I am running an LGM with the analysis command, type = meanstructure missing h1; You once mentioned it is possible to set the program so that all available data applies to the dependent variables only instead of all variables. Now, my sample size is based on all data, including covariates. I'd like to restrict it to the dependent measure only. How do I do this?
Hi, I'm from Quebec, so sorry for my accent!! I'm trying to use MPlus, It's new for me. I'm doing growth modelin on a variable censored from de bottom at three times non-regular. What i want is the intercept and the slope for everybody. I did it with SPSS ans SAS and I got a intercept arround 12 and a positive slope, that it's normal, in know my data and It's for sure positive across time.
The problem is that I want to work with MPlus but with this input i got a negative slope??
variable: names are sexe age1-age3 y1-y3 a1-a3; usevariables are age1-age3 y1-y3; tscores = age1-age3; censored are y1-y3 (b);
If you have done type = basic to check that your descriptive statistics are correct (variables are in the right columns in the data matrix), then please send your input, output, data and license number to firstname.lastname@example.org.
I found the problem... I did not know that when I put type = missing, I have to tell what is the missing (missing=.) Now it's working well!! But, I have another question about plot. I made the plot of individual growth and I can see 10 individuals at a time. How a can plot the regression that MPlus give in the output. And, is it possible to have a plot for the two regression, one for each gender? I whant to see at the same time the model for female and the model for male in a graph.
Hi, thank you for your time. With the type = plot3, I can see just 3 choices... Histogram Scatterplot Observed individual values And in none of these, I see a menu options.
Djangou C posted on Sunday, February 28, 2016 - 4:37 pm
Hi, I am running an LGM to assess the effect of an intervention at each time point. Given that the groups are different at baseline, I want to control for this difference in the analysis. Below is the code used. I am not sure if this strategy is reasonable as baseline variable is used as an outcome (to construct the LGM) as well as a control variable. Could you please give your thoughts on this? Thank you.
You should not have S1B as a measure of i and st the same time influencing i. Instead, let i be defined at the first time point by using time score 0 and regress s on i and intervention. This means that i is the control variable where i is an error-free version of S1B.
Djangou C posted on Sunday, February 28, 2016 - 5:46 pm