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tipr
View on CRAN: Click
here
Download and install tipr package within the R console
Install from CRAN:
install.packages("tipr")
Install from Github:
library("remotes")
install_github("cran/tipr")
Install by package version:
library("remotes")
install_version("tipr", "1.0.2")
Attach the package and use:
library("tipr")
Maintained by
Lucy D'Agostino McGowan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.tipr . https://github.com/r-causal/tipr/issues . https://r-causal.github.io/tipr/ . https://github.com/r-causal/tipr . tipr citation info . tipr results . tipr.pdf . tipr_1.0.2.tar.gz . tipr_1.0.2.zip . tipr_1.0.2.zip . tipr_1.0.2.zip . tipr_1.0.2.tgz . tipr_1.0.2.tgz . tipr_1.0.2.tgz . tipr_1.0.2.tgz . tipr_1.0.2.tgz . tipr_1.0.2.tgz . tipr archive . https://CRAN.R-project.org/package=tipr .
First Published: 2017-11-28
Latest Update: 2022-09-05
Description:
The strength of evidence provided by epidemiological and observational studies is inherently limited by the potential for unmeasured confounding.We focus on three key quantities: the observed bound of the confidence interval closest to the null, the relationship between an unmeasured confounder and the outcome, for example a plausible residual effect size for an unmeasured continuous or binary confounder, and the relationship between an unmeasured confounder and the exposure, for example a realistic mean difference or prevalence difference for this hypothetical confounder between exposure groups. Building on the methods put forth by Cornfield et al. (1959), Bross (1966), Schlesselman (1978), Rosenbaum & Rubin (1983), Lin et al. (1998), Lash et al. (2009), Rosenbaum (1986), Cinelli & Hazlett (2020), VanderWeele & Ding (2017), and Ding & VanderWeele (2016), we can use these quantities to assess how an unmeasured confounder may tip our result to insignificance.
How to cite:
Lucy D'Agostino McGowan (2017). tipr: Tipping Point Analyses. R package version 1.0.2, https://cran.r-project.org/web/packages/tipr. Accessed 10 Apr. 2025.
Previous versions and publish date:
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Other R packages that tipr depends,
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Complete documentation for tipr
Functions, R codes and Examples using
the tipr R package
Some associated functions: adjust_coef . adjust_coef_with_binary . adjust_coef_with_r2 . adjust_hr . adjust_hr_with_binary . adjust_or . adjust_or_with_binary . adjust_rr . adjust_rr_with_binary . e_value . exdata_continuous . exdata_rr . observed_bias_order . observed_bias_tbl . observed_bias_tip . observed_covariate_e_value . pipe . r_value . tip . tip_coef . tip_coef_with_r2 . tip_hr . tip_hr_with_binary . tip_or . tip_or_with_binary . tip_rr . tip_rr_with_binary . tip_with_binary . tipr .
Some associated R codes: adjust_coef_with_r2.R . adjust_coefficient.R . e_value.R . exdata_continuous.R . exdata_rr.R . observed-bias-plot-helpers.R . observed_bias_order.R . observed_bias_tbl.R . observed_bias_tip.R . observed_covariate_e_value.R . r_value.R . tip-helpers.R . tip.R . tip_coef.R . tip_coef_with_r2.R . tip_with_binary.R . tipr-package.R . utils.R . Full tipr package functions and examples
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