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Message/Author
 aguri posted on Monday, November 19, 2012 - 10:04 pm
Dear Dr. Muthen
I am using MPLUS 3.11 to run a Latent Class Analysis.
The database are from TIMSS 2007 about student attitudes to math, 12 items(Likert 4-point) and about 4000 test takers included.I try to make exploratary LCA to find how many classes would be approriate, two questions are bumped into:
1. the p-value of Likelihood Ratio Chi-Square from c(1) to c(3) are 1, when c(4), something showed up...
THE MODEL ESTIMATION DID NOT TERMINATE NORMALLY DUE TO A NON-POSITIVE DEFINITE FISHER INFORMATION MATRIX. CHANGE YOUR MODEL AND/OR STARTING VALUES.
.......

so I try to recode the data from 4-point to 2 categories (positive and negative orientation),and the result showed 5 classes is much better. I am not sure what happened when 4-point situations, and could I deal with the problem as description !!??(Do you recommend to change estimates method or setting starting value!?)
2. If I want to know which class level each test taker belongs to, what can I do !!??
THANKS A LOT :-)

my code as reference ~
TITLE: LCA
DATA: FILE IS test1115.dat;
VARIABLE: NAMES ARE gender i1-i12 ;
USEVARIABLES ARE i1-i12;
CLASSES = c (3);
CATEGORICAL = i1-i12;
ANALYSIS: TYPE = MIXTURE;
OUTPUT: TECH1 TECH7;
 Linda K. Muthen posted on Tuesday, November 20, 2012 - 12:00 pm
The two chi-square statistics given for the frequency tables of the categorical variables are not useful when you have more than about 8 variables. You should ignore these.

You should not recode your data. You should use more starts, for example, 1000 250.
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