My.stepwise
0.1.0Stepwise Variable Selection Procedures for Regression Analysis
Overview
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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-06-0911 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0811 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-109 OK · 5 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
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- Documented parameters
- 100%
- Return-value docs
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- References docs
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1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2017-06-29
- Total releases
- 1 / 9 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.3.3
- Download size
- 6.2 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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