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)
a data frame containing the variables in the 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.
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.
# 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 × 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 × 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