This function performs the Levene's test for equality of variance.
levene_test(data = NULL, x, groups, alpha = 0.05, modcv = FALSE)a data.frame
the variable in the data.frame or a vector on which to perform the Levene's test (usually strength)
a variable in the data.frame that defines the groups
the significance level (default 0.05)
a logical value indicating whether the modified CV approach should be used.
Returns an object of class adk. This object has the following fields:
call the expression used to call this function
data the original data supplied by the user
groups a vector of the groups used in the computation
alpha the value of alpha specified
modcv a logical value indicating whether the modified
CV approach was used.
n the total number of observations
k the number of groups
f the value of the F test statistic
p the computed p-value
reject_equal_variance a boolean value indicating whether the
null hypothesis that all samples have the same variance is rejected
modcv_transformed_data the data after the modified CV transformation
This function performs the Levene's test for equality of variance. The data is transformed as follows:
$$w_{ij} = \left| x_{ij} - m_i \right|$$
Where \(m_i\) is median of the \(ith\) group. An F-Test is then performed on the transformed data.
When modcv=TRUE, the data from each group is first transformed
according to the modified coefficient of variation (CV) rules before
performing Levene's test.
“Composite Materials Handbook, Volume 1. Polymer Matrix Composites Guideline for Characterization of Structural Materials,” SAE International, CMH-17-1G, Mar. 2012.
library(dplyr)
carbon.fabric.2 %>%
filter(test == "FC") %>%
levene_test(strength, condition)
#>
#> Call:
#> levene_test(data = ., x = strength, groups = condition)
#>
#> n = 91 k = 5
#> F = 3.883818 p-value = 0.00600518
#> Conclusion: Samples have unequal variance ( alpha = 0.05 )
#>
##
## Call:
## levene_test(data = ., x = strength, groups = condition)
##
## n = 91 k = 5
## F = 3.883818 p-value = 0.00600518
## Conclusion: Samples have unequal variance ( alpha = 0.05 )