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                                       Details for article 2 of 20 found articles
 
 
  Asymptotics of forced-in variables from screening processes
 
 
Title: Asymptotics of forced-in variables from screening processes
Author: Lian, Ie-bin
Appeared in: Communications in statistics
Paging: Volume 24 (1995) nr. 1 pages 131-151
Year: 1995
Contents: 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.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 2 of 20 found articles
 
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