plotVisreg: Visualizing adjusted linear regression models

In lwjohnst86/rstatsToolkit: Bundles up all my most used functions for doing statistical analysis

Description

Generates plots of a linear regression model which includes confounding variables.

Usage

plotVisreg(data, y, x, covar, ylabel = x, xlabel = y, ...)

Arguments

data	Dataset with the variables of interest
y	The dependent or outcome variable in the regression equation
x	The independent or exposure variable in the regression equation
covar	The confounding variables, that is the variables being adjusted for
ylabel	The y-axis label
xlabel	The x-axis label
...	Other options. In development

Details

This function runs a linear regression on the specified variables and plots the partial residuals. This allows for visualizing the relationship between the outcome and the exposure, after adjusting for confounders. A linear slope is plotted through the partial residuals, with a confidence interval band around it. The output is a plot. This function depends on visreg.

Value

Outputs a plot of the regression model

Author(s)

Luke Johnston

lwjohnst86/rstatsToolkit documentation built on May 21, 2019, 9:15 a.m.