Latent Variable Module
Latent variable models have been popularized at Hopkins by
Dr Karen Bandeen-Roche, Associate Professor in the Departement of
Biostatistics. She has made substantial contributions in this area and
has provoked students' interest. Numerous latent variable programs have
been written by several different authors,
many of whom were/are Dr Bandeen-Roche's students.
Originally, Dr Bandeen-Roche wrote
Gauss programs to perform latent class analysis and Diana
Miglioretti wrote SAS programs to perform latent class regression.
These programs have since been translated into Splus and now include
some error checking procedures. Both Liz Garrett and
Qian-li Xue have written Splus programs to perform latent class
analysis and regression.
Dr Bill Rising and Brent Johnson have since took some of the current
improved on the computing efficiency and added some error checking
procedures to create a so-called "user-friendly" LCA function.
Currently, we are
aiming to create a single latent variable class to handle
a wide variety of data, models, and problems.
Latent Class Analysis
These functions perform standard (unrestricted)
latent class analysis on
binary data. They
take an N x M matrix of 0/1 responses and a hypothesized
number of classes, J, as arguments
and return a vector of prevalences for each of the
J classes and an M x J matrix of posterior probabilities.
Splus programs (for UNIX)
You must unzip (gzip -d filename.gz) and
untar (tar xvf filename.tar) this file.
Splus programs (for UNIX or PC)
Download all four files:
Latent Class Regression