This function performs the Levene's test for equality of variance.

levene_test(data = NULL, x, groups, alpha = 0.05, modcv = FALSE)

## Arguments

data 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.

## Value

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

## Details

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.

## References

“Composite Materials Handbook, Volume 1. Polymer Matrix Composites Guideline for Characterization of Structural Materials,” SAE International, CMH-17-1G, Mar. 2012.

## See also

calc_cv_star

transform_mod_cv

## Examples

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 )