Post-hoc pairwise t-tests for ANOVA

Runs pairwise t-tests for a one-way analysis of variance, with corrections for multiple comparisons.

Usage

posthocPairwiseT(x, ...)

Arguments

x

An aov object, as returned by aov. Only one-way ANOVA models are supported.

...

Additional arguments passed to pairwise.t.test, such as p.adjust.method.

Value

Prints a table of p-values for all pairwise group comparisons. The underlying result is also returned as a list (with the same structure as pairwise.t.test) so it can be assigned to a variable and inspected if needed.

Details

Takes a fitted one-way ANOVA object and runs pairwise t-tests for all pairs of groups, applying a correction for multiple comparisons. This is a simpler alternative to TukeyHSD that uses the same correction methods (e.g., Holm, Bonferroni) as pairwise.t.test.

See also

pairwise.t.test, TukeyHSD, aov

Examples

dataset <- data.frame(
  outcome = c(1, 2, 3, 2, 3, 4, 5, 6, 7),
  group = factor(c("a", "a", "a", "b", "b", "b", "c", "c", "c"))
)

anova1 <- aov(outcome ~ group, data = dataset)
summary(anova1)
#>             Df Sum Sq Mean Sq F value  Pr(>F)   
#> group        2     26      13      13 0.00659 **
#> Residuals    6      6       1                   
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

# post-hoc pairwise comparisons with Holm correction (the default)
posthocPairwiseT(anova1)
#> 
#> 	Pairwise comparisons using t tests with pooled SD 
#> 
#> data:  outcome and group 
#> 
#>   a      b     
#> b 0.2666 -     
#> c 0.0081 0.0208
#> 
#> P value adjustment method: holm 

# Bonferroni correction instead
posthocPairwiseT(anova1, p.adjust.method = "bonferroni")
#> 
#> 	Pairwise comparisons using t tests with pooled SD 
#> 
#> data:  outcome and group 
#> 
#>   a      b     
#> b 0.7997 -     
#> c 0.0081 0.0312
#> 
#> P value adjustment method: bonferroni