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Selecting the number of classes
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Latent Variable Mixture Modeling
posted on Tuesday, August 24, 2004 - 12:08 pm
I read your recent chapter in the Kaplan text on latent variable modeling, and have a question about a paper I'm revising. I have a continuous outcome that is not normally distributed. I modeled it with freely estimated class variances, and found three trajectories. However, the variables are not normally distributed. I gather that I cannot use the LMR LRT for testing the number of trajectories. The BIC supports four classes, but the change in BIC from three to four classes is minimal, and the fourth class is very superficial. Can I use the BIC criteria, since I cannot use the LMR LRT to select 3 classes?
posted on Tuesday, August 24, 2004 - 12:23 pm
Note that the assumption of within-class normality does not imply that the mixture is normal but can be very non-normal. Your observed variables correspond to the mixture. So these mixture models handle non-normal observed variables. Therefore, you can use the LMR. The performance of the LMR - and the BIC - is, however, not sufficiently well-known in most cases. I would not decide on number of classes based only on statistical measures but also interpretability. Given what you say about the superficial 4th class, it sounds like the way to go is 3 classes.
posted on Wednesday, August 17, 2005 - 2:51 pm
I am currently working on a model of behavior change about which there is some controversy in the literature. Specifically, there is some debate regarding the nature of the latent "readiness to change" construct. Some of the debate about the measurement model for the readiness to change construct essentially centers on whether individuals occupy discrete/discontinuous states of readiness or whether the construct is better modeled as continuous. My question is whether evaluation using mixture modeling might be able to shed some light on this, on statistical grounds. That is would a finding that one class best explained the data argue against the notion of different discrete classes and suggest a continuous latent construct? Or is the distinction between continuous and categorical latent variables largely a matter of heuristic concern? Vermunt, for instance, notes that the distinction between latent classes and latent traits is largely a matter of the number of points across which one intergrates. So I suppose the question is does mixture modeling provide statistical evidence regarding the categorical/continuous nature of a latent construct?
posted on Thursday, August 18, 2005 - 9:47 am
That is a good question that we still know too little about. I was less hopeful about this earlier. But I am looking at this currently for categorical items, contrasting latent class modeling with factor analysis modeling and with hybrids of the two, and I am gradually getting the impression that in several cases these models are distinguishable in terms of statistical fit. A one-class model with a continuous factor might fit considerable better or worse than a 2-class model without continuous factors. And often, hybrids fit considerably better than either. True, the classes can be seen as discrete points on a continuum - taking a non-parametric view of the factor distribution (which I think your Vermunt reference is about) - and this matter can only be resolved by relating the classes to other variables - antecedents and consequences - to see if classes are significantly different on those variables. Given that we can now do these analyses conveniently in a general modeling framework, it would be interesting to see more investigations of this type.
Chuck Green
posted on Friday, August 19, 2005 - 8:26 am
Yes, that is the reference to Vermunt to which I was referring. When you discuss hybrids are you referring to latent categorical variables derived from a comnbination continuous latent factors and observed variables?
posted on Friday, August 19, 2005 - 9:23 am
By hybrid I mean a model that has both continuous and categorical latent variables (the outcomes can be of any kind). For example, a latent class model that has factor variation within classes making the items correlate within class.
Patrick Malone
posted on Thursday, July 20, 2006 - 3:33 pm
This is a really simple question, the answer to which has the potential to make me feel a complete idiot.
The general reference to using BIC, ABIC, etc. to select the number of classes is to choose the "lowest" BIC -- in fact, that is the terminology used in the Nylund et al. draft on the website.
But something Bengt said in passing in either Maryland or San Antonio in May stuck with me -- I *think* he said, "the BIC closest to zero."
So do we want lowest value of BIC or lowest absolute value of BIC? I couldn't find guidance in the manual, the technical appendices, or the discussions.
Bengt O. Muthen
posted on Thursday, July 20, 2006 - 3:50 pm
I should have said lowest BIC. Perhaps I was talking about the possibility of a negative BIC which could happen when logL is positive so that the first BIC term is negative - if the sample size and/or #par.'s is small, the negative first tems will dominate the positive second term and BIC will be negative. But even so, we want smallest BIC (not in an absolute sense).
Patrick Malone
posted on Thursday, July 20, 2006 - 7:14 pm
Thank you -- you just saved a paper!
Justin Jager
posted on Tuesday, September 26, 2006 - 9:00 am
I'm using the tech14 option in conjunction with Type=mixture to request a PBL ratio test. I am having a difficult time manipulating which class is the first class identified (and therefore is the class deleted to obtain the c-1 comparison model).
I ran a 3 class solution and a 4 class solution. Comparing the mean estimates across the 3-class solution and the 4-class solution, it is clear which class out of the 4 class solution is the "new" class. Intuitively, it seems to me that I want the "new" class to be the first class identified, so that when comparing the c model to c-1 model the deleted class will be the "new" class.
In order to accomplish this, I re-ran the 4-class solution, but this time used the tech14 option, and listed the start values for the "new" class first, and then listed the start values for the three remaining classes (listing the start values for the largest class last). However, the first class identified is not the "new" class whose start values are listed first.
Given the above I have two questions:
(1) Am I being to stringent in my use of the ratio test by identifying the "new" class and manipulating the start values so that it is the first class identifed?
(2) If the answer to #1 is No, then do you have any suggestions for manipulating the model so that the "new" class is the first class identified?
Bengt O. Muthen
posted on Sunday, October 01, 2006 - 12:14 pm
(1) You don't have to do this. As long as the best loglikelihood values are obtained for a given number of classes, Tech14 is fine.
Christian M. Connell
posted on Friday, October 26, 2007 - 10:05 am
Two questions re: use of Tech14 with LCA:
1) How do you identify the optimal optseed # in cases were several appear to have been replicated (sample output below)?
Loglikelihood values at local maxima, seeds, and initial stage start numbers:
-2571.979 181293 212
-2571.979 688839 273
-2571.979 830570 369
-2571.979 unperturbed 0
-2694.316 350608 334
-2694.316 478421 311
-2696.832 967237 48
-2696.832 247224 94
-2696.832 471398 74
2) in using tech14 with the following values: lrtstarts = 40 10 2500 20; I get a warning indicating that 4 of 5 bootstraps failed to replicate. The p-value for the BLRT is significant, but I assume the lack of replication is a significant problem. How should the lrtstarts be increased, and at what point would you determine that the solution can not replicate?
Linda K. Muthen
posted on Friday, October 26, 2007 - 4:05 pm
You can use any one of the optseeds that result in the best loglikelihood.
Version 5 will have improvements for TECH14. I would wait until it is out and use TECH11 in the meantime.
Sylvana Robbers
posted on Friday, March 28, 2008 - 5:59 am
Dear dr. Muthen,
I would like to react on one of the messages above (July 20, 2006) about the interpretation of the BIC.
Dr. Nagin describes in his book (Group-based modeling of development, 2005) that the lowest absolute BIC-value is preferred, so not the closest to zero.
So, what should be the right approach?
I look forward to your reaction.
Sylvana Robbers
Linda K. Muthen
posted on Friday, March 28, 2008 - 6:46 am
I think the post after that clarified the statement and said the lowest BIC.
Sylvana Robbers
posted on Friday, March 28, 2008 - 7:00 am
Maybe my question was not clear. I mean that dr. Nagin states that the BIC closest to zero is the best, and you propose the lowest BIC, which contradicts each other.
So, is it the lowest BIC or the closest to zero?
Sylvana Robbers
posted on Friday, March 28, 2008 - 7:08 am
By the way, the sentence in my first message should be:
Dr. Nagin describes in his book (Group-based modeling of development, 2005) that the lowest absolute BIC-value is preferred, so the closest to zero.
(without 'not').
Thanks in advance for your time.
Bengt O. Muthen
posted on Friday, March 28, 2008 - 11:35 am
Let me see if I get this right. The Mplus BIC is
BIC(M) = -2logL + r log n,
where L is the likelihood, r is the number of parameters and n is the sample size. In Mplus we want the smallest BIC(M).
Nagin in (4.1) of his book uses the alternative
BIC(N) = logL - 0.5 r log n,
so that BIC(N) = -2 BIC(M). Nagin wants the largest BIC(N).
With BIC(M) the second term is always positive (or non-negative). The first term is typically positive as well because logL is typically negative. The term decreases as the likelihood increases (gets better). So here we want small positive BIC(M) values. In the rare cases when logL is positive (L > 1) the first term is negative and gets bigger negative as the likelihood increases. So here too do we want smaller BIC(M) where say -10 is smaller than -5 (-10 is further to the left on the real line).
I think this in line with my earlier post.
Sylvana Robbers
posted on Monday, March 31, 2008 - 1:55 am
Finally I understand it :-)
Thank you very much for your clear answer!
Alexandre Morin
posted on Friday, April 25, 2008 - 1:01 pm
Could you have made a mistake ?
I've been playing with BICs formulas and something does not add right...
-2 * Bic(M)= -2 (-2LogL + r log n) =
4 logL - 2 r log n, which is not Bic(N).
I believe it is the reverse:
- 2 Bic(N) = BIC(M)
-2 (logL - 0.5 r log n)= -2 logL + r log n.
This does not change the conclusion for the positive versus negative BIC issues however.
Christian M. Connell
posted on Friday, July 11, 2008 - 12:50 pm
Is there a way to test the difference between two LCAs with the same number of classes, but in which one model includes a forced zero-behavior class (i.e., a forced no-substance use class)?
Specifically, I've determined a 4-class solution fits the data best relative to 1,2,3, and 5-class models. However the fit indices for a restricted and unrestricted 4-class model are nearly equivalent:
Adj BIC: 8138.76 (unrest) 8140.35 (rest)
LMR-LRT p-value: .03 (unrest)<.001 (rest)
Entropy: .83 (unrest) .83 (rest)
My sense is that the BIC discrepancy is negligible (?) and that the restricted model should be selected based upon parsimony (i.e., fewer parameters estimated). The actual make-up of the 4-classes is comparable (basically, one of the unrestricted model classes has a high number of non-use individuals), but prevalence of the classes is different across the models, and predictors vary slightly.
Any guidance -- or a specific test that I might run to determine the "best" model?
Bengt O. Muthen
posted on Sunday, July 13, 2008 - 5:13 pm
I think I would go with the unrestricted model if it has the lower BIC, unless you have a specific theory for the existence of a zero class. I am not much for "model trimming", but just reporting the results even if some parameters may not be needed. But if you want to test for one of the classes being at zero probability for all item, perhaps you can use the Wald test of Model Test. For instance, you can define item j's probability as
Model Constraint:
pj = 1/(1+exp(tj));
where tj is the label for the threshold of item j. Then you use
Model test:
You do this for all items at the same time. I haven't tried it, but I think it should work.
Christian M. Connell
posted on Monday, July 14, 2008 - 4:01 am
Thank you for the response. A couple of follow-ups:
Is there any indication as to the "sensitivity" of the Adj. BIC -- given these differences are less that 2 pts?
Would these two 4-class models be considered nested, since the same predictors and number of classes are specified -- only one model includes constraints that force one class to include youth with no use? If so, is it appropriate to conducted a difference in chi-square (or equivalent) test to see whether the constraints significantly worsen fit?
Also, any utility in examining the quality of classification table -- even though entropy is identical, there is some variation both the diagonal and off-diagonal elements.
Bengt O. Muthen
posted on Monday, July 14, 2008 - 8:16 am
There is a literature on how differences between BIC values should be viewed. See for instance
Kass R. E. and Raftery, A. E. (1993). Bayes factors. Journal of the American Statistical Association 90, 773-795
The models are nested, but the assumptions of the likelihood-ratio chi-square test are not fulfilled because the zero-class model specifies parameters that are on the border of their admissible space, namely zero item probabilities conditional on class. Come to think of it, the Wald test would be negatively affected by this too.
The classification table might tell you about differences across models in being able to tell certain classes apart.
Bruce A. Cooper
posted on Monday, July 14, 2008 - 3:23 pm
I'm evaluating GMM solutions to identify the "best" number of classes for an outcome (total sleep time) measured over 14 occasions. There is clearly one large class, and some number of smaller classes, probably 2 or 3.
I take it from Bengt's response in this thread on October 01, 2006 - 12:14 pm that specifying starting values is not necessary to get a valid BLRT test of the K vs K-1 solutions with TECH14. I assume that the way the classes differ would therefore be based on the profile means for the two solutions? So, how to identify the K and K-1 mean profiles that were identified in the BLRT? (I've found that the "K" BLRT solution is not identical to the model solution it follows.")
Bruce A. Cooper
posted on Monday, July 14, 2008 - 3:53 pm
Next question on selecting the "best" number of classes.
I'm puzzled about the interpretation of the VLMR and BLRT tests for the K vs K-1 solutions. I've obtained identical H0 LL values (and -2LL diff values) from TECH11 and TECH14 outputs in the same run, and VLMR will have a p-value WAY larger than .05, while BLRT will have a p-value below .0000. Further, after obtaining BLRT for a sequence of solutions with increasing classes (even specifying LRTBOOTSTRAP=100), I have found that it is always significant at .0000 even when the #classes is getting silly. I've also found that the BIC and SABIC also get smaller with additional classes, even for a large number of classes (5 or more, with most being very small), so not much help there.
Tofighi & Enders (2008) recommended the BLRT and sample-size adjusted BIC as the most useful indices for GMM solutions, and Nylund et al. (2006 revised draft) also like the BLRT for GMM.
Do you have further suggestions on the use of these indices vis a vis the # of classes and substantive interpretations in trying to find the "real" solution?
Bruce A. Cooper
posted on Monday, July 14, 2008 - 5:31 pm
Still another question re the # of classes (my ignorance seems bottomless!) -
How does one decide what values to specify for the LRTSTARTS command? I've read a couple of posts here about it, and the V5 manual (pp. 500-501). The defaults are 0 0 20 5, and you suggest perhaps 2 1 50 15 as an example of a different specification. Why so few for the K-1 class solution? Why that number for the K-class solution? (The question arises partly because of the problematic data set you've helped me with, for which I needed to specify 1500 random starts to get a replicated maximum before going to the BLRT. So, I can use the OPTSEED option from one or more of the replicated solutions when I run the TECH14 analysis, but what issues dictate how to choose the number of draws for the bootstrapped K-1 and K solution analysis?)
Any references would be great, so I don't have to keep bothering you!
Bruce A. Cooper
posted on Tuesday, July 15, 2008 - 7:38 am
Belay that second message re the use of the BLRT resulting in p-values < .0000.
That happened with specified starting values and LRTBOOTSTRAP >= 100, but after running more models last night, and another TECH14 BLRT this morning using the default for holding random effects constant, and allowing the TECH14 to run on its own (no specs for LRTBOOTSTRAP or LRTSTARTS), I got a BLRT that made sense (in this case, not significant)! This was after specifying OPTSEED from an analysis I ran overnight, where I used 4000 random starts and got two (2!?!) replicated maximums for the LL.
I also checked the K-1 LL in the TECH14 output, and it was the same as the maximum from the 3-class solution I had gotten previously with the same ANALYSIS settings. So there's some consistency! and a way to know what the K-1 solution would look like from the TECH14 K-1 model.
I'm still troubled though, that out of 4000 random starts, I would get only two replications of the largest LL (-3880.753), then just one LL that I had gotten multiple replications of in prior runs of this 4-class analysis (-3882.103), then 25 identical LL (-3883.747), with the difference between the largest and smallest LL from these three solutions being only 2.994. Having only two out of 4000 replicated LL still seems pretty chancy, making me wonder about a local maximum that I just happened to hit by chance, twice.
Bengt O. Muthen
posted on Tuesday, July 15, 2008 - 10:28 am
Your 4 last posts touch on topics we teach at our 2-day Mplus Short Courses. One just took place as the psychometric meeting and another one is coming up in November at Ann Arbor. This is in the area of Topic 5 and 6 (see our web site for topics and handouts). It is too large a topic to teach on Mplus Discussion - so I will just give some brief comments.
Topic 5 has on slide 197:
"More On LCA Testing Of K � 1 Versus K Classes Bootstrap Likelihood Ratio Test (LRT): TECH14
� LRT = 2*[logL(model 1) � logL(model2)], where model 2 is nested within model 1
� When testing a k-1-class model against a k-class model, the LRT does not have a chi-square distribution due to boundary conditions, but its distribution can be determined empirically by bootstrapping
Bootstrap steps:
1. In the k-class run, estimate both the k-class and the k-1-class model to
get the LRT value for the data
2. Generate (at most) 100 samples using the parameter estimates from the
k-1-class model and for each generated sample get the log likelihood
value for both the k-1 and the k-class model to compute the LRT
values for all generated samples
3. Get the p value for the data LRT by comparing its value to the
distribution in 2."
Because step 2 generates data according to the k-1-class model, the k-1-class model is easier to fit than the k-class model and therefore requires fewer starts.
Having only 2 replicated best LLs out of 4000 is a sign of a problem - it typically indicates that the model tries to read too much out of the data. This happens when using too many parameters such as too many classes, particularly when the sample size is not large and the data signal is not strong.
Bruce A. Cooper
posted on Tuesday, July 15, 2008 - 11:26 am
Thanks very much for the information, Bengt, and for confirming that getting only 2 maximum LL out of 4000 does indicate a problem with this model! I *have* been worried that I was trying to squeeze water from this stone!
I saw an earlier announcement about the November short course and I have been planning to attend. Meanwhile, I see that your handouts are available to view online and will look through the ones for Topics 5 & 6.
You used to sell the short course handouts through the Mplus website, but I couldn't find the page for ordering them. It's very generous of you to offer them for download now! I like to read as much as I can to find answers to my questions before bothering you folks, so I really appreciate the references you provide and the short-course handouts. Thank you.
Bruce A. Cooper
posted on Tuesday, July 15, 2008 - 5:04 pm
I've run a 3-class GMM to test a 3 vs 2-class model with BLRT. I first ensured that I had a maximum LL that had many replications, then selected two seeds to check the solution. OPTSEED with both seeds produced identical solutions. I ran the model with one of the seeds using OPTSEED, first with no specifications for the TECH14 BLRT. I got a p = 0.3333 with 9 successful BS draws. Then, I ran the model with the same OPTSEED, but this time specifying
to increase the reliability of the BLRT and the K-1 solution. I get identical LL for the K model (same seed), and identical LL for the K-1 model (and it is identical to the LL from the previous 2-class model I ran without BLRT).
However, the p-value for the BLRT is now 0.0000 with 50 successful BS draws. This is the same type of result I referred to earlier, where the BLRT produces p = .0000 no matter how many classes are in the model, when specifying LRTBOOTSTRAP at some number, usually 50, 100, or 150 for the models I've run.
Could you direct me to a reference that will help me understand this inconsistency in BLRT p-values for the same LL and -2LL diff?
Linda K. Muthen
posted on Wednesday, July 16, 2008 - 3:14 pm
We don't have any further references. Please send your input, data, output, and license number to
Bruce A. Cooper
posted on Monday, July 28, 2008 - 11:12 am
Erratum: My posting on July 14, 2008 - 3:53 pm was wrong about the recommendation of Tofighi & Enders (2008) regarding the indices they recommended for choosing the number of classes in a GMM. I have found my own error in a Google(TM) search using their names, and hope this correction will also show up in future Google searches so folks won't be misled by my error.
I wrote that Tofighi & Enders "recommended the BLRT and sample-size adjusted BIC as the most useful indices for GMM solutions" but my memory failed me, and I should have looked at the paper again before citing them. In fact, Tofighi & Enders (2006; 2008) did not evaluate the BLRT at all in their Monte Carlo study of GMM indices for choosing the number of classes, because it had just been added to Mplus when they did their study. Instead, their recommendation was that the sample-size adjusted BIC was best overall index in its performance across a number of conditions, and the Lo-Mendell-Rubin LRT was next best in several situations.
In fact, Nylund, Asparouhov, & Muthen (2006 revised draft; Structural Equation Modeling, 2007) recommended the BLRT for choosing the number of classes in GMM under some circumstances, but their Monte Carlo study did not evaulate very many conditions for GMM.
Sorry for the error!
Bruce A. Cooper
posted on Monday, July 28, 2008 - 11:38 am
Linda -
Thanks for your note on July 16th and the follow-up tech spt via email. My question is "where-to-go-from-here-for-now" in using the BLRT to help choose the number of classes for GMM.
I understand that it is best to set the largest class as the last class when using the BLRT, but (from another posting) that the order of the other classes is not essential. However, I have been unsuccessful in making the largest class the last class, whether I use class intercepts from the solution being tested as starting values, or whether I use the categorical latent variable means. With either method, the program still re-orders the classes so that the largest class is not last in the TECH14 run, defeating the purpose of the BLRT to some extent, and taking a lot of time to run repeated bootstrap tests trying to make the last class the largest. Using the categorical latent variable means, for example, I got this from the prior solution for the 4-class model being tested, in which the last class WAS largest:
Categorical Latent Variables
So, I specified in the Model %OVERALL% statement for the TECH14 run:
[ c#1*-1.146 c#2*-2.576 c#3*-2.860 ];
But no matter how I ordered those three values, the subsequent runs put the largest class as number 2 or 3. Any thoughts about what I'm doing wrong?
Linda K. Muthen
posted on Monday, July 28, 2008 - 11:41 am
Please send your files and license number to
Mogens Fenger
posted on Sunday, August 17, 2008 - 9:28 am
Dear Linda and Bengt,
I�m running a lot of LCA and SEM analysis with and without factors and covariates. A few questions (hope they are not too "simple"):
1) A suppose that the dot in scale correction factor is a decimal identifier.
2) The simplified Satora-Bentler use of scale correction factors in the Difference testing I suppose that the number of parameters are the number of free parameters.
3) When I incorporate co-variates in an analysis the number of subjects may differ considerably because of exclusion of missing values for the co-variates. Concomitantly, the LL and the statistics (AIC etc) change considerably, say with 2100 subjects the BICadjusted may be 31,000 and when incorporating a co-variate only 1700 subjects are included with a BICadjusted being 25,000. The correction for sample size may not seem appropriate. Is it possible to compare the two models by calculating F in chi-square (n-1)*F? Or alternatively correcting e.g. BIC by correcting for sample size (e.g. using the above numbers BICcorr = (25,000/1700)*2100 = 30,882)?
An alternative way to do comparisons is by using the USEOBSERVATION option to only include a full data set. Its easy to do, but becomes tedious as more covariates are included.
4) How do you calculate DF in a mixture model?
5) Is there any rules for using the entropy meassure in decision of best fit?
Linda K. Muthen
posted on Monday, August 18, 2008 - 8:33 am
1. Yes.
2. Yes.
3. Only models with the same set of observed variables and the same set of observations can be compared.
4. Degrees of freedom are relevant only for models where means, variances, and covariances are sufficient statistics for model estimation. In other cases, the number of free parameters is used.
5. Entropy is not a fit statistic.
Mogens Fenger
posted on Tuesday, August 19, 2008 - 1:50 am
Thanks Linda, This cleared up a few things for me. A few follow up questions:
If we in a model with the same set of obersvations replace one covariate with another so the number of paramters and subjects are the same, shoudln't it be possible to compare the two models? If the first model gives a BIC say 31000 and the second 30000, wouldn't you conclude that the second model is a better model and should be preferred?
Entropi: although entropi is not a fit statisitcs, is there any formal way to conclude that an entropy of 0,7 is worse than 0.8 (e.g. in the example above), and would you be able to include such a result in your decission of which model to choose?
Linda K. Muthen
posted on Tuesday, August 19, 2008 - 7:25 am
You cannot change the set of observed variables if you want to compare models.
Entropy ranges from zero to one with the higher value being the better value as far as classification is concerned.
Michael Spaeth
posted on Wednesday, October 29, 2008 - 2:57 am
I have a question concerning tech14. My LRT-value in the real data is dramatically different as compared to the LRT-value in the simulated data sets, which I monitored in the tech8 window (e. g. 124 vs. 66). Should I alter the settings of lrtstarts, or is this not really a problem? In addition the p-values of VMLR and tech14 dramatically differ too (p = .95 vs. p < .001). The real data and generated data H0-LL's (also H1-LLs) in tech14 are the same, as described in the manual. So I think it's a problem with the generated data sets and their H1- and H0-LLs (lrtstarts)!?
Linda K. Muthen
posted on Wednesday, October 29, 2008 - 8:02 am
I would need to see your outputs to answer this question. Please send them and your license number to
Michael Spaeth
posted on Wednesday, October 29, 2008 - 9:12 am
Ok, it takes some days to finally compute the tech14s then I would send it. But I guess it's rather hard to find a hint on only the outputs because BLRT LRT-values of generated data sets are available only on the tech8 window (disappearing after computation).
The following sentence in my last post was nonsense:
'The real data and generated data H0-LL's (also H1-LLs) in tech14 are the same, as described in the manual.'--> I only wanted to say, that I reproduced the H0 and H1 LLs of 'real data k-1 run' in my tech 14 run, probably pointing to the fact that something is wrong with bootrapping of the generated data set. But this is a guess based on the phenomena I described regarding the LLs in the tech8 window.
thank you and so long, michael
Mogens Fenger
posted on Sunday, November 16, 2008 - 1:32 am
Dear Linda and Bengt,
In a SEM mixture model can you compare (e.g. using BIC) two models in which one model treats an indicator as continuous and the second model treats the indicator as ordinal?
Bengt O. Muthen
posted on Sunday, November 16, 2008 - 10:29 am
No, that gives different likelihood scales.
Alexandre Morin
posted on Friday, January 23, 2009 - 12:25 pm
In mixture models (especially with large samples) it sometimes happens that the examined fit indices (CAIC, BIC, aBIC, etc) keep on decreasing while additional classes are added, potentially because of their sensitivity to sample size. In most cases when this happens, the additional classes don't necessarily make sense (susbstantively or statistically: very small classes, classes that only represent a meaningless division of preceding classes, etc.).
In those cases, to choose the number of classes one is left with theory and subjectivity.
It seems to me that in such cases the fit indices (CAIC, BIC, aBIC, etc) associated with varying number of classes might be depicted graphically and interpreted as an EFA scree test to help in the determination of the correct number of classes.
1) Do you have any misgiving about this method ?
3) Do you know of any references of a paper either suggesting the use of this method (scree test) or using this method to choose the correct number of classes)?
Thank you very much.
Bengt O. Muthen
posted on Friday, January 23, 2009 - 5:53 pm
1) No
2) No
However, you need to always be open to the possibility that you are fishing in the wrong pond - the model family you are in may not be the best for the data and if you switch model family you might find a minimum BIC. For example switching from LCGA to GMM.
Matthew Cole
posted on Wednesday, June 10, 2009 - 4:56 pm
Hi Linda and Bengt,
Can you tell me what the difference is in Tech11 between the VLMR and the adjusted LMR?
Also, you recommend that the last class is the largest class. However, you also recommended that model identifying restrictions not be included in the first class. Would you consider starting values for the first class to be model identifying restrictions? I am currently using starting values for the first class to make it the smallest class, thereby making sure that the first class for Tech11 is not the largest class.
Thanks, Matt
Linda K. Muthen
posted on Thursday, June 11, 2009 - 11:15 am
The authors provided a post-hoc adjustment. You can see the original article for the details. We do not use the adjusted LMR.
Starting values are not model identifying restrictions. These would be some restrictions on model parameters.
I would use starting values to make the last class the largest class not the first class the smallest class.
Keng-Han Lin
posted on Thursday, February 18, 2010 - 1:28 pm
Hi Linda and Bengt,
I'm using LCA on a complex survey data with 48 indicators (13 of them are continuous). The BIC suggests 6-class model, 46213.84(2-class model) 45634.95(3) 45419.72(4) 45322.00(5) 45195.95(6) 45290.84(7), but we are wondering if there's other rule we could follow to better determine the number of class.
BLRT(tech 14) doesn't support for complex data. The results (p-value )of LMR test are as following, 0.047(2-class model) 0.373(3) 0.582(4) 0.591(5) 1.000(6) 1.000(7). In 3-class model which has LMR p-value of 0.373, does it suggest 2-class(H0) is good enough in our case?
If so, which statistics should I depend on? Or other criteria I should take into account?
Thank you so much for your help.
Linda K. Muthen
posted on Thursday, February 18, 2010 - 2:03 pm
Perhaps the following paper which is available in the website can help:
Nylund, K.L., Asparouhov, T., & Muthen, B. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling. A Monte Carlo simulation study. Structural Equation Modeling, 14, 535-569.
You should also consider whether the classes have any substantive or theoretical basis.
Ingrid Holsen
posted on Tuesday, December 07, 2010 - 5:14 am
I am investigating trajectories of body image over time, 13 to 30 years. The sample in GMM is 1082. I have problems deciding number of classes (we are several here who are puzzled).
3 classes; BIC the lowest, but LMR-LRT 0.079, with 4 classes it is 0.038). Entropy for 3 classes is 0.727 and for 4 classes 0.734 (not very high!). However, the 4 class solution has one class which is only 1.5%, that's 15 persons, don't make much sense. I have learned to trust the LMR-LRT, but find it hard to proceed with 4 classes due to the sample size in each class. What is your opinion, also regarding the relatively low entrophy?
Best regards, Ingrid
Ingrid Holsen
posted on Tuesday, December 07, 2010 - 6:32 am
Adding to my questions above... The Bootstrap test is significant for both a 3 and 4 class solution. The LMR-LRT value above is of course the p-value.
A collegue suggested to add
to my modelcommand, then the 3 class solution performed somewhat better. The LMR-LRT (p) 0.024 ( 4 class (p) 0.21 ). However the Entropy is around 0.70 (a bit lower for both a 3 and 4 class solution).
Thanks for your help.
Linda K. Muthen
posted on Tuesday, December 07, 2010 - 10:34 am
The significance of LMR-LRT should be interpreted only the first time it is greater than .05 not after that. Your first post suggests two or three classes. The meaningfulness of the classes should determine your choice.
tomas dvorak
posted on Thursday, January 03, 2013 - 6:54 am
a have a question about selecting the number of classes in LCA. For any reasonable number of classes Tech11 and Tech 14 show zero p-values. Also BIC decreases (for 3 or more classes) rather slowly. Does this mean LCA does not fit the data and should not be used? On the other hand, 4 and 5 class solutions have high entropy (around 0.9) and(given my research goals) seem to make sense. Is it ok to use LCA and choose a solution that makes sense with respect to my research goals?
Thanks for your help,
Linda K. Muthen
posted on Thursday, January 03, 2013 - 11:36 am
This may point to the need for a different type of model, for example, a factor mixture model. If your indicators are categorical, TECH10 might help you see what the problem is.
Alysia Blandon
posted on Tuesday, June 11, 2013 - 9:31 am
I am running a Latent Profile Analysis with 5 continuous variables. My sample size is 430. I have been able to replicate the loglikelihood values for the 1 and 2 class solutions. I have also been using the steps outlined by Asparouhov & Muth�n webnote 14 to test the number of latent classes using the BLRT from TECH 14 using the OPTSEED option. Based on those recommendations I get the warning THE BEST LOGLIKELIHOOD WAS NOT REPLICATED. I continue to get the message even after increasing LRTSTARTS to 50 20 100 20 and using LRTBOOTSTRAP from 100 through 500. In all of these, the loglikelihood for the k-1 class is the correct one from step 1.
Bengt O. Muthen
posted on Tuesday, June 11, 2013 - 10:31 am
Please send input, output, data and license number to
. Send the outputs from all the steps recommended in Web Note 14.
Miriam Forbes
posted on Monday, March 03, 2014 - 7:16 pm
Hi Linda and Bengt,
In my LPA and FMA analyses, the BLRT remains significant (at .0000) for every analysis. My samples are n = 533 and n = 181, so I'm not sure it's a result of too much power. Shaunna Clark thought she had read cases of this, and suggested relying on ICs and substantive interpretation of the models (and the other LRTs, which do reach non-significance). I was wondering whether you know of any citations to justify this kind of decision?
Thanks and all the best,
Bengt O. Muthen
posted on Tuesday, March 04, 2014 - 6:50 pm
I would use BIC and substantive interpretation. The Nylund et al paper also shows that BIC is one of the top indices (second best?). Notwithstanding the Nylund et al article, my experience is that BLRT is less dependable in practice for some reason.
Miriam Forbes
posted on Tuesday, March 04, 2014 - 9:43 pm
Thanks, Bengt! I'll emphasise the Nyuland et al. paper.
All the best,
hazel liao
posted on Wednesday, June 10, 2015 - 5:08 am
As far as I know, BIC decreases when the model has less free parameter which means the model is parsimony and we should choose the lowest BIC after compared models.
However, when I compared models ( 2-group with 16 free parameters, 3-group with 22 free parameters, 4-groups with 28 free parameters), BIC/ adjusted BIC decreased when group number increased. Is this output reasonable?
Linda K. Muthen
posted on Wednesday, June 10, 2015 - 1:30 pm
BIC depends not only on the number of parameters but also on the loglikelihood. If the loglikelihood increases faster then the penalty for the number of parameters, BIC will decrease.
hazel liao
posted on Wednesday, June 10, 2015 - 7:59 pm
You are right, loglikelihood increases faster in my example.Thank you very much!!
By the way, I know we should minimize fit function, but what relation between the loglikelihood and Fit function?
Sabrina Thornton
posted on Tuesday, October 27, 2015 - 1:52 am
I read 'Using Mplus TECH 11 and TECH14 to test the number of latent class' by Asparouhov & Muthen. I presume that it is appropriate to use AUXILIARY(bch) command in these tests since I do have a distal outcome variable that was predicted by the resulting classes. It does make sense to me to include this common as done in the automatic 3 step approach.
Thanks in advance for your help.
Jon Heron
posted on Tuesday, October 27, 2015 - 3:13 am
it's pretty much standard practice to determine the number of classes using an unconditional mixture model without either covariates or outcomes.
In theory you might, in a GMM, have a covariate which explains some intercept variance and hence reduces the number of classes but I've only ever seen this done once in a publication.
Christy Denckla
posted on Friday, October 28, 2016 - 1:39 am
TECH 14 is indicating that with 1000 random starts I am only getting 2
successful bootstrap draws for 3 vs 4 classes. While the LRT values make sense at 4 classes (p=< .01), the BLRT p-value is 1.0. I checked for a local solution by testing if the 4 class model parameter estimates were replicated across two different models with seed values from the two best loglikelihood values, and I got replicated parameters.
We have specified freed time parameters given the likelihood of non-linear time (looking at depression before and after childbirth among a bereaved sample). Our sample size is >10,000.
Based on an earlier post, it seems that only 2 successful bootstrap draws with 1000 random starts could be a issue. What could be causing the failure to replicate no more than 2LLs? Is the BLRT pointing to a problem in our model specification?
Bengt O. Muthen
posted on Friday, October 28, 2016 - 12:24 pm
Regarding your second sentence, there is no LRT for mixtures unless you are looking at a frequency table.
Regarding BLRT problems, see our web note 14.
samah Zakaria Ahmed
posted on Monday, February 13, 2017 - 12:04 pm
depending on AIC and BIC, i found that 4 classes are suitable for my latent class variable in spite of depending on the entropy, i found that 2 classes are suitable. how can i take the correct decision?
Bengt O. Muthen
posted on Monday, February 13, 2017 - 5:54 pm
Q1: Yes.
1. See Topic 5's treatment of FMM.
2. See the paper on our website:
Asparouhov, T. & Muthen, B. (2015). Residual associations in latent class and latent transition analysis. Structural Equation Modeling: A Multidisciplinary Journal, 22:2, 169-177, DOI: 10.1080/10705511.2014.935844. Download Mplus files.
For these general analysis strategy questions you want to use SEMNET.
Bengt O. Muthen
posted on Monday, February 13, 2017 - 5:56 pm
Q1: Yes.
1. See Topic 5's treatment of FMM.
2. See the paper on our website:
Asparouhov, T. & Muthen, B. (2015). Residual associations in latent class and latent transition analysis. Structural Equation Modeling: A Multidisciplinary Journal, 22:2, 169-177, DOI: 10.1080/10705511.2014.935844. Download Mplus files.
For these general analysis strategy questions you want to use SEMNET.
Katie Gelman
posted on Saturday, June 17, 2017 - 7:29 am
Dear Drs. Muthen,
I have a question about assessing the stability of classes, specifically stability of individuals within class in a GMM. Is the bootstrap ever used to replicate and compare resulting class membership once the best fitting number of classes has been established? If so, how would I do this?
Many thanks.
Virginia Rangel
posted on Friday, June 30, 2017 - 12:42 pm
I am working on trying to create a typology (the literature suggests three types) but all of the analyses, regardless of the model, suggests a one-class model. To arrive at this conclusion, I focused on interpreting the LMR test, which for all classes (i.e., 2, 3, etc.) has a p value much greater than 0.05 (e.g., 0.2, 0. 5, etc.). Is this the correct interpretation, or should I look to other indicators (e.g., BIC) or to the final class counts (or to something else), which might suggest a different number of classes?
Bengt O. Muthen
posted on Friday, June 30, 2017 - 5:06 pm
Just use BIC.
Kathy Xiao
posted on Monday, August 21, 2017 - 2:55 pm
I have around 14 binary and categorical variables for LCA, but starting from 2 classes, the p-value of LMR is non-significant, and it never becomes significant. May I know any explanation of this situation? Thanks very much!
Bengt O. Muthen
posted on Monday, August 21, 2017 - 4:59 pm
You may have only 1 class. Check BIC.
Kathy Xiao
posted on Monday, August 21, 2017 - 5:02 pm
Thanks for your reply. The BIC and Adjusted BIC kept decreasing from 1 class and more. So I am not sure which class to select.
The entropy increases till 4-class model and then decreases.
Bengt O. Muthen
posted on Monday, August 21, 2017 - 5:17 pm
I would go with BIC and when, as here, it doesn't help, I would change the model, e.g. introduce residual correlations or a factor. See our handouts and video for Topic 5, plus the paper on our website:
Asparouhov, T. & Muthen, B. (2015). Residual associations in latent class and latent transition analysis. Structural Equation Modeling: A Multidisciplinary Journal, 22:2, 169-177, DOI: 10.1080/10705511.2014.935844. Download Mplus files.
Kathy Xiao
posted on Monday, August 21, 2017 - 5:30 pm
What if the BIC keeps decreasing to 8 classes and it is substantively not meaningful?
If I don't change the model, can I select the model by (1) largest entropy; (2) relatively small BIC; (3) substantive interpretation when the p-value of LMR are all non-significant?
Thanks for answering and sharing the article!
Bengt O. Muthen
posted on Tuesday, August 22, 2017 - 5:24 pm
I would not use entropy as the major factor in deciding on the number of classes. That's like choosing a SEM model based on R-square instead of model fit.
Read what I suggested instead.
Daniel Lee
posted on Sunday, December 24, 2017 - 9:26 pm
Hi Dr. Muthen,
In my Latent Profile Analysis, the AIC, BIC and adjusted BIC were lower (>100) in the 3 class model, but the LRT tests were not significant.
I am not sure what to make of these results. Does it mean I should proceed to examine a 4-class LPA model? Or, should I just accept the 2-class LPA model (even though the BIC, AIC, and adjusted BIC decrease by over 100 units)?
Thank you for your help.
Bengt O. Muthen
posted on Tuesday, December 26, 2017 - 4:06 pm
Go by BIC.
Emily Gagen
posted on Saturday, January 20, 2018 - 12:31 pm
Hi Dr. Muthen,
In my latent class analysis, the AIC and ssaBIC decreased with each increase in number of classes, but the BIC increased at each step. Entropy increased up until the 4 class model, and decreased with 5 classes. The 3 class model is most consistent with the literature and is the most interpretable. I'm mostly wondering whether I should be concerned that the BIC value was increasing with each successive model.
Thank you for your help!
Bengt O. Muthen
posted on Saturday, January 20, 2018 - 4:41 pm
You should indeed be concerned that BIC doesn't decrease with increasing number of factors. If BIC is worse for 2 classes compared to 1 class (non-mixture), I would stop and not use a mixture. Perhaps your sample size is extreme.
Emily Gagen
posted on Saturday, January 20, 2018 - 6:00 pm
I apologize, I wasn't clear - the BIC decreased (improved) for 2 classes compared to 1 class, but then increased again for each subsequent model (3-5). Separately, the AIC and ssa BIC decreased each time. Is this an indication that I should choose a 2 class model rather than 3? For reference, my sample size is 134 - I'm not sure what you mean by extreme. Thank you for your help.
Bengt O. Muthen
posted on Sunday, January 21, 2018 - 5:21 pm
I would choose 2 classes.
Larissa Gaias
posted on Monday, January 22, 2018 - 12:16 pm
Hello, I am having a related problem to Kathy, but it is particularly an issue related to trying to account for nesting in my data.
I have a Latent Profile Analysis with 6 indicators. I have 103 teachers who are in 9 schools. I am trying to account for non-independence using type = complex, cluster is schoolid.
My BIC and AIC continuously decrease as I add a profile. When I don't account for clustering, the LMR LRT suggests a 3-profile model (I include one covariance between two indicators, constrained to be equal across profiles). When I do account for clustering, I get non-significant LRTs for all profiles. However, the estimates of the indicators for each profile do not change regardless of whether clustering is accounted for or not.
I am wondering about the appropriateness of the clustering in this situation (is 9 clusters too small) and why we might be seeing this issue with fit even if the results don't change? Can I trust the results of the non-clustered LPA if the results are identical when we account for clustering? Thank you!
Larissa Gaias
posted on Monday, January 22, 2018 - 2:26 pm
I should add that I tried adding covariances and a factor to the model with clustering and it did not help with distinguishing between the classes using the LMR LRT.
Bengt O. Muthen
posted on Monday, January 22, 2018 - 5:09 pm
9 schools is too few for Complex (and Twolevel) - you need at least 20. Instead, use 8 dummy variables as covariates to represent the schools.
Larissa Gaias
posted on Monday, January 22, 2018 - 6:33 pm
Thank you! Is the case only for LPA/LCA or for all models?
Bengt O. Muthen
posted on Tuesday, January 23, 2018 - 5:46 pm
For all models.
posted on Wednesday, March 14, 2018 - 3:08 am
I'm running an LPA with 6 indicators and a sample n > 2000. I'm comparing different latent-class-solutions. The BLRT is for every solution significant. The BIC (and SABIC) dicreases with each class more. However, there is a "kink" (comparatively big dicrease) in the between the 5-class and the 6-class solution:
classes BIC
1 33468
2 30722
3 30083
4 29615
5 29375
6 28561
7 28401
8 28253
9 28133
Is this a sign that I should choose the 6-class-solution?
Thanks for a reply!
Bengt O. Muthen
posted on Wednesday, March 14, 2018 - 3:27 pm
Perhaps. But the fact that BIC doesn't show a minimum may reflect the need to include residual correlations for certain pairs of variables; when such correlations are included as needed, BIC may show a minimum. A factor mixture model may be helpful in finding such residual correlations.
But if you don't feel comfortable with such an analysis excursion, you might want to simply pick 6 classes and report the BIC decline over classes as an argument.
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That's what I got, too (or... close enough. I got a mean of 38.5 with a standard deviaiton of 12.6). A "normal distribution" occurs when 68% of the population is within 1 standard deviation of the mean. This survey shows that 69% are within 1 standard deviation from the mean, so we are very close to a normal distribution. Surprising! I thought we were more negatively skewed (skewed towards the higher age group) than that, but I guess not.marcfrm wrote:If I did the math correctly:
average: 36.6 years
standard deviation: 12.65 years
69% of the riders are between 36.6+/-12.65 years

subset: commoncrawl


text:
Discussions about eggcorns and related topics
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The forum administrator reserves the right to request users to plausibly demonstrate that they are real people with an interest in the topic of eggcorns. Otherwise they may be removed with no further justification. Likewise, accounts that have not been used for posting may be removed.
Thanks for your understanding.
Chris -- 2018-04-11
The roots of the English verb "ding" run deep. One use of the verb, popular from the fourteenth to the eighteenth century, meant to beat, knock, crush, or press a person. This usage probably derives from a Norse word meaning "to hammer." But in this period "ding" also meant to make a ringing sound, a usage that may be onomatopoetically derived from the noise made by a bell. This latter meaning extended itself to mean saying something repeatedly with the intentions of driving it into the other person's mind.
These two usages of "ding," derived from different sources, have cross-fertilized each other. One of these usages, or perhaps both of them, have given rise to a modern sense of "ding" that means to penalize someone, or to make someone the object of abuse. We talk about "dinging someone for a loan." Or a referee that "dings the team two points" for breaking a rule. Or teachers that "ding" students for not doing their homework.
The term "golddigger" put in an appearance in the Roaring Twenties. A golddigger was a woman who became a companion of a rich male in order to mine his gold. It was inevitable, I suppose, that some one would miss the metaphor behind the word "golddigger" and change the term to "golddinger." The web has a few examples:
Reality TV forum: "I just watched Meri-de's video interview on The Outback Jack web-site and she said that Jack confided in her that he thinks that Marissa is a golddinger." (http://www.fansofrealitytv.com/forums/o … rview.html)
Blog post: "This Tomi Rae…was nothing but a user and a golddinger" (http://www.artharris.com/2007/01/22/tom … -kids-too/)
TV message board: " If she is so rich why did she have to call everyone to get cash to bail him out? Slade…he deserves the houchy gold dinger." (http://boards.bravotv.com/lofiversion/i … 85428.html)
Forum post discussing Fosset: "okso he is dead not sean for 3 mouths and she not a gold dinger " (http://www.topix.com/forum/chicago/T2G8J9R835DBIE14U/p2)
Last edited by kem (2015-12-18 13:02:51)
Hatching new language, one eggcorn at a time.
Nice one, Kem! I've grown to expect your lucid and rigorous analysis, but how in the world wide web did you ever dig up this little gem?
What a difference a key makes; finger >> dinger >> bell >> (telephone) ring tone. I can just imagine a 007 movie theme lyric like, "The man with the golden 'phone'..." So, it's no surprise that I got an extra kick out of the imagery in a couple of other web examples concerning Goldfinger cellphone ring tones:
For the Men, could you marry a woman of a different religion, and if however you married such woman, would you compel her to change her religion for yours?
[Response] It depends on the dowry… a few oil platforms could help a lot to open my heart to some Arab beauty…
[Response] In other word, you're a goal digger? lol
my hands are full put it in my shirt pocket…yea THAT happens ALL THE TIME (eyes rollimg)…guy has massive hands, what did she think would happen…oh, he's rich & already has a bad character rep…can you say GOAL DIGGER!!!
I'm from the ghetto. Walking 20 miles until you grow up and get a chance to buy a bicycle, but then here comes the man with the money and sometimes you as a young youth and you have this girl that you like. But you have some goal digger girls. I'm not saying you have good girl, you have excellent girls out there, but you still have goal diggers and you still have to be looking out for them.


text:
Winter Apple and Dried-Fruit Pie Recipe
This variation on apple pie lends some variety in texture and flavor. You can (and should) customize the sweetness, based on the levels of tartness of the apples and dried fruits that you choose.
Read more: Pie of the Week: Winter Apple Pie with Dried Fruit
- Yield:serves 8
- Active time: 1 hour
- Total time:4 hours
- One recipe Easy Pie Dough, one half shaped and chilled in a pie plate, the other rolled out flat and chilled on a floured sheet pan
- 8 medium Golden Delicious, Braeburn, or other baking apples peeled, cored, and sliced into 1/4-inch slices
- 10 ounces dried fruits (a combination of dried cherries, chopped dried figs, dried cranberries, currants, raisins)
- 1 tablespoon zest from one lemon
- 6 ounces granulated sugar (adjust to taste, depending on sweetness of apples and dried fruits)
- 1/2 ounce cornstarch
- 1 teaspoon cinnamon
- 1 pinch grated nutmeg
- 1 whole egg, lightly beaten
- Sanding sugar for top (optional)
Adjust oven rack to lower position and preheat the oven to 425°F. Place apple slices in a large bowl or pot. Pour boiling water directly over top. Cover and set aside at room temperature for ten minutes. Drain apples well and transfer to a large bowl. Allow to cool for 20 minutes, tossing occasionally. Transfer to a large bowl and toss with the dried fruit. Whisk together the sugar, starch, and spices and add to the apple mixture. Toss until well-coated. pour the contents of the bowl into the chilled pie shell. Cover with the top crust, either by cutting the chilled top crust into strips and weaving a lattice, or by covering the pie with the whole crust. Crimp the sides and chill the pie for 15 - 20 minutes.
When ready to bake, brush the top with egg wash and sprinkle with sanding sugar. If you've covered the pie with a whole top crust, cut slits in the top. Bake for 20 minutes, then turn down the heat to 375°F and bake for additional time: for non-lattice, approximately 40 minutes, for lattice, approximately 50, both rotating halfway through. The crust should be golden brown and the filling should be bubbling. If parts of the crust start to look too dark, cover the darker parts with small patches of foil to protect them from the heat.
Allow the pie to cool completely before serving. You may make this pie in advance, but it is best served the same day that you bake it.
This Recipe Appears InPie of the Week: Winter Apple Pie with Dried Fruit Thanksgiving Pie Countdown: Apple and Dried Winter Fruit Pie
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its the short cut for south central cartel a rap gangster group form the south central.
Evil side on the cut thang S.C.C.
by OG.Rhymez June 06, 2006
An internet abbreviation for "sitting in chair chuckling." It is to replace LOL for work related situations.
LOL is played out.
LOL is played out.
Burt: Hey, what do you think of the Heat's chances this season?
Ernie: SCC!
Ernie: SCC!
by Borpit December 21, 2011
SceneAccess.org, a private Bittorrent tracker with one of the best pre speeds on the net
guy1: i have 2 invites to scc
guy2: what's scc?
guy1: stfu and gtfo and diaf you newb
guy2: what's scc?
guy1: stfu and gtfo and diaf you newb
by Joseph Bilks December 08, 2007
SCC: an abbreviation for Terminator: the Sarah Connor Chronicles (aka T:SCC, TSCC).
A TV show with Terminators.
A TV show with Terminators.
Save the scc, bring it back !
by m_33 May 28, 2009
(n.) (plural) Abbreviation for Sabretooth Crotch Crickets. Nastier than your usual pubic lice. See Sabretooth Crotch Crickets and SCC.
You hoe yourself around like that and you might end up with SCCs like you wouldn't believe.
Damn SCCs keep screamin' at me every time I get close to your mom's snatch!
Damn SCCs keep screamin' at me every time I get close to your mom's snatch!
by O May 03, 2004
SCC (Simons Closet Closet) originated late one night after discovery of a Closet's Closet. Only original members of the SCC are aloud to be part of the club.
Person 1- Hey, lets go back to the SCC and Party it up
Person 2- Sounds good, no outsiders allowed in though..
Person 2- Sounds good, no outsiders allowed in though..
by S.T.M March 04, 2012
S.C.C. stands for Snow Cone Click and is a fresh west coast social group. Usually very legitiment and hella good looking guys getting all the bitches. Staten Island is their first language. Only the select few can experience the joy of being in this awesome, fun loving group and rolling straight to the room, taking of the girlies clothes and turning their asses around!! NO ONE can put it down like S.C.C.
man, s.c.c. gets all the hot girls.....i wish i could get in!!!! but my name is rene so whatever....im gonna go cry
by S.C.C. December 26, 2007


text:
Cultural identification doesn't cut it. And unless you can write a compelling diversity statement about being Native American I don't think checking the box will help all that much.[/i]If you were 1/32 but grew up on a reservation, sure, you could be Native American. But you, OP, are not.
I am 1/4 Muskogee Native American, and I check the box because I ALWAYS have. When I was 6 years old taking my first standardized test, when I didn't even know what AA was, I checked NA because my grandmother and father had made me proud of my culture. Its a part of who I am. It doesn't sound like this is the case with you, please don't check it.
A little part of me died when I read the op


text:
See archival images, stills from reenactments, and images of individuals featured
Slave Ship Mutiny
Behind the Scenes
Learn how the story of Massavana and The Meermin was adapted to television through interviews with historian Nigel Warden and producer/director Joe Kennedy. See what it was like to bring this story to life with behind-the-scenes footage of the actors, crew and interviews with drama director Nic Young. Understand how much the story means to South Africans such as heritage activist Lucy Campbell.
Slave Ship Mutiny
The slave ship Meermin set sail from Madagascar for South Africa in 1766, but the ship would never make it to Cape Town, the slaves mutinied and managed to overpower the Dutch crew, ordering the ship be sailed back to Madagascar and freedom.


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What would be the be the easiest way to go about getting madsonic and owncloud on the raspberry pi?
I am looking to retire an old win 98 machine. Its running Ubuntu headless its loud as crap and is probly cugging electricity.
Users browsing this forum: No registered users and 1 guest


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Bird Dress in my shop now, photographed beautifully by my flower Danniella Jaine
It's all going on, always the same and they prove what we were talking about. But I fear there are two extremes and I'm forever wanting to be in the middle and forever struggling to or from one end of this teeter - tatter. Playground talk again. I think we understand; the same page, but then I go back to what I was saying before. Do you know that it was beautiful? ... sometimes they want to keep beautiful things and make them last forever, maybe this time they will be you, because it's definitely me - but I'll never tell you that, because we said they think the impossible. We stayed that way for years in a few hours... felt like home. I miss that.


text:
I'm a coffee drinker who appreciates tea, but until my sister got into it, I mainly drank a few flavored bagged teas (and of course, Southern sweet iced tea). I pull out the Throat Coat and Breathe Easy when I'm sick, but aside from that, teas have never been a daily part of my life. However, my sister has exposed me to a broader range of flavors, and to loose teas, so I'm now enjoying tea more often.
Richmond, VA


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U.S. stocks erased losses in the final 15 minutes as investors bought shares before changes to MSCI Inc. indexes and weighed developments in budget negotiations. Commodities rose. Treasuries were little changed.
The Standard & Poor's 500 Index closed up less than 0.1 percent at 1,416.18 at 4 p.m. in New York, erasing an earlier 0.3 percent drop and capping a second straight weekly gain. Yields on 10-year U.S. notes were little changed at 1.62 percent after losing seven basis points during the week amid concern about the U.S. budget talks. The S&P GSCI Index of 24 raw materials added 0.1 percent as industrial metals led gains.
The MSCI All-Country World Index of stocks added 0.1 percent. Some $321.9 billion was invested in exchange-traded funds linked to MSCI indexes at the end of October, according to MSCI, and about $3 trillion of funds are benchmarked against its indexes globally. Earlier losses in U.S. equities were triggered by skepticism that lawmakers will agree on a budget to avoid the fiscal cliff of automatic spending cuts and tax increases.
"Rebalances can sometimes create price dislocation and excessive volatility," Mike Shea, a managing partner at New York-based brokerage firm Direct Access Partners LLC, wrote in an e-mail. "There's a fair amount of potential for price dislocation there."
MSCI Changes
Changes to MSCI's global indexes were implemented at the close of trading today, causing the S&P 500 to jump as much as 0.2 percent to its highest intraday level of 1,418.86 within the final two minutes of trading before paring most of its gain by the close. The eight U.S. companies that were added included homebuilder Lennar Corp. and Under Armour Inc., a sportswear maker. For-profit education company Apollo Group Inc. and coal miner Walter Energy Inc. were among the seven stocks removed.
MSCI made the changes after a semi-annual review. Amendments to indexes can alter share prices as passively managed funds buy and sell stocks to mirror the benchmark indexes.
"A lot of the volatility near today's close is due to the MSCI rebalance," Ryan Larson, the Chicago-based head of U.S. equity trading at RBC Global Asset Management (U.S.) Inc., said by e-mail. His firm oversees $250 billion. "Outside of that, we've been trading solely on political rhetoric in Washington."
Stocks, commodities, bonds and the euro rose this month on signs of growth in the U.S. and Asia and speculation political leaders in America and Europe will take steps to keep their economies from deteriorating.
Market Movers
The S&P 500 closed at the highest level since the election on Nov. 6 and capped a 0.3 percent gain for November. U.S. equity funds tracked by EPFR Global attracted more than $10 billion in net inflows during the fourth week of November, their best showing in more than a year, according to the Cambridge, Massachusetts-based research firm.
Utility, telephone and consumer-staples companies led gains among the index's 10 main industry groups today, while industrial and technology stocks retreated. Wal-Mart Stores Inc., Home Depot Inc. and Hewlett-Packard Co. added at least 0.8 percent for the biggest gains in the Dow Jones Industrial Average.
VeriSign Inc. plunged 13 percent, the most in the S&P 500, after a contract extension letting the company register Web sites ending in .com limited price increases. Yum! Brands Inc. lost 9.9 percent after saying quarterly same-store sales in China will decline. MetroPCS Communications Inc. rallied 5 as Guggenheim Securities LLC said the wireless carrier may get a bid from Sprint Nextel Corp.
Economic Data
Stocks also fell earlier as government data this morning showed spending by U.S. consumers unexpectedly declined and incomes stagnated in October as superstorm Sandy kept those in the Northeast from getting to work or from shopping. Purchases decreased 0.2 percent, the weakest reading since May, after a 0.8 percent gain in the prior month, Commerce Department figures showed. Personal incomes were unchanged.
The Stoxx Europe 600 Index slipped 0.2 percent today, erasing earlier gains in the final hour of trading. The regional benchmark index climbed 0.9 percent this week, extending the November advance to 1.5 percent.
The euro appreciated 0.5 percent versus the yen, extending this month's advance to almost 4 percent. It also capped a fourth-straight monthly gain versus the dollar.
German lawmakers approved today Greece's latest rescue package designed to ease terms for aid and help resolve the three-year-old debt crisis.
Next page: Asian Currencies
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The Vineyard At Hershey partners are, from left, Jason Reimer, president; Mike Wilson, vice president; and L. Paul Vezzetti, winemaker. On Feb. 23, they celebrated the winery's first anniversary with their new Sparkling Moscato at their facility. Photo/Beth Moore Baker
The Vineyard At Hershey partners are, from left, Jason Reimer, president; Mike Wilson, vice president; and L. Paul Vezzetti, winemaker. On Feb. 23, they celebrated the winery's first anniversary with their new Sparkling Moscato at their facility. Photo/Beth Moore Baker
Like a rare vintage wine, The Vineyard at Hershey has been highly sought out since decanting itself to the world last February.
The Vineyard At Hershey partners are, from left, Jason Reimer, president; Mike Wilson, vice president; and L. Paul Vezzetti, winemaker. On Feb. 23, they celebrated the winery's first anniversary with their new Sparkling Moscato at their facility. Photo/Beth Moore Baker
Like a rare vintage wine, The Vineyard at Hershey has been highly sought out since decanting itself to the world last February.
The Londonderry Township winery attracted more than 15,000 people in its opening year, plus an additional 1,100 for a merlot release party in September, President Jason Reimer said.
Winery sales flowed to the tune of nearly 3,000 gallons — double what its partners had expected.
And projections are to do twice that much in this second year, with a nearly completed 12,000-square-foot building that will house production and expand the winery's ability to entertain.
The new facility, which includes a deck overlooking the vineyard, will be home to the vineyard's "Decked-Out Live" summer concert series.
"The vineyard should be a place you want to come out to," Reimer said. "Our goal is to immerse you in the experience."
For the partners at The Vineyard at Hershey, that means more than creating a top-notch wine menu and first-rate guest experience.
They believe in fostering regional tourism and making the Hershey-Harrisburg area a destination, which not only helps solidify a long-term future for their vineyard and others like it, but also provides a bump in consumer spending at other local attractions and hospitality venues.
Achieving that requires thinking outside the box, Reimer said.
Through on-site dining collaborations, emphasis on facility rentals, sales to area restaurants and private label distribution for corporate clients — blended with a heavy dose of social media interaction and promotion — the vineyard has been the catalyst for growth in Hershey Harrisburg Wine Country.
"It's all working hand in hand," said Reimer, who led the charge in creating the wine trail program last spring.
Growing trail
With marketing help from the Hershey Harrisburg Regional Visitors Bureau and a share of Dauphin County hotel tax funds — $50,000 this year — the 15-winery trail is having a measurable impact on foot traffic and sales at member wineries.
"We saw upward of 200 people during that (ValenWine's Day) weekend," said Candace Smith, a spokeswoman for Mount Hope Estate and Winery in Rapho Township, referring to the two-day wine and chocolate event that ran before Valentine's Day.
Mount Hope is one of three recent additions to Wine Country.
"I would expect we would see at least a 15 percent increase in foot traffic," Smith said of the winery's new trail association. "I think people who really aren't local will see this area as a wine destination."
Wine trails serve to put the message out about the wineries' use of locally sourced grapes and fruits, she said. Pennsylvania is the fourth-largest grape-producing state in the country, according to the Pennsylvania Wine Association.
"The more we can give them a reason to spend a day or a weekend, the better it is for everybody," said Jim Miller, owner of Moon Dancer Vineyards and Winery in Lower Windsor Township.
Because of its location at the southern end of Wine Country, Moon Dancer already attracts visitors from several neighboring states, including New York, Maryland and Virginia.
Joining Wine Country only enhances the draw and creates greater sales opportunity, Miller said.
Moon Dancer plays host to live music throughout the year. Miller has installed a wood-fired pizza oven to boost his offerings. He also is growing hops, with plans to start brewing his own line of beer this year.
"We've got the capacity in the facility to do that without changing our footprint," he said.
Beer is a natural progression for wineries, he said.
Outside draw
Wine Country's signature events are driving visitation spikes from outside a 60-mile radius, which is generating sales growth for supporting businesses such as Premiere #1 Limousine Service LLC in Londonderry Township.
In less than a year, there were 50 wine tours booked through Wine Country, Reimer said.
"This year, we'll easily double that," he said.
A standard tour is four wineries, said Jonathan Snavely, Premiere's business development manager.
"We've seen a 300 percent increase on tours," he said, also noting the company's collaboration with the nearby Mason-Dixon Wine Trail.
Last year, Premiere had 17 vehicles. It is up to 29 this year with the growth in retail traffic, he said, which also includes weddings and other private bookings. The limo company handled 445 weddings in 2012.
About 70 percent of the company's weekly trips are for corporate travel. That makes up about 51 percent of revenue, Snavely said.
That could be starting to shift. Premiere has run 15 wine tours already in 2013 and another 30 are on the schedule, he said, which translates to about 120 people.
About 80 percent of the alcohol-related tourism business is local and the majority of attendees are women, Snavely said.
"Our groups do buy a lot of wine," he said of the impact on the wineries.
Restaurant and hotel partners also are benefiting from the tour packages, which Snavely expects will triple from the first year.
The goal of Wine Country was not to drive overnight hotel stays, Reimer said. It was about driving retail traffic while creating opportunities for the bureau and other partners to sell packages that would extend leisure trips.
"It's absolutely doing that," he said
Wine Country by the numbers
15: The number of wineries participating in Hershey Harrisburg Wine Country. The wine trail started with 12 last year.
1: The Vineyard at Hershey, which led the charge in creating Wine Country, celebrated its first anniversary during the weekend.
12: The Vineyard at Hershey started with family volunteers. It has grown to a full-time, paid staff of 10 with two additional commissioned salespeople. And the vineyard is hiring as it grows and prepares to open a new building for production and entertaining.
60 percent: While 60 percent of The Vineyard at Hershey's business comes from tastings and direct wine sales, a growing percentage is tied to private events, sales to area restaurants and other private label distribution.
50: The number of Wine Country tours booked last year. Wine Country President Jason Reimer expects that number to double this year; Premiere #1 Limousine Service LLC is projecting it to triple.
2,000: Ticket sales generated by signature events in the spring and fall last year. Of those, 30 percent came from outside a 60-mile radius. Promotional efforts last year focused on the Baltimore and Washington, D.C., markets. The focus this year is on marketing Wine Country to the Philadelphia market.
75 percent: The recent ValenWine's Day event bolstered sales for participating wineries by an average of 75 percent over last year. There were 487 tickets sold that weekend, including 450 couples.
$600: The cost of the average wine tour package through Premiere #1 Limousine Service. Most group bookings have been for six to eight people.
32 percent: In 2011, 23 percent of Premiere customers said they heard of the company through referral or previous use. That percentage increased to 32 last year.
Added blends
The Vineyard at Hershey has seen steady interest in facility rentals for private events.
Corporate clients and restaurants seeking private label wines are a growing area, President Jason Reimer said.
Members 1st Federal Credit Union ordered several hundred cases of wine for client gifts, he said.
JoBoy's Brew Pub in Manheim ordered 100 cases of red and white wine to serve as its house options, Reimer said.
The Vineyard at Hershey is targeting additional business in those areas.


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NY Times: NSA Should Be Barred From Requiring Companies To Introduce Surveillance Backdoors
from the good-for-them deptThis is a bit surprising, given the source, but the NY Times editorial board has come out strongly against the NSA's practice of forcing companies to install backdoors in no uncertain terms:
These back doors and special access routes are a terrible idea, another example of the intelligence community's overreach. Companies and individuals are increasingly putting their most confidential data on cloud storage services, and need to rely on assurances their data will be secure. Knowing that encryption has been deliberately weakened will undermine confidence in these systems and interfere with commerce.In two short paragraphs, the editorial gets right to the heart of the problem. The "cost" to having these backdoors is undeniably huge in terms of trust and privacy. The harm to individuals and businesses is tremendous, but the benefits are, at best, minor. We get vague discussions about stopping some terrorist attacks, but still others get through. Yet, in every day life there are risks. It's ridiculous to expect 100% perfection in stopping terrorists, and when we go way too far in trying to stop every attack, we lead to unintended consequences such as destroying privacy and harming the ability of companies to build better, more secure products.
The back doors also strip away the expectations of privacy that individuals, businesses and governments have in ordinary communications. If back doors are built into systems by the N.S.A., who is to say that other countries' spy agencies — or hackers, pirates and terrorists — won't discover and exploit them?
Surprisingly, again, the NY Times then speaks out in support of a bill from Rep. Rush Holt that would make it illegal for the government to require backdoors in various products. This would be a huge step in enabling the US tech industry to move forward with more secure encryption.
Representative Rush Holt, Democrat of New Jersey, has introduced a bill that would, among other provisions, bar the government from requiring software makers to insert built-in ways to bypass encryption. It deserves full Congressional support. In the meantime, several Internet companies, including Google and Facebook, are building encryption systems that will be much more difficult for the N.S.A. to penetrate, forced to assure their customers that they are not a secret partner with the dark side of their own government.This is unlikely to happen, unfortunately. The DOJ, for years, has been pushing for even more backdoors. And, you may recall, just a month or so before the Snowden leaks, the DOJ wanted the power to fine companies who wouldn't install surveillance backdoors. The law enforcement world would go absolutely ballistic, should Holt's bill ever get near becoming law.
Filed Under: backdoors, nsa, nsa surveillance, rush holt, security, surveillance


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Water chestnut (Trapa natans) is an aquatic plant native to Asia. Introduced to North America near Concord, Massachusetts in 1859, water chestnut became established in locations throughout the northeast and by the early 20th
century was moving southward. It can be found from Maryland all the way north to Maine and in some parts of Canada. Read the Water Chestnut Eradication Report 1999-2012.
Check out a detailed view of the water chestnut. This aggressive species is a prolific reproducer. One acre of water chestnut can produce enough seeds to cover 100 acres the following year. With four, hard half-inch long spines that are sharp enough to penetrate shoe soles and large enough to keep people off beaches, these seeds are major hazards to water recreation. Additionally, water chestnuts can wipe out native bay grasses from some areas, create breeding grounds for mosquitoes, and provide poor habitat to native fish and birds. To help control its distribution, the sale of all species of water chestnut are banned from most of the Southern United States, including Maryland.
Water chestnut first appeared in Maryland in the Potomac River near Washington, D.C. as a two-acre patch in 1923. The plant spread rapidly, covering 40 river miles within a few years. By 1933, 10,000 acres of dense beds extended from Washington, D.C. to just south of Quantico, VA. This resulted in the loss of bay grasses, and the U.S. Army Corps of Engineers responded by conducting a massive removal effort from 1939 to 1945, with follow-up removal by hand until at least 1965. The cost was estimated at $2.8 million(converted from 1950 to 1992 dollars).
Water chestnut was recorded in the Bird River in Baltimore County for the first time in 1955. The Maryland Departments of Game and Inland Fish and Tidewater Fisheries used mechanical removal and an herbicide (2,4-D, the only fully-licensed herbicide that has been successfully used to control water chestnut) to control the population. However, in 1964 it reappeared in the Bird River and an additional 100 acres were discovered in the Sassafras River in Kent County. A combination of removal techniques were used once again in 1965, when 200 acres existed in the Sassafras. This effort was believed to have been successful, and no plants had been noted in vegetation surveys until summer 1997.
The Bird River water chestnut population spread from approximately 50 plants in summer 1997 to over three acres in 1998, and approximately 30 acres in 1999. A massive mechanical and volunteer harvesting effort began on both rivers in 1999, resulting in the removal of approximately 400,000 pounds of plants from the two rivers. In light of the potentially massive problems posed by water chestnut, the Maryland Department of Natural Resources (DNR) continued mechanical and hand removal efforts. Less than 1000 pounds of plants were discovered and removed from both rivers in 2000, indicating that the 1999 removal efforts were successful in reducing the total number of plants. In 2001, a large volunteer force was used instead of the mechanical harvesters, which was a significant milestone for the overall eradication effort.
In 2012, the water chestnut harvest on the Sassafras River decreased to 26 bushels, down from 50 bushels the year before. A majority of the plants were found in Dyer and Woodland Creeks. Lloyds and Turners Creek, which have been infested with water chestnut since the early 90's, have experienced a sharp decline. This year's harvest was cut short due to an algal bloom of the cyanobacteria, Mycrocystis aeruginosa, which occurs annually in the river. Across the Bay, 12 bushels were removed from the Bird River, mostly from the small cove adjacent to Railroad Creek and the creeks near Days Cove. Personal watercraft and canoes were used to effectively remove the water chestnut there. With the help of volunteers, DNR has managed to control water chestnut on the Bird and Sassafras Rivers for the last several years without the need for chemical control.
Water chestnut seeds can remain viable in sediments for up to 12 years, requiring follow-up surveys each year. DNR will continue its annual survey to ensure the Bird and Sassafras remain free of this floating invasive species. If you have observed water chestnut in these or any other rivers in Maryland, please contact Mark Lewandowski at 410-260-8634 or email firstname.lastname@example.com
580 Taylor Ave, Annapolis MD 21401