Performs Levene's test to assess the null hypothesis that the variances are equal across all groups (samples) defined by the independent variable.
Arguments
- data
A data frame containing the variables specified in the formula.
- formula
A formula of the form
DV ~ IV, whereDVis the dependent (response) variable andIVis the independent (grouping) variable.- alpha
A numeric value specifying the significance level. Must be between 0 and 1. Default is 0.05.
- silent
A logical value. If
FALSE(default), results are printed to the console. IfTRUE, no output is printed.- summary
A logical value (default:
FALSE). IfTRUE, a summary table for the input data is returned.- misc
A logical value. If
FALSE(default), only essential parameters are returned. IfTRUE, additional auxiliary parameters are included in the output.- transform
A function used to transform the response variable into deviations from a specified location measure.
Value
A list containing the test statistics, p-value, degrees of freedom,
and optionally a summary table and/or auxiliary parameters,
depending on the values of summary and misc.
Details
transform:
The concept is similar to ANOVA procedure (transform the response variable to
residuals before analysis). Possible transformation are:
y' = |yi - ybar| (default)
y' = (yi - ybar) ^ 2
y' = ln((yi - ybar) ^ 2)
y' = sqrt(|yi - ybar|)
The ybar could be either mean, median (default), or trimmed-mean.
References
Levene, H. (1960). Robust tests for equality of variances. In I. Olkin (Ed.), Contributions to probability and statistics: Essays in honor of Harold Hotelling (pp. 278–292). Stanford University Press.
Sharma, D., & Kibria, B. M. G. (2013). On some test statistics for testing homogeneity of variances: A comparative study. Journal of Statistical Computation and Simulation, 83, 1944–1963. https://doi.org/10.1080/00949655.2012.675336
Zhou, Y., Zhu, Y., & Wong, W. K. (2023). Statistical tests for homogeneity of variance for clinical trials and recommendations. Contemporary Clinical Trials Communications, 33, 101119. https://doi.org/10.1016/j.conctc.2023.101119
Examples
df0 <- roGFP[[1]]
out <- Levene_test(df0, ro ~ grp)
#>
#> ---------------------------------------
#> Levene's homogeneity of variance test
#>
#> Response: ro
#>
#> DF SS MS Fvalue pvalue
#> Group 3 0.01 0 3.1837 0.0325
#> Residuals 46 0.03 0
#> Total 49 0.03
#>
#> #> Group variances are unequal.
#> ---------------------------------------
boxplot(ro ~ grp, df0, horizontal = TRUE)
points(x = df0$ro, y = jitter(as.numeric(df0$grp), amount = 0.15))