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chest
View on CRAN: Click
here
Download and install chest package within the R console
Install from CRAN:
install.packages("chest")
Install from Github:
library("remotes")
install_github("cran/chest") Install by package version:
library("remotes")
install_version("chest", "0.3.7") Attach the package and use:
library("chest")
Maintained by
Zhiqiang Wang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-12-16
Latest Update: 2023-03-23
Description:
Applies the change-in-effect estimate method to assess confounding
effects in medical and epidemiological research (Greenland & Pearce (2016)
). 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
How to cite:
Zhiqiang Wang (2019). chest: Change-in-Estimate Approach to Assess Confounding Effects. R package version 0.3.7, https://cran.r-project.org/web/packages/chest. Accessed 05 Jun. 2026.
Previous versions and publish date:
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Complete documentation for chest
Functions, R codes and Examples using
the chest R package
Some associated functions: chest . chest_clogit . chest_cox . chest_forest . chest_glm . chest_lm . chest_nb . chest_plot . diab_df .
Some associated R codes: chest.R . chest_clogit.R . chest_cox.R . chest_forest.R . chest_glm.R . chest_lm.R . chest_nb.R . chest_plot.R . data_diab_df.R . Full chest package functions and examples
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