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Hi,
I´m trying to find out which of 3 alternative (observed) classes best fit different individual level outcomes summarized in a single latent variable ("life chances"). I thought a LCA would do the job, however im struggling with 2 questions:
1. What´s the best way to include the restriction in a LCA for latent classes to be defined by observed classes? Is Example 7.21 the right model specification?
2. After estimating 3 different models for 3 different observed classes, how can I decide which model best fits the data given that the alternative classes are NOT nested? (all I´ve read about this issue refers to models comparing different nested classes).
I´d appreciate your expert advice on this matter. I´m sure the answer is not very complicated, but i couldn´t find it out by my own means. Thank you. |
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1. If you mean observed classes like gender, the KNOWNCLASS option should be used as shown in Example 7.21.
2. People use BIC to compare non-nested classes. |
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| Thanks for your answer. With observed classes I mean occupational grouppings(i.e. "manual workers" or "managers"), which are not individuals traits but "level 2" variables. I´d like to restrict the LCA to fit this groups. |
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Put the categorical latent variable on the between list:
VARIABLE:
CATEGORICAL is occup;
CLASSES = cb (2);
BETWEEN = cb;
MODEL:
....
%BETWEEN%
%OVERALL%
%cb#1%
[occup$1@15]; !occup = 0
%cb#2%
[occup$1@-15]; !occup = 1 |
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| Thanks again for your reply. I´ll try it that way. |
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