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!
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"
Binary- 0/1 (no/yes)
So it is weighted nominal categorical variables.
Okay.
Please explain weighted nominal categorical variables.
Registration is now open for SAS Innovate 2025 , our biggest and most exciting global event of the year! Join us in Orlando, FL, May 6-9.
Sign up by Dec. 31 to get the 2024 rate of just $495.
Register now!
ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.
Find more tutorials on the SAS Users YouTube channel.