# Latent Class Analysis with poLCA

**is.R()**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

On an airplane the other day, I learned of a method called latent class (transition) analysis, and it sounded like an interesting thing to try in R. Of course, as with everything R, There is a Package for That, called poLCA, written by none other than Drew Linzer (of Votamatic fame) and Jeffrey Lewis.

I wasn’t able to think of a good application for transition analysis specifically, but I did use Christopher’s ANES data to estimate latent “types” of respondents. The example model illustrates a four-class model, and I’ll leave it as an exercise for the interested reader to assign subjective names to each class.

This Gist also attempts to improve on the default plot both by eschewing the 3-D effect, and by putting classes, rather than variables, in direct comparison with one another. Also, for what it’s worth, the plot code shows how to draw a bar plot when you have already computed counts or proportions — use stat=”identity”.

Thanks for celebrating Advent with us, and for your feedback and support. We’re taking a little break after tomorrow’s post, but we’ll be back better than ever next year!

**leave a comment**for the author, please follow the link and comment on their blog:

**is.R()**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.