Check model assumptions with easystats package in R

Packages we will need:

install.packages("easystats", repos = "https://easystats.r-universe.dev")
library(easystats)
easystats::install_suggested()

Easystats is a collection of R packages, which aims to provide a framework to tame the scary R statistics and their pesky models, according to their github repo.

Click here to browse the github and here to go to the specific perfomance package CRAN PDF

First run your regression. I will try to explain variance is Civil Society Organization participation (CSOs) with the independent variables in my model with Varieties of Democracy data in 1990.

cso_model <- lm(cso_part ~ education_level + mortality_rate + democracy,data = vdem_90)

	Dependent variable:
	cso_part
education_level	-0.017**
	(0.007)
mortality_rate	-0.00001
	(0.00004)
democracy	0.913***
	(0.064)
Constant	0.288***
	(0.054)
Observations	134
R2	0.690
Adjusted R2	0.682
Residual Std. Error	0.154 (df = 130)
F Statistic	96.243*** (df = 3; 130)
Note:	*p<0.1; **p<0.05; ***p<0.01

Then we check the assumptions:

performance::check_model(cso_model)