I am running a LCGA on a continuous variable assessed at 7 consecutive time points. I have a few questions left after consulting the MPlus manual.
- I have included only those participants who have filled out the assessments at time point 1 and at least one other time point. Is that sufficient, or should participants have filled out more than 2 measurement points?
- The continuous variable that I use is left skewed with an abundance of scores equal to 0. Therefore I have tried to run a LCGA with a censored distribution. However, entropy values are quite less optimal with a censored model than with a "normal" model. For example: entropy in 3-class "normal" model = 0,834; entropy in 3-class censored model = 0,783. Should I consider using a non-censored model despite the fact that the continuous variable I use is left skewed?
- In the Mplus syntax, do I have to state somewhere that my variable is a continuous variable? Right now, in the non-censored model I state nothing about the measurement level of my variable and in the censored model I only state "censored=eds1-7(b)". I can find commands in the manual for categorical variables, count variables etc but not for continuous variables.
I have one additional question: through the syntax TECH7 I can request the statistics for each class. I am interested in the Mean scores for each time point in each of the classes, which indeed are given. But is there also a possibility to request accompanying standard deviations and confidence interval's for each of these time points, for each class?
I am now deciding the optimal number of classes. I consulted BIC, LMR-LRT, and BLRT.
The BLRT is significant at the p<.001 level for all models I run (1-7 class models). The LMR-LRT p-value is .47 for the 4 versus 3 class model, but after that again becomes significant for the 5 versus 4 class model: p=.004. Does this mean that I could also explore the possibility of using the 5-class model, or should I already have stopped after I found that the 4-class model (compared to the 3-class model) was not significant based on the LMR-LRT value? (and should I as such stick with the 3-class model?)
I have another question about using a left skewed continuous dependent variable in GMM. The variable I use is obviously skewed to the left, but opposed to the variable that I was talking about above (post: posted on Wednesday, February 22, 2017 - 4:38 am), there is not an abundance of scores equal to 0. For the currenct variable, the values range from 0-26 with a median, mode, and interquartile range of 5 (which also indicates the skewness).
For this variable, would it also be appropriate to use CENSORED = x1-x3(b) to indicate that the scores are censored with a floor effect, even though for this variable there maybe isn't a "true" floor effect as there is not an abundance of scores equal to zero?