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ps53
Calcite | Level 5

Greetings! 

 

I am looking for a data reduction method for binary weighted variables. I did a factor analysis on a tetrachoric matrix, but it does not account for weights. It seems like Latent Class Analysis might be useful, but again, I don't know how to incorporate the weights, and I don't want to establish a number of factors a priori, rather look at the data (like a scree plot in FA) to decide how to split the variables into factors/ latent variables. 

 

Specifics: I have 8 (yes/no) outcomes I want to create logistic models for. Rather than making 8 models, I think there should be a natural trend among some of the variables so I am hoping to reduce to a few factors/ latent vars to model. Thanks!

4 REPLIES 4
PaigeMiller
Diamond | Level 26

A search on that search engine rhyming with "Schmoogle" produces only one hit for "binary weighted variables", and I can't access that web page. So please tell us what you mean by "binary weighted variables"

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Paige Miller
ps53
Calcite | Level 5

Binary- 0/1 (no/yes)

So it is weighted nominal categorical variables.

PaigeMiller
Diamond | Level 26

Okay.

 

Please explain weighted nominal categorical variables.

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Paige Miller
ps53
Calcite | Level 5
Weighted- the data are weighted
Nominal- not ordinal
Categorical- not continuous

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