topic Re: Data Reduction Method for Binary Weighted Variables in Statistical Procedures

Data Reduction Method for Nominal Categorical Weighted Variables

ps53 — Fri, 04 Oct 2019 05:21:07 GMT

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!

Re: Data Reduction Method for Binary Weighted Variables

PaigeMiller — Thu, 03 Oct 2019 21:23:44 GMT

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"

Re: Data Reduction Method for Binary Weighted Variables

ps53 — Fri, 04 Oct 2019 05:20:19 GMT

Binary- 0/1 (no/yes)

So it is weighted nominal categorical variables.

Re: Data Reduction Method for Binary Weighted Variables

PaigeMiller — Fri, 04 Oct 2019 10:39:19 GMT

Okay.

Please explain weighted nominal categorical variables.

Re: Data Reduction Method for Nominal Categorical Weighted Variables

ps53 — Mon, 07 Oct 2019 06:42:20 GMT

Weighted- the data are weighted
Nominal- not ordinal
Categorical- not continuous