Package: My.stepwise
Type: Package
Title: Stepwise Variable Selection Procedures for Regression Analysis
Version: 0.1.0
Author: International-Harvard Statistical Consulting Company <nhsc2010@hotmail.com>
Maintainer: Fu-Chang Hu <fuchang.hu@gmail.com>
Description: The stepwise variable selection procedure (with iterations
 between the 'forward' and 'backward' steps) can be used to obtain
 the best candidate final regression model in regression analysis.
 All the relevant covariates are put on the 'variable list' to be
 selected. The significance levels for entry (SLE) and for stay
 (SLS) are usually set to 0.15 (or larger) for being conservative.
 Then, with the aid of substantive knowledge, the best candidate
 final regression model is identified manually by dropping the
 covariates with p value > 0.05 one at a time until all regression
 coefficients are significantly different from 0 at the chosen alpha
 level of 0.05.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: True
Depends: R (>= 3.3.3)
Imports: car, lmtest, survival, stats
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-06-29 07:43:02 UTC; Jane
Repository: CRAN
Date/Publication: 2017-06-29 09:13:47 UTC
Built: R 4.6.0; ; 2026-04-25 14:05:04 UTC; unix
