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 John Sandberg posted on Wednesday, May 03, 2006 - 12:13 pm
Hi; I have a couple of quick questions concerning single indicators in LCA. The reason I want a single indicator is I'm testing multiple variable models, in some the indicator is specified on a variable with others, in some it's by itself (unfortunately, it would be nice to have more indicators).

In covariance structure models, there are a number of ways to include a single-indicator latent variable. One of these is to fix the factor loading to one and error variance at 0, the other is to fix the residual variance to account for reliability.

If I'm correct, the analogue to the first solution to this in LCA in MPLUS is to fix the logit at some high value (say 15) for one class, thus producing a probability on one class of 1. The first question I have is, can I just enter the indicator into the model in this case as I would in SEM and produce the same result as if I created a 2 class latent variable w/the constraint?

My second question is how to produce an anlogue to the second solution, fixing the probability (in this case the logit) to some lower threshold to account for imperfect measurement, making some assumption about how imperfect. Is this a valid technique?

That's it,

Best,
Jack

Best
 Bengt O. Muthen posted on Thursday, May 04, 2006 - 11:23 am
You can accomplish this by having a latent class variable take the role of an error-free counterpart to the categorical outcome. This is discussed in our handout for "Day 4" of our 5-day course.
- See pages 10 and 11.
 claudia cs  posted on Friday, August 23, 2019 - 5:01 pm
Good evening,

Is it possible to run an SEM using six single indicator latent variables (all variables were answered on a dichotomous yes/no response, e.g. have you been bullied on school property the past 12 months)? Theoretically I could create 3 factors with 2 indicators each using the "by" command, however, the estimate for one of those indicators is - albeit significant - below 0.5. Would it be more advisable to create 3 factors using 2 indicators each or could I still run the SEM using the six (dichotomous) single indicator variables?

Thank you very much!
 Bengt O. Muthen posted on Saturday, August 24, 2019 - 6:23 am
There is no benefit to using a single-indicator factor for dichotomous observed variables. A significant loading of 0.5 is fine. However, 2 indicators per factor is not a strong measurement model. What you should do in your particular case depends on your substantive theory.
 claudia cs  posted on Monday, August 26, 2019 - 9:13 pm
Thank you for your response! Does this mean any dichotomous variable can be treated as an observed variable?
 Bengt O. Muthen posted on Wednesday, August 28, 2019 - 3:29 pm
Right.
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