Asymptotics of forced-in variables from screening processes

研究成果: Article

1 引文 (Scopus)

摘要

Freedman, Navidi and Peters (1988) had shown that when a two-stage variable selection procedure is used to screen linear regression equations, the type I error rate of the t-test for a forced-in-first estimator is inflated if the ratio of the number of parameters to number of data points is large. In this paper, we investigate the asymptotic distribution of the “force-in-last” estimator, and show that this estimator is bias toward zero asymptotically and its asymptotic standard error is close to the nominal standard error under certain conditions. To remedy the bias and reduce the inflation of the type I error rate, two estimators involved with propensity score (Rubin and Rosenbaum, 1983) were introduced.

原文English
頁(從 - 到)131-151
頁數21
期刊Communications in Statistics - Theory and Methods
24
發行號1
DOIs
出版狀態Published - 1995 一月 1

指紋

Screening
Estimator
Type I Error Rate
Standard error
Propensity Score
t-test
Selection Procedures
Variable Selection
Linear regression
Inflation
Asymptotic distribution
Categorical or nominal
Zero

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

引用此文

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