var_tests | R Documentation |
Displayed sample sizes and SDs and performs Brown-Forsythe and
Fligner-Killeen variance equality tests (tests of homogeneity of variances)
per group combinations. This is primarily a subfunction of
anova_neat
, but here it is available separately for other
potential purposes.
var_tests(xvar, group_by, dat = NULL, hush = FALSE, sep = ", ")
xvar |
Either a numeric vector (numbers of any given variable), or, if
|
group_by |
Either a vector of factors with which to group the |
dat |
Either |
hush |
Logical. If |
sep |
String (underscore |
Prints test results.
Brown-Forsythe test (i.e., Levene's test using medians) is calculated via
car::leveneTest
. Fligner-Killeen test, which may
be more robust (i.e., less affected by non-normal distribution), is calculated
via stats::fligner.test
. (See also Conover
et al., 1981, p. 360.)
Brown, M. B. & Forsythe, A. B. (1974). Robust tests for the equality of variances. Journal of the American Statistical Association, 69, pp. 364-367.
Conover W. J., Johnson M. E., & Johnson M. M. (1981). A comparative study of tests for homogeneity of variances, with applications to the outer continental shelf bidding data. Technometrics, 23, 351–361.
Fligner, M. A. & Killeen, T. J. (1976). Distribution-free two-sample tests for scale. ‘Journal of the American Statistical Association. 71(353), 210-213.
Fox, J. & Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Levene, H. (1960). Robust tests for equality of variances. In I. Olkin, H. Hotelling, et al. (eds.). Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling. Stanford University Press. pp. 278–292.
anova_neat
data("ToothGrowth") # load base R example dataset # the statistics of the four functions below should match var_tests(ToothGrowth$len, ToothGrowth$supp) var_tests('len', 'supp', ToothGrowth) car::leveneTest(len ~ supp, data = ToothGrowth) stats::fligner.test(len ~ supp, ToothGrowth) # again the results below should match each other var_tests(ToothGrowth$len, interaction(ToothGrowth$supp, ToothGrowth$dose)) var_tests('len', c('supp', 'dose'), ToothGrowth) car::leveneTest(len ~ supp * as.factor(dose), data = ToothGrowth) stats::fligner.test(len ~ interaction(supp, dose), ToothGrowth)
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