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arXiv · 1805.08670

Regression Analysis of Proportion Outcomes with Random Effects

Colman Humphrey·Dan Swingley
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Abstract

A regression method for proportional, or fractional, data with mixed effects is outlined, designed for analysis of datasets in which the outcomes have substantial weight at the bounds. In such cases a normal approximation is particularly unsuitable as it can result in incorrect inference. To resolve this problem, we employ a logistic regression model and then apply a bootstrap method to correct conservative confidence intervals. This paper outlines the theory of the method, and demonstrates its utility using simulated data. Working code for the R platform is provided through the package glmmboot, available on CRAN.

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Colman Humphrey, Dan Swingley. 2018-05-22. Regression Analysis of Proportion Outcomes with Random Effects. https://arxiv.org/abs/1805.08670

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