Section 8.4 Post-Hoc Test
A post-hoc test is a statistical test conducted after ANOVA to assess the significance of differences between group means when an overall difference is detected. The F ratio from ANOVA indicates the presence of significant differences among the groups, and post-hoc tests aim to identify the specific nature and location of these differences (Vogt & Johnson, 2011).
While the results from our one-way ANOVA suggest that the mean scores for confidence in the police are equal across groups who watched different videos, we will conduct a post-hoc test for demonstration purposes.
There are many types of post-hoc tests, but I will use Tukey’s honestly significant difference (HSD) test to identify which groups differ.
tukey.police.by.con <- TukeyHSD(x = aov(formula = ConPolT2 ~ Condition,
data = media_and_police_cleaned))
tukey.police.by.con
The
diff column represents the difference between the means in the sample. The lwr and upr columns denote the lower and upper bounds of a confidence interval around the diff value. The p adj column displays the adjusted p-value, indicating the statistical significance of the difference after adjusting for multiple comparisons. Not surprisingly, confidence in the police was not significantly different between any of these groups.
