Multilevel sem, modification, and cat...
Message/Author
 phdstudent posted on Tuesday, February 03, 2009 - 11:17 am
I'm looking at relationship between a latent predictor var ( w/ 2 binary indicator vars, x1 x2) and an observed y var (binary). I want to examine whether the latent predictor at clus level modifies relationship at indiv level. For each clus, I calc mean values for the 2 indicators of the latent predictor var (representing % indiv in clus for whom x1=1, eg). These vars, cx1 cx2 are considered continuous. (1) Is my code correct? (2) This model takes too long to estimate. Is there a way to shorten time? When I got output I received this message. What does it mean? "THE ESTIMATED BETWEEN COVARIANCE MATRIX COULD NOT BE INVERTED. COMPUTATION COULD NOT BE COMPLETED IN ITERATION 81. CHANGE YOUR MODEL AND/OR STARTING VALUES.THE MODEL ESTIMATION DID NOT TERMINATE NORMALLY DUE TO AN ERROR IN THE COMPUTATION. CHANGE YOUR MODEL AND/OR STARTING VALUES."
(3) how do I add my indiv-level categ covars to this model?

VARIABLE:
NAMES ARE clus y x1 x2 cx1 cx2;
CATEGORICAL = y x1 x2;
BETWEEN = cx1 cx2;
CLUSTER = clus;
MISSING ARE ALL (-9999) ;
ANALYSIS:
TYPE = TWOLEVEL RANDOM;
ALGORITHM = INTEGRATION;
INTEGRATION = 7;
MODEL:
%WITHIN%
fw by x1 x2;
s | y ON fw;
%BETWEEN%
fb BY x1 x2;
x1@0 x2@0;
w by cx1 cx2;
y s ON fb w;
OUTPUT:
TECH1 TECH8;
 Bengt O. Muthen posted on Tuesday, February 03, 2009 - 12:04 pm
You have not declared x1, x2 as Within= variables which implies that they have Between variation, that is random intercepts. So when you say on Between

fb by x1 x2;

you are talking about a factor for these 2 random intercepts. So your factor w is approx the same as fb - you only need one of them. Delete your w by... statement. So fb moderates the influence of fw on y.
 shahadut hossain posted on Friday, February 06, 2009 - 11:59 am
Hi:

I am going to design a study which will be a two-level SEM. My question is how many cluster do I need and what should be the size of each cluster. I have two latent variable indogenous variables (one with two indicator another with 3 indicators), 5 exgoneous (continuous)variables. Could you please guide me how to perform a monte-carlo analysis to have an idea to determine the number of clusters and the cluster size. I have 16 clusters in total.

Thanks
 Linda K. Muthen posted on Friday, February 06, 2009 - 4:09 pm
You should look at mcex9.6.inp which is a multilevel CFA. Usually a minimum of 30-50 clusters is recommended with multilevel modeling. See papers by Joop Hox for further information.