Second Order LCA for different behaviors PreviousNext
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 Samuel Johnson posted on Tuesday, December 09, 2014 - 4:22 pm
Can I conduct a second order LCA on two sets of related but not identical sets behaviors?

For example, risk behaviors and academic behaviors. I would expect them to be related to one another but not the same underlying construct.

Membership in each of the 2 first-order classes would be based on three binary indicators. For example, patterns of academic behaviors (c1) measured by 3 observed binary variables u11, u12, u13. Patterns of risk behaviors (c2) measured by and three observed binary variables u21, u22, u23.

Could I do a second order LCA to determine classes (f) of joint patterns of academic behaviors and risk behaviors?

Thanks,
Samuel
 Bengt O. Muthen posted on Tuesday, December 09, 2014 - 6:02 pm
Yes, this can be done. You have an example of a second-order LCA (actually a more complex LTA) in UG ex8.15. You have say 2 1st-order latent class variables c1 and c2 and a 2nd-order latent class variable c. You relate them by saying

c1 c2 on c;

And you use the construction

Model c1:
....
Model c2:
...
 Alvin  posted on Friday, June 05, 2015 - 3:59 pm
Hi Dr Muthen, I am looking at the dyadic profiles of characteristics of husbands and wives (having run two independent LCAs for each group and achieved a two and a three-class solution for husbands, and I am looking at a joint LCA). In testing a second-order LCA, I understand that class invariance will have to be established across the two groups (as in multigroup LCA)? Would it matter if one has two different class solutions in this case? Next, I'll look at predictors of joint-class memberships..
 Bengt O. Muthen posted on Friday, June 05, 2015 - 4:03 pm
Perhaps you are saying that some classes are the same and some different across husbands and wifes? If so, you can hold measurement parameters equal for the same classes.
 Alvin  posted on Friday, June 05, 2015 - 4:17 pm
yes that's what I meant - many thanks!
 Alvin  posted on Monday, June 22, 2015 - 12:06 am
Hi Dr Muthen, I am running a second order LCA based on a dyadic dataset (in wide format), looking at joint profiles or distributions amongst husbands and wives living in the same household. Would I have to transform the data from wide to long (with a variable identifying the dyad, husband/wife) and set it up using class-specific commands for the analysis? Or would it be possible to analyze the data in wide format? Many thanks
 Linda K. Muthen posted on Monday, June 22, 2015 - 6:10 am
You can analyze it in wide format. The non-independence of observations is handled by multivariate modeling. This is discussed in both the Topic 7 and Topic 8 course handouts and videos on the website.
 SRL posted on Friday, February 16, 2018 - 1:31 pm
Hi, I am interested in a higher-order latent class variable indicated by two first-order latent class variables. I have specified an LTA relating the two latent class variables to each other and a higher order LCA with one class. When looking at the results of the two different models, I get different loglikelihoods and slightly different proportions across the joint distribution of the two latent class variables, when I expected them to be the same. Any insight into why they may be different?
 Bengt O. Muthen posted on Friday, February 16, 2018 - 6:07 pm
I assume the LTA model is c1 -> c2. But that is the model that has "a higher order LCA with one class"? A latent class variable with one class is not a variable.
 SRL posted on Tuesday, February 20, 2018 - 3:13 pm
To clarify, I specified two different models. I have c2 on c1 for the LTA model. For the higher order LCA,I specified classes "c(1) c2(2) c3(4); and compared the joint distribution of the two latent class variables for the LTA model and higher-order. They were slightly different (see below) and Im trying to make sense of this difference and if its meaningful. I cannot get the higher order latent class variable with more than one class to converge.
 SRL posted on Tuesday, February 20, 2018 - 3:14 pm
FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS
BASED ON THE ESTIMATED MODEL

Latent Class
Pattern

1 1 1 216.34917 0.06799
1 1 2 407.09808 0.12794
1 1 3 1607.95824 0.50533
1 1 4 317.52216 0.09979
1 2 1 53.73423 0.01689
1 2 2 101.11018 0.03178
1 2 3 399.36556 0.12551
1 2 4 78.86238 0.02478



FINAL CLASS COUNTS AND PROPORTIONS FOR THE LATENT CLASS PATTERNS

BASED ON THE ESTIMATED MODEL



Latent Class

Pattern



1 1 136.76939 0.04298

1 2 349.36717 0.10979

1 3 1722.88154 0.54145

1 4 339.90955 0.10682

2 1 133.31656 0.04190

2 2 158.83728 0.04992

2 3 284.44515 0.08939

2 4 56.47337 0.01775
 Bengt O. Muthen posted on Tuesday, February 20, 2018 - 3:32 pm
Send the output for the 2 models to Support along with your license number.
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