Tests for equal means in a one-way design (not assuming equal variance). A wrapper around the base function oneway.test(). This is is an alternative to the standard one-way ANOVA in the situation where the homogeneity of variance assumption is violated.

welch_anova_test(data, formula)

Arguments

data

a data frame containing the variables in the formula.

formula

a formula specifying the ANOVA model similar to aov. Can be of the form y ~ group where y is a numeric variable giving the data values and group is a factor with one or multiple levels giving the corresponding groups. For example, formula = TP53 ~ cancer_group.

Value

return a data frame with the following columns:

  • .y.: the y variable used in the test.

  • n: sample count.

  • statistic: the value of the test statistic.

  • p: p-value.

  • method: the statistical test used to compare groups.

Examples

# Load data #::::::::::::::::::::::::::::::::::::::: data("ToothGrowth") df <- ToothGrowth df$dose <- as.factor(df$dose) # Welch one-way ANOVA test (not assuming equal variance) #::::::::::::::::::::::::::::::::::::::::: df %>% welch_anova_test(len ~ dose)
#> # A tibble: 1 x 7 #> .y. n statistic DFn DFd p method #> * <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> #> 1 len 60 68.4 2 37.7 2.81e-13 Welch ANOVA
# Grouped data #::::::::::::::::::::::::::::::::::::::::: df %>% group_by(supp) %>% welch_anova_test(len ~ dose)
#> # A tibble: 2 x 8 #> supp .y. n statistic DFn DFd p method #> * <fct> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> #> 1 OJ len 30 29.4 2 17.1 0.00000295 Welch ANOVA #> 2 VC len 30 59.4 2 17.2 0.0000000194 Welch ANOVA