Learn R Programming

⚠️There's a newer version (1.0.2) of this package.Take me there.

tipr: R tools for tipping point sensitivity analyses

Authors: Lucy D’Agostino McGowan License: MIT

Installation

# install.packages(devtools)
devtools::install_github("lucymcgowan/tipr")
library("tipr")

Usage

After fitting your model, you can determine the unmeasured confounder needed to tip your analysis. This unmeasured confounder is determined by two quantities, the association between the exposure and the unmeasured confounder (if the unmeasured confounder is continuous, this is indicated with smd, if binary, with exposed_p and unexposed_p), and the association between the unmeasured confounder and outcome outcome_association. Using this

Copy Link

Version

Install

install.packages('tipr')

Monthly Downloads

267

Version

0.3.0

License

MIT + file LICENSE

Maintainer

Lucy D'Agostino McGowan

Last Published

February 6th, 2024

Functions in tipr (0.3.0)

%>%

Pipe operator
observed_covariate_e_value

Calculate the Observed Covariate E-value
observed_bias_order

Order observed bias data frame for plotting
lm_tip

Tip a linear model result with a continuous confounder.
tip_with_binary

Tip a result with a binary confounder.
tip

Tip a result with a continuous confounder.
observed_bias_tbl

Create a data frame to assist with creating an observed bias plot
observed_bias_tip

Create a data frame to combine with an observed bias data frame demonstrating a hypothetical unmeasured confounder
tipr

tipr