Discrete Exponential-Family Models for Multivariate Binary Outcomes
arXiv ยท 2022
Studies that collect multi-outcome data such as tobacco and alcohol use are becoming increasingly common.
Work in progress2022
Abstract
Studies that collect multi-outcome data such as tobacco and alcohol use are becoming increasingly common. In principle, multi-outcomes studies investigate the correlations between outcomes, including, causal links and/or joint distributions. Although there are many methods for studying multivariate outcomes, significant limitations regarding scale and interpretation persist. Here we introduce a model based on the exponential-family for discrete binary outcomes that provides a flexible framework for hypothesis testing of multiple binary outcomes in a computationally efficient fashion.
Cite
@misc{vegayonDiscreteExponentialFamilyModels2022,
title = {Discrete Exponential-Family Models for Multivariate Binary Outcomes},
author = {{Vega Yon}, {George G.} and {Pugh}, {Mary Jo} and {Valente}, {Thomas W.}},
year = {2022},
month = {11},
publisher = {arXiv},
number = {arXiv:2211.00627},
doi = {10.48550/arXiv.2211.00627},
url = {https://arxiv.org/abs/2211.00627},
}