Perform Bartlett's test for equality of variances

Uses bartlett.test on model residuals grouped by a factor.

Usage

performBartlettTest(model, data, group)

Details

The test statistic compares the pooled variance to the individual group variances. It is computed as \(\chi^2 = (N - k) \ln S_p^2 - \sum (n_i - 1) \ln s_i^2\), where \(S_p^2\) is the pooled variance and \(s_i^2\) the group variances. Under the null it approximates a chi-square distribution with \(k-1\) degrees of freedom.

Arguments

model

an object of class lm.

data

data frame used to fit model.

group

name of the grouping variable.

Value

An object of class htest containing the chi-squared statistic, p-value and degrees of freedom.

References

Bartlett, M. S. (1937). Properties of sufficiency and statistical tests. Proceedings of the Royal Society of London, 160(901), 268–282. doi:10.1098/rspa.1937.0109

Hartley, H. O. (1950). The maximum F-ratio as a short-cut test for heterogeneity of variance. Biometrika, 37(3/4), 308–312. doi:10.2307/2332383

Examples

 data(mtcars)
 mtcars$cyl <- factor(mtcars$cyl)
 m <- lm(mpg ~ wt, data = mtcars)
 performBartlettTest(m, mtcars, "cyl")
#> 
#> 	Bartlett's test for equality of variances
#> 
#> data:  mpg ~ wt
#> X-squared = 4.1572, = 2, p-value = 0.1251
#>