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My.stepwise
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Download and install My.stepwise package within the R console
Install from CRAN:
install.packages("My.stepwise")
Install from Github:
library("remotes")
install_github("cran/My.stepwise") Install by package version:
library("remotes")
install_version("My.stepwise", "0.1.0") Attach the package and use:
library("My.stepwise")
Maintained by
Fu-Chang Hu
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[Scholar Profile | Author Map]
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First Published: 2017-06-29
Latest Update: 2017-06-29
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.
How to cite:
Fu-Chang Hu (2017). My.stepwise: Stepwise Variable Selection Procedures for Regression Analysis. R package version 0.1.0, https://cran.r-project.org/web/packages/My.stepwise. Accessed 25 Aug. 2026.
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Complete documentation for My.stepwise
Functions, R codes and Examples using
the My.stepwise R package
Some associated functions: My.stepwise.coxph . My.stepwise.glm . My.stepwise.lm .
Some associated R codes: Full My.stepwise package functions and examples
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