Statistical Science

Randomization Does Not Justify Logistic Regression

David A. Freedman

Full-text: Open access

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.

Article information

Source
Statist. Sci. Volume 23, Number 2 (2008), 237-249.

Dates
First available in Project Euclid: 21 August 2008

Permanent link to this document
http://projecteuclid.org/euclid.ss/1219339115

Digital Object Identifier
doi:10.1214/08-STS262

Mathematical Reviews number (MathSciNet)
MR2516822

Citation

Freedman, David A. Randomization Does Not Justify Logistic Regression. Statistical Science 23 (2008), no. 2, 237--249. doi:10.1214/08-STS262. http://projecteuclid.org/euclid.ss/1219339115.


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