期刊
ANNALS OF APPLIED STATISTICS
卷 2, 期 1, 页码 176-196出版社
INST MATHEMATICAL STATISTICS
DOI: 10.1214/07-AOAS143
关键词
Models; randomization; experiments; multiple regression; estimation; bias; balanced designs; intention-to-treat
Regression adjustments are often made to experimental data. Since randomization does not justify the models, bias is likely; nor are the usual variance calculations to be trusted. Here, we evaluate regression adjustments using Neyman's nonparametric model. Previous results are generalized, and more intuitive proofs are given. A bias term is isolated. and conditions are given for unbiased estimation in finite samples.
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