This R package was developed by the Methodology Center to allow R users to perform latent class causal analysis (LCCA), latent class analysis (LCA), and LCA with covariates. LCA describes relationships among a set of categorical variables by assuming that they are conditionally independent given an unobserved categorical variable. The lcca.r package uses imputing estimating equations to estimate the average causal effects of a latent exposure (i.e., latent class) on a normally-distributed outcome variable. LCCA combines aspects of latent class analysis with Rubin’s causal model (Rubin, 1974; 2005).
The LCCA package includes 3 primary functions:
- lca: Fit a conventional LCA model
- lcacov: Fit an LCA model with covariates
- lcca: Fit an LCCA model
Schafer, J. L., & Kang, J. (2013). LCCA package for R users’ guide (Version 1.1.0). University Park: The Methodology Center, Penn State.
- Download the zip file from this webpage.
- Launch R.
- In R, under the “Packages” menu, select “Install pacakge(s) from local Zip files…”
- Select the downloaded zip file.
- If installation is succesful, the R Console will display the message “package ‘lcca’ successfully unpacked and MD5 sums checked.”
X = vector of measured confounders
C = latent class variable
Y(C) = vector of potential distal outcomes
U1…Uj = observed items from the data set
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