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

The 'chest' package applies the change-in-effect estimate method for assessing confounding effects in medical and epidemiological research. 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 (2007) <doi:10.1177/1536867X0700700203>). Currently, the 'chest' package has functions for linear regression, logistic regression, Cox proportional hazards model and conditional logistic regression.

Version: 0.2.0
Depends: R (≥ 2.10)
Imports: tidyverse, survival, grid, speedglm, forestplot, broom, tibble, MASS, scales, tidyselect
Suggests: spelling, knitr, rmarkdown
Published: 2019-12-16
Author: Zhiqiang Wang [aut, cre]
Maintainer: Zhiqiang Wang <zhiqiang.wang at menzies.edu.au>
License: GPL-2
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: chest results

Downloads:

Reference manual: chest.pdf
Vignettes: chest-vignette
Package source: chest_0.2.0.tar.gz
Windows binaries: r-devel: chest_0.2.0.zip, r-devel-gcc8: chest_0.2.0.zip, r-release: chest_0.2.0.zip, r-oldrel: chest_0.2.0.zip
OS X binaries: r-release: chest_0.2.0.tgz, r-oldrel: chest_0.2.0.tgz

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