chest: Change-in-Estimate Approach to Assess Confounding Effects

Applies the change-in-effect estimate method to assess confounding effects in medical and epidemiological research (Greenland & Pearce (2016) <doi:10.1146/annurev-publhealth-031914-122559> ). It starts with a crude model including only the outcome and exposure variables. At each of the subsequent steps, one variable which creates the largest change among the remaining variables is selected. This process is repeated until all variables have been entered into the model (Wang Z. Stata Journal 2007; 7, Number 2, pp. 183–196). Currently, the 'chest' package has functions for linear regression, logistic regression, negative binomial regression, Cox proportional hazards model and conditional logistic regression.

Version: 0.3.7
Depends: R (≥ 2.20)
Imports: broom, ggplot2, survival, grid, forestplot, MASS, tibble, dplyr
Suggests: spelling, knitr, rmarkdown
Published: 2023-03-23
DOI: 10.32614/CRAN.package.chest
Author: Zhiqiang Wang [aut, cre]
Maintainer: Zhiqiang Wang <menzies.uq at>
License: GPL-2
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: chest results


Reference manual: chest.pdf
Vignettes: chest-vignette


Package source: chest_0.3.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): chest_0.3.7.tgz, r-oldrel (arm64): chest_0.3.7.tgz, r-release (x86_64): chest_0.3.7.tgz, r-oldrel (x86_64): chest_0.3.7.tgz
Old sources: chest archive


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