which he voted against. "It creates a further burden on all the citizens of Nassau County."
If elected Nassau County Executive, Mangano plans on repealing the Home Energy Tax that was put into effect by Nassau County Executive Tom Suozzi and the Democratic majority of the county legislature in order to fill a projected deficit in the budget. The tax remains in effect for 2010 and, according to Republican critics of the tax, is particularly damaging to seniors who need oil or gas to heat their homes in the winter.
Mangano feels the tax can be repealed and the county can make up the money it would generate by fixing the county's property assessment system, which he said loses $100 million of the "taxpayers' hard-earned money each and every year."
"It is now not only crushing our generation, but it is resulting in indebting future generations to the tune of $1 billion. The state watchdog agency (Nassau Interim Finance Authority or NIFA) says and I agree that the property tax assessment system must be fixed or Nassau County is heading toward insolvency in 2012," Mangano said.
The problem of a broken assessment system, according to Mangano, is a problem that requires immediate attention and he is committed to fixing it. "This administration managed to take what should be an easily understandable system and create significant errors in it," he said, adding that despite 300 county employees working on the assessment system and a new computer system, the error rate remains unchanged. "It still continues to lose $100 million a year."
Mangano proposes freezing property assessments and allow them to be corrected over a period of four years. "We have a plan to freeze, fix and save Nassau County taxpayers $100 million a year," he said. "Tom Suozzi specifically promised not to borrow to pay back property tax assessments. Yet, he continues to do so. It's wrong for our generation and it's certainly irresponsible and wrong to burden future generations."
Mangano has also been critical of the current administration for having too many high-paying, patronage jobs in spite of Suozzi's initiative to reduce the county workforce by 1,000. "The people who have lost their jobs are the people that cut the grass, take care of your parks and plow the roads while he has doubled his staff in size, costing taxpayers $22 million a year more. Over eight years, it's $176 million wasted on excess management while Nassau County continues to plunge deeper in debt to the tune of $150 million in debt this year with [NIFA] projecting a $226 million deficit by the year 2012," he said. "The solutions [Suozzi] offers in his four-year plan are nothing more than continued tax increases and it's just the wrong direction for Nassau County."
Mangano believes it is time for a new direction for Nassau County. He vows to fix the assessment system, reducing the money being paid out to property tax refunds as well as the interest on money being borrowed to pay them. He also vows to cut back patronage positions, end the Home Energy Tax and create local jobs. "This election is about the person who has the knowledge, experience and desire to fix Nassau County not only for our generation, but for our future generations. I have that experience," he said.
Mangano is running under the Republican and Tax Revolt Party lines.
Tom Suozzi
Tom Suozzi is running for a third term as the Nassau County Executive. The election year may be his toughest because of the tough fiscal times that have hit Nassau County residents. However, Suozzi believes he has done his part to control taxes while improving the financial status of the county. His most recent budget for the 2010 year calls for no tax increase on the county's portion of the property tax bill, although his Republican opponents have been critical of a 2.5 percent Home Energy Tax that was implemented this year.
"People are fed up with property taxes," said Suozzi, pointing out that the county portion is only 16.9 percent of the total property tax bill. "We've kept the property taxes in the county relatively under control while they've gone up dramatically in other places."
In six of his last seven years, there was no property tax increase in the county budget. "Property taxes have always been the big issue the whole time I've been in office. Even with the bad financial condition that the whole world is facing, I couldn't raise the property taxes," said Suozzi, pointing out the county has the highest bond rating it has had in the last 13 years. "We've managed to keep the county's finances stable. We've done it keeping the property taxes under control. We've managed to keep our bond ratings stable."
In a tough fiscal time when municipalities are struggling with budget cuts, Suozzi believes it has taken tough decisions to present fiscally responsible budgets to taxpayers including the 2010 budget. "It was very difficult to do because we have a lot of increases in expenses that are mandated," he said, noting that expenses that have increased such as pay raises negotiated in union contracts the county had to absorb. Suozzi said the "no tax increase" budget was made possible by the efforts made to reduce expenses.
Reducing the county's workforce was the main initiative that was used to contain costs. Suozzi said there are 1,000 fewer county workers now than when he took office in 2002. The 2010 budget also calls for 700 fewer workers than the 2009 budget. "That's not easy to do. We've had to, for example, do a lot of civilianization in the police department so we could keep the same number of officers on the street, but reduce the size of the overall headcount and our crime rate is the lowest it's been in 30 years," he said.
While his opponents have criticized Suozzi for not making enough spending cuts, he said the Republican caucus of the Nassau County Legislature hasn't proposed anything specific they would have done differently.
Suozzi has been outspoken on the high property taxes paid by Nassau residents because of the various levels of government and has focused some of his attention on New York State (he had a "Fix Albany" campaign and chaired a statewide commission on property tax relief) because he feels the property tax burden is unfairly being passed down from the state too heavily on the residents of Nassau County. "It's a statewide systemic problem that needs to be addressed," he said of property taxes. "The problem is in Albany. Local taxes in New York State are 78 percent above the national average, the highest local taxes in America. We have to fix it systemically."
In his next term in office, Suozzi hopes to work on economic development and revitalization. He recently presented a master plan for the future development for Nassau County, entitled 90/10 Master Plan. "Ninety percent of Nassau County needs to stay exactly the way it is now. We have to keep all the stuff we love about Nassau County," said Suozzi, pointing out that the county has four big problems — property taxes, young people not moving to the county, traffic and pockets of poverty. "Ten percent of Nassau County has to be completely re-imagined and redeveloped in a way that expands the tax base, attracts young people to live here, gets people to not necessarily take their car everywhere they want to go and cleans up blighted areas."
He supports the "Cool Downtown" initiatives to revitalize downtown areas and has strongly supported the Lighthouse Project, which includes a new Nassau Coliseum and development of the area around it. "The Lighthouse Project is essential to the longterm future of Nassau County," Suozzi said.
Suozzi believes the county is providing better services and has been more fiscally responsible since he took office as Nassau County Executive. "We're providing services and we're doing it well. It's difficult but we're trying to do it in a way that's affordable to the taxpayers," he said.
Suozzi is running on the Democratic, Independent and Working Families Party lines.


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text:
This is the last of the events that have kept me busy for the last couple of months, at least until July!
And let me tell you, I loved! this party, specially because it was all girly and pink, but also because everything was picture perfect! A beautiful party for beautiful baby Isabela's 1st birthday. The theme was inspired by "Curious George Inspired Monkey Birthday Party!" from Paiges of Style . It was a real pleasure to work with Isabela's mom. She is one crafty and creative mommy and had ideas and details that we incorporated into every little thing. She even created the popcorn cones, party hats for the kids and pompom cupcake toppers!
I found this adorable girl monkey clip art from Little Fairy Land and used her in the invitations, banner and favor boxes.
Centerpieces were ceramic pots filled with mini bananas and a centerpiece topper.
Food label pom poms created by Isabela's mom and labels to complete the look.
Water bottles for "thirsty monkeys".
The favor boxes to be filled with all the candy yummy-ness...
Since the party was held at Little Gym, we were not allowed to stick anything onto the walls, so we had to attach the banner to the table.
Wrapped Baby food jars for the baby guests.
The candy and cake table...
These chocolate monkey pops were created by a friend of the family.
Our now popular chocolate dipped marshmallows!
And, of course, a spectacular birthday hat for little Isabela.
I think this is the cutest party yet, what do you think?
Next up in July: More custom orders for baptisms, birthdays and baby showers and last and most importantly, my own little boy's 3rd birthday party, which I can't wait to show you!
See you soon!


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Oh, how I tire of the End of Men headlines.
Two recent books have reignited the conversation, though, as their titles indicate, they come at it from decidedly different perspectives. In "Manning Up," Kay Hymowitz argues that men taking longer to grow up and get married (which are, you know, boogeyman-bad phenomena) is a problem for which feminism is to blame. Then there's "Man Down," by Dan Abrams, which argues that women are better than men at basically everything. (On a recent appearance on The View, Joy Behar made him blush when she asked: "Did you just write the book to get laid?") In his book, Abrams cites a lot of science that'll have women feeling proud, but some of it is cause for pause. Check, for example, this, from a Q&A at MyDaily:
You cite a study that shows that people often find news more credible when it's read by a female newscaster, but that the same people often find male newscasters more credible in general. This dynamic shows up in your analysis of women in politics as well. Can you tell us what you think is going on here?
Look, I think that there are still a lot of people who have what I might view as antiquated stereotypes about how they view everything from world leaders to doctors to newscasters. It's really striking, the idea that they viewed the messages coming from a woman as more credible but when they were asked who was more credible, they said men.
And this is exactly the kind of thing that gets my blood boiling whenever I come across something like Hymowitz' "Manning Up"–woe be the man, no longer the king of the castle, the apex of the food chain! I'm not the only one; here's a nice little taste from Kate Tuttle's take down in the Boston Globe:
[Hymowitz's] zeal to somehow tie women's educational and economic advances to this perceived downward spiral in men's maturity levels leads her to make wild claims and to confuse cause and effect, as when she points out that women only make less money than men if you take into account their disproportional numbers in low-paying careers–there's a more logical way to spin that fact, as I'm sure she realizes. But when your point is that somehow women are doing better than men, and that this improvement in women's lives somehow comes at the expense of men's identity, well, it's better to throw around lines like 'feminism's siren call to the workplace' than to question why jobs traditionally held by women pay less than jobs traditionally held by men.
An important question, doncha think? Perhaps it has to do with fears of being perceived as too ambitious, or of women's work being undervalued? (An equally important question might be this: who are these women–writing books, running for the second-highest public office–so quick to denigrate feminism?)
More annoying, though, is this: on the very same day I found myself reading one women's argument as to why feminism is to blame for all that ails the modern man and one man's assertion that, to quote the Grateful Dead, The Women Are Smarter, I came across an NYT piece titled "At M.I.T., Success Comes With Unexpected Consequences." The story leads off with a nod to M.I.T.'s recent push to hire more women, but quickly takes a nosedive into the unexpected consequences. And as we all know, unexpected consequences are never good.
But with the emphasis on eliminating bias, women now say the assumption when they win important prizes or positions is that they did so because of their gender. Professors say that female undergraduates ask them how to answer male classmates who tell them they got into M.I.T. only because of affirmative action.
(I have some idea of how I'd answer such a statement. And I didn't even go to M.I.T.)
But wait; there's more! For every positive development, an unintended consequence. Pro: every committee must include a woman! Con: because there are so many fewer women than men on the faculty, nearly every woman is on a committee–and, thus, losing time for research,
as well as the outside consultancies that earn their male colleagues a lot of money.
Pro: There are better family leave policies in place. Con:
Yet now women say they are uneasy with the frequent invitations to appear on campus panels to discuss their work-life balance. In interviews for the study, they expressed frustration that parenthood remained a women's issue, rather than a family one.
As Professor Sive said, 'Men are not expected to discuss how much sleep they get or what they give their kids for breakfast.'
Better grab a Pop-Tart for this next one:
Despite an effort to educate colleagues about bias in letters of recommendation for tenure, those for men tend to focus on intellect while those for women dwell on temperament.
Sure doesn't sound like we're on equal ground [she typed with a smile]. And yet, it seems all but impossible to escape the hand-wringing over the End of Men.
Speaking of the end of men, Hanna Rosin, who wrote the article of the same name for The Atlantic, on last week's Double X Gabfest spoke with her colleagues Jessica Grose and Kate Julian about manning up, manning down, and the end of men. In it, Rosin puts forth an interesting theory: They're old themes in America: that of the self-made man, the constant opportunity for self-reinvention. It's an ideology, she says, that created a constant state of "anxiety in men, that you were constantly having to prove yourself."
At that point, another voice, I think Grose, pipes in to say that the women she knows, in their 20s and 30s, are incredibly anxious about making something of themselves, too, weighed down by the idea of having it all.
Um, yeah. We'd tend to agree. So, let's just take a moment to review: in addition to the sorts of unexpected consequences outlined in the NYT piece about M.I.T., women are also facing the kind of anxiety that men have been dealing with for centuries–only, because it's new to our gender as a whole, we have to navigate that without benefit of role models… And yet, we wonder, is this the end of men?
I suppose it depends on what is meant by the word "men." Could it be that what's really going on is that the traditional definitions are growing less and less relevant; that women are becoming more like traditional 'men,' and men, more like us?
Interestingly, later still I found myself flipping through the mountainous stack of unread magazines on my dining room table (/desk). A headline on this month's Marie Claire caught my eye: "New Trend: Male Baby Fever." Inside, the piece claims that men are hankering to become daddies, dumping women not yet ready to settle down. (Wonder what Hymowitz would make of that?)
(While this, I'm sure, is generally viewed as a warm-fuzzy variety story, a trend to be applauded, the logical counterpart–the one about those women who aren't feeling the settling down thing–would likely be met with tsk-tsks and hyperbolic cries that this time, feminism has really done it; the end of the world as we know it is near!)
But. I wonder.
Even if it is only a (insert air quotes here) Trend Piece, and even if it only hints at an inkling of a trend, might it hold the potential for a pleasant-yet-unintended consequence: If men are increasingly the ones with baby-fever, maybe, soon enough, they'll be the ones fighting for a more family friendly workplace. Maybe they'll want their wives to make the same kind of money they do. While I don't envision a day when they'll be the ones stuck talking sleep, judged on their temperament, rather than their accomplishments, I like to imagine a time when it occurs to them that a more equal world is worth fighting for–and an unintended consequence of fighting for it might be better conditions for everyone.
Pipe dream or Pop Tart? Time will tell.


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OK, I sorta stole that from Jim Gaffigan (OH, I love that guy!) But these butterscotch muffins are soooo good, and super-easy to make, you have to try them!
Butterscotch Muffins
adapted by me from a Better Homes and Gardens recipe
Oven: 400 degrees
Yield: 10 - 12 muffins
1 3/4 c all-purpose flour
1/3 c sugar
2 teaspoons baking powder
1/4 teaspoon salt
1 cup butterscotch chips (1/2 of a 10 oz. bag)
1 beaten egg
3/4 cup milk
1/4 cup cooking oil
handful of rolled oats
- Spray twelve 2.5" muffin cups with non-stick vegetable spray (or line with paper baking cups;) set aside.
- In a medium mixing bowl, combine flour, sugar, baking powder, salt, and butterscotch chips. Make a well in the center of this dry mixture, and set aside.
- In another mixing bowl, (honestly, I just dump it all in the one bowl, but who am I to tell BHG how to bake) combine egg, milk, and oil. Add egg mixture all at once to the dry mixture.
- Stir JUST til moistened (batter will still be lumpy!) I watched Alton Brown talk about muffins once, and he said to stir it no more than 20 strokes, and then force yourself to walk away. He's right.
- Spoon batter into prepared muffin cups, filling each 2/3 full.
- Sprinkle each muffin with some rolled oats. . . . a little sprinkle of cinnamon and sugar is amazing, too.
- Bake in a 400 degree oven, for 20 minutes or until golden.
- Cool in muffin cups for 5 minutes, then remove.
- Serve warm, and enjoy!


text:
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text:
Do you go to your favourite salon or spa and pamper yourself with a fabulous manicure only to almost immediately muck up your polish fumbling for your keys because you just can't wait long enough for it to dry completely? Or do you paint your nails at home and wake up with sheet prints instead of a glossy finish? Do you wear away your polish quickly typing everyday at work? Isn't it infinitely frustrating?
A perfect manicure really finishes an outfit. From french tips to almost black, impeccable, shiny nails are a must-have accessory.
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text:
Coll 17/8(1) 'Shaikh of Koweit: Date Gardens of the Sheikh in Iraq' [410v] (825/1452)
The record is made up of 1 volume (721 folios). It was created in 17 Aug 1932-31 Jan 1934. It was written in English and Turkish. The original is part of the British Library: India Office The department of the British Government to which the Government of India reported between 1858 and 1947. The successor to the Court of Directors. Records and Private Papers.
About this item
- Content
The volume consists of extensive correspondence, memoranda and reports regarding the Faddaghiyeh Estates of the Shaikh of Kuwait, changes made to their tax-exempt status, and lawsuits regarding their ownership.
The records provide details of the lawsuits brought against the Shaikh of Kuwait in the Iraqi courts by the heirs of the previous owners of the Bashiyeh and Faddaghiyeh properties. These rested on claims that the original sales were not correctly registered with the Tapu Department under the old Ottoman Law, as the Shaikh had refused to take out Turkish nationality papers. The file also concerns changes to the tax-exempt status of the date gardens, following the instigation of the Istihlak tax by the Government of Iraq. Questions arose as to whether the Government of Iraq was obligated to guarantee the tax-exempt status originally granted by HM Government ( HMG Her or His Majesty's Government in London. ), and whether HMG Her or His Majesty's Government in London. was obligated to compensate the Shaikh for loss of revenue. The correspondence on file primarily concerns attempts by British Officials to defend the Shaikh's status as owner of the date gardens, and discussions about possible compensation.
The principal correspondents and authors are: the High Commissioner for Iraq (Francis Henry Humphrys), the Colonial Office, the Foreign Office, the Political Agent A mid-ranking political representative (equivalent to a Consul) from the diplomatic corps of the Government of India or one of its subordinate provincial governments, in charge of a Political Agency. , Kuwait (Harold Richard Patrick Dickson), the Political Resident A senior ranking political representative (equivalent to a Consul General) from the diplomatic corps of the Government of India or one of its subordinate provincial governments, in charge of a Political Residency. in the Persian Gulf Historically used by the British to refer to the sea area between the Arabian Peninsula and Iran. Often referred to as The Gulf or the Arabian Gulf. (Hugh Vincent Biscoe), HM Ambassador to Iraq, HM Counsellor to HM Embassy, Iraq (Sir George Arthur Ogilvie-Forbes), and the Legal Secretary to the High Commissioner for Iraq (John Harry Barclay Nihill). The volume also contains translations of letters received from the Shaikh of Kuwait (Aḥmad al-Jābir Āl Ṣabāḥ), his Basra Agent (Abdul Aziz as Salim al-Badr), his lawyer (Jacob Gabriel), and the Government of Iraq.
The following reports and legal documents appear within the volume:
- Memorandum prepared by the Judicial Advisor to the High Commissioner for Iraq (G Alexander), regarding attempts made to deprive the Shaikh of Kuwait of certain of his date gardens, ff 658-679.
- Translation of judgement No. 77/930, issued on 30th December 1931 by the Court of First Instance, Basrah; and translation of decree No. 66/932 dated 9 May 1932, issued by the Court of Appeal, Baghdad, for service on the Shaikh of Kuwait, ff 634-644.
- Short histories of the Shaikh of Kuwait's Bashiyeh and Faddighiyeh gardens on the Shatt al Arab from the time of their purchase to date, written by the Political Agent A mid-ranking political representative (equivalent to a Consul) from the diplomatic corps of the Government of India or one of its subordinate provincial governments, in charge of a Political Agency. , Kuwait, ff 621-629.
- List of persons to be served with legal documents from the Court of First Instance, Basrah, f 533.
- 'The Date Gardens in Iraq of the Sheikhs of Koweit and Mohammerah. Scope of Undertakings given by HM Government in 1914. Case for the Opinion of the Law Officers of the Crown, and Opinion Thereof', ff 458-476.
- Explanatory notes with accompanying sketch map of the Faddaghiyeh Estate, ff 205-209.
- English translations of the four Tapu deeds connected with the Faddaghiyeh Estate dispute (deeds originally dated August 1915), ff 90-99.
- Copy power of attorney document, written in Turkish, issued by the TC Asliye Mahkemesi Altinci Hukuk Dairesi 6 [Turkish Republic Civil Court of First Instance, 6th Law Department] on the 15 Ramandan 1326 [1908] in favour of Ahmet Pasha Kazim Azzubair, ff 78-80.
The file continues with Collection 17/8 part 2, reference IOR/L/PS/12/2854.
The volume includes dividers which give lists of correspondence references found within the volume by year. These are placed at the end of the correspondence (folios 4-5).
- Extent and format
- 1 volume (721 folios)
- Arrangement
The papers are arranged in rough chronological order from the rear to the front of the volume.
- Physical characteristics
Foliation: the main foliation sequence (used for referencing) commences at the inside front cover with 1, and terminates at the inside back cover with 723; these numbers are written in pencil, are circled, and are located in the top right corner of the recto The front of a sheet of paper or leaf, often abbreviated to 'r'. side of each folio. Two additional foliation sequences are also present in parallel between ff 4-721, and ff 695-721; these numbers are also written in pencil, but are not circled.
- Written in
- English and Turkish in Latin script View the complete information for this record
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- Coll 17/8(1) 'Shaikh of Koweit: Date Gardens of the Sheikh in Iraq'
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- front, back, spine, edge, head, tail, front-i, 2r:22v, 24r:41v, 43r:72v, 74r:78v, 81r:88v, 90r:100v, 104r:112v, 114r:155v, 157r:159v, 163r:168v, 170r:198v, 200r:289v, 293r:310v, 312r:462v, 467r:467v, 469v:531v, 534r:596v, 598r:613v, 615r:618v, 620r:633v, 645r:678v, 680r:705v, 717r:718v, 722r:723v, back-i
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- Usage terms
- Open Government Licence


text:
LINYI, China (CCTV/CNN) - Firefighters in China rescued a 4-year-old boy who dangled by his head from a window's guard rail.
Firefighters in China rescued a 4-year-old boy whose head became stuck in a window's guard rail, leaving him hanging four stories above ground.(Source: CCTV/CNN)
According to Chinese state media CCTV, the child climbed out of the fourth-floor window and fell, leaving his head stuck in between the security bars.
The boy's grandfather, who was sleeping, heard him crying and called firefighters for help.
Firefighters put a security rope around the boy's chest while they worked to free him from the rail.
Neighbors held a blanket underneath the child just in case he fell, but the crew managed to pry the bars apart and pull him back to safety.
His condition remains unknown.
Copyright 2019 CCTV via CNN. All rights reserved.


text:
The Ford Transit remains at the top of a car thief's hit list reveals the UK's police unit dedicated to vehicle crime, the ACPO Vehicle Crime Intelligence Service (AVCIS).
Thieves' Favourites
The workman's favourite is the most popular vehicle to be stolen in the first quarter of 2011,* illustrating that it's not just those with high-end vehicles that need to be wary of theft. Not only does a van such as the Ford Transit prove to be valuable in terms of spare parts or as scrap metal, but the lure of potential tools and other contents stored in the back makes it irresistible for thieves.
"Vehicles appearing in the list may surprise motorists," said Head of AVCIS, Detective Chief Inspector Mark Hooper. "Although high-end cars are stolen to order by criminals, those driving more affordable vehicles should not be complacent. Whatever vehicle you drive, security should always be a priority."
The list has been released as part of Car Crime Awareness Week, which runs 13-19 June 2011, in order to raise general awareness of vehicle crime and remind motorists to be vigilant and security-conscious.
Top ten stolen vehicles in Q1 2011
1) Ford Transit
2) Vauxhall Astra
3) Ford Fiesta
4) Volkswagen Golf
5) Vauxhall Corsa
6) BMW 3 Series
7) Ford Focus
8) Mercedes-Benz Sprinter
9) Ford Mondeo
10) Honda Civic
As part of Car Crime Awareness Week, AVCIS is advising motorists to follow these guidelines to prevent their vehicles from being targeted by criminals:
• Ensure that car keys are not left in sight within your house: thieves often fish keys through letterboxes and open windows
• If you have a garage, store your car there whenever possible
• With the summer months approaching, people often leave doors and windows open: ensure your keys aren't easily accessible for opportunist thieves, but equally do not hide them and put yourself at risk of harm from a determined thief
• Lock your car whenever you leave it. Even if you are simply unloading the car, make sure that you remove the keys and lock the vehicle. If your car is stolen through these means if often invalidates your insurance
*1 January – 31 March 2011 AVCIS data on file
Almost 9,000 vehicles across the UK were stolen in just 36 days at the beginning of 2011, reports the Association of Chief Police Officers Vehicle Crime Intelligence Service (AVCIS).
The statistics have been revealed ahead of AVCIS' Car Crime Awareness Week, which takes place on 13-19 June 2011. The initiative aims to raise the public's awareness of vehicle crime methods in order to drive down offences.
This new data illustrates that 50 per cent of thefts were made when a vehicle was left at the owner's home address or close by, including 17.6 per cent through the burglary of properties to obtain car keys.
A third were stolen when vehicles were away from the home and four per cent of crimes during the 36 day sample were made by opportunist thieves, where keys were left in or within easy reach of the vehicle. Shockingly, this would mean that annually 3,400 thefts could be easily prevented through heightened awareness.
These figures demonstrate that vehicle crime continues to be an issue across the UK," said Detective Chief Inspector Mark Hooper, Head of AVCIS. "Criminals will use a variety of means to steal cars, from towing them away or simply driving them off when owners leave the keys in the ignition to burgling houses and sophisticated attacks on manufacturers' security systems.
"Our aim is to increase general awareness, including encouraging motorists to take simple precautions and advise manufacturers of criminals' methods so they can continue to help drive down vehicle crime.
In the lead up and during Car Crime Awareness Week AVCIS will release information on the current state of vehicle crime relating to freight vehicles, agricultural equipment, caravans and motorhomes, as well as to the general motorist.
For more information on vehicle crime and AVCIS visit http://www.avcis.police.uk/ or the Car Crime Awareness Week Facebook page www.facebook.com/CarCrimeAwarenessWeek .
UK lost or stolen vehicles 1 January 2011 – 5 February 2011
(36 day sample*)
Number & Method of theft
• 2,916 (33%) Home address or vicinity where the owner claims to have the keys
• 2,824 (32%) Unattended away from the home where the owner claims to have the keys
• 1,555 (17.6%) Car key burglary
• 1,037 (11.7%) Unrecorded details/unconfirmed loss/vehicle not stolen
• 342 (3.9%) Unattended with keys
• 98 (1.1%) Direct robbery of vehicle
• 54 (0.6%) Acquired by fraud
*Statistics have been generated from the Police National Computer using keywords. Additional offences may have occurred and are not identified within this report. Read more! Read more: http://www.blogdoctor.me/2007/02/expandable-post-summaries.html#ixzz0PTplKsFN


text:
Cooperation to add greater emphasis on areas of raw materials, recovery and utilization, and private operators
Messe Munchen and the BDE, Bundesverband der Deutschen Entsorgungs-, Wasser- und Rohstoffwirtschaft e.V., (Federation of the German Waste, Water and Raw Materials Management Industry) have agreed on a cooperation for IFAT. This International Trade Fair for Water, Sewage, Refuse and Recycling will in the future take place under the name of IFAT ENTSORGA. As part of this cooperation, the concept pursued so far at IFAT will be continued, with greater emphasis on the areas of raw materials, recovery and utilization, and private operators.
"IFAT ENTSORGA will not only provide the most efficient forum for the industry, it will also further expand its position as the world's leading trade fair for the environmental sector," said Eugen Egetenmeir, managing director of Messe München GmbH. "In view of the ever growing number of environmental trade fairs, IFAT ENTSORGA gives orientation to the sector. At the same time it offers companies the opportunity of concentrating their marketing activities at the world's leading environmental trade fair."
Based in Berlin, the BDE, with its 750 member companies, is an association for the recycling and waste management sector. The cooperation between IFAT and ENTSORGA opens up new national and international markets for its member companies.
"Today, on a worldwide comparison, Germany can boast the highest levels of recycling," said BDE President Peter Kurth. "And that is due in large part to the privately owned companies involved in the waste management, sewage and recycling sector, which have invested in the latest technology and systems. This achievement is not an end in itself, rather it is an active and essential contribution to climate protection and careful use of natural resources. IFAT is an excellent platform at which to present the tremendous potential of our sector, and to support the companies within this industry in their efforts to reach out to markets around the world."