R script for performing ANCOVA with post-hoc tests and showing adjusted group means.

ancova_post_hoc.r

# Based on https://stats.stackexchange.com/a/57254
# Before running, look at all comments starting with XXX below

library('car')
library('compute.es')
library('effects')
library('emmeans')
library('ggplot2')
library('multcomp')
library('pastecs')
library('WRS2')

# XXX Update this with the data file location
df <- read.csv('C:\\Users\\guogu_000\\Documents\\Research\\R\\data.csv')

# XXX Update this with the number of levels for the categorical factor
contrasts(df$factor) = contr.sum(2)

model = aov(dv ~ factor + covariate + factor:covariate, data=df)

# Using 'II' should give more-or-less the same output as statsmodels
Anova(model, type='III')

posth = glht(model, linfct=mcp(factor='Tukey'))
summary(posth)
emmeans(model, ~ factor:covariate)