Randomization Does Not Justify Logistic Regression
Methodology
2008-08-29 v1
Abstract
The logit model is often used to analyze experimental data. However, randomization does not justify the model, so the usual estimators can be inconsistent. A consistent estimator is proposed. Neyman's non-parametric setup is used as a benchmark. In this setup, each subject has two potential responses, one if treated and the other if untreated; only one of the two responses can be observed. Beside the mathematics, there are simulation results, a brief review of the literature, and some recommendations for practice.
Cite
@article{arxiv.0808.3914,
title = {Randomization Does Not Justify Logistic Regression},
author = {David A. Freedman},
journal= {arXiv preprint arXiv:0808.3914},
year = {2008}
}
Comments
Published in at http://dx.doi.org/10.1214/08-STS262 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)