A latent variable model with mixed binary and continuous response variables
Methodology
2015-07-07 v1
Abstract
We propose a method for obtaining maximum likelihood estimates in a model with continuous and binary outcomes. Combinations of left and right censored observations are also naturally modeled in this framework. The model and estimation procedure has been implemented in the R package lava.tobit. The method is demonstrated on brain imaging and personality data where measurement error on predictor variables is handled in a latent variable framework. A simulation study is conducted comparing the small sample properties of the MLE with a limited information estimator.
Cite
@article{arxiv.1507.01182,
title = {A latent variable model with mixed binary and continuous response variables},
author = {Klaus K. Holst and Esben Budtz-Jørgensen and Gitte Moos Knudsen},
journal= {arXiv preprint arXiv:1507.01182},
year = {2015}
}