linearcheck R package

This is a package that checks the assumptions (equal variance, normality, independence, linearity) for a simple linear regression. Do not use this package for a multiple linear regression as there is only one x variable included.

Equal Variance Assumption

• residplot() allows you to specify x and y variables in a dataset to build a residual plot.

• bptable() allows you to specify x and y variables in a dataset and prints Breusch-Pagan test results. Prints Breusch-Pagan interpretation if commentary = TRUE.

Normality Assumption

• qqgraph() allows you to specify x and y variables in a dataset to build a Quantile-Quantile plot.

• swtable() allows you to specify x and y variables in a dataset and prints Shapiro-Wilk test results. Prints Shapiro-Wilk interpretation if commentary = TRUE.

Independence Assumption

• acf_pacf() allows you to specify x and y variables in a dataset to build ACF and PACF plots for both x and y variables.

• dwtable() allows you to specify x and y variables in a dataset and prints Durbin-Watson test results. Prints Durbin-Watson interpretation if commentary = TRUE.

Linearity Assumption

• linearplot() allows you to specify x and y variables in a dataset to build a scatterplot with line of best fit.

• stats_table() allows you to specify x and y variables in a dataset and prints summary statitistics. Prints adjusted R-squared and p-value interpretation if commentary = TRUE.

Installation

1. Install and load in devtools package

install.packages("devtools")
library(devtools)

2. Install r package from github and load in linearcheck package

install_github("chloefeehan/linearcheck")
library(linearcheck)

Examples

Equal Variance Assumption

data(cars)
residplot(cars, speed, dist)
bptable(cars, speed, dist, commentary = TRUE)

Normality Assumption

data(cars)
qqgraph(cars, speed, dist)
swtable(cars, dist, commentary = TRUE)

Independence Assumption

data(cars)
acf_pacf(cars, speed, dist) 
dwtable(cars, speed, dist, commentary = TRUE)

Linearity Assumption

data(cars)
linearplot(cars, speed, dist, title = "Plot") 
stats_table(cars, speed, dist, commentary = TRUE)