This function extends bartlett.test to a multivariate
response setting. It performs the Bartlett test of homogeneity of variances
for each of a set of response variables, and prints a compact summary.
Arguments
- y
A data frame or matrix of numeric response variables in a multivariate linear model.
- group
a vector or factor object giving the group for the corresponding elements of the rows of
y- ...
other arguments, passed to
bartlett.test
Value
An object of classes "anova" and "data.frame", with one observation
for each response variable in y.
Details
Bartlett's test is the univariate version of Box's M test for equality of covariance matrices. This function provides a univariate follow-up test to Box's M test to give one simple assessment of which response variables contribute to significant differences in variances among groups.
References
Bartlett, M. S. (1937). Properties of sufficiency and statistical tests. Proceedings of the Royal Society of London Series A, 160, 268-282.
See also
boxM for Box's M test for all responses.
Examples
bartlettTests(iris[,1:4], iris$Species)
#> Bartlett's Tests for Homogeneity of Variance
#>
#> Chisq df Pr(>Chisq)
#> Sepal.Length 16.0057 2 0.0003345 ***
#> Sepal.Width 2.0911 2 0.3515028
#> Petal.Length 55.4225 2 9.229e-13 ***
#> Petal.Width 39.2131 2 3.055e-09 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
data(Skulls, package="heplots")
bartlettTests(Skulls[,-1], Skulls$epoch)
#> Bartlett's Tests for Homogeneity of Variance
#>
#> Chisq df Pr(>Chisq)
#> mb 7.3382 4 0.1191
#> bh 0.7315 4 0.9474
#> bl 3.5155 4 0.4755
#> nh 4.3763 4 0.3575