MVT (version 0.3)

homogeneity.test: Test of variance homogeneity of correlated variances

Description

Performs several test for testing equality of $p \ge 2$ correlated variables. Likelihood ratio test, score, Wald and gradient can be used as a test statistic.

Usage

homogeneity.test(object, test = "LRT", type = "scale")

Arguments

object

object of class 'studentFit' representing the fitted model.

test

test statistic to be used. One of "LRT" (default), "Wald", "score" or "gradient".

type

one of "scale" (default) or "both" indicating the type of the hypothesis to test homogeneity of variances or variances and means, respectively.

Value

A list of class 'homogeneity.test' with the following elements:

statistic

value of the statistic, i.e. the value of either Likelihood ratio test, Wald, score or gradient test.

parameter

the degrees of freedom for the test statistic, which is chi-square distributed.

p.value

the p-value for the test.

estimate

the estimated covariance matrix.

null.value

the hypothesized value for the covariance matrix.

method

a character string indicating what type of test was performed.

null.fit

a list representing the fitted model under the null hypothesis.

data

name of the data used in the test.

References

Harris, P. (1985). Testing the variance homogeneity of correlated variables. Biometrika 72, 103-107. Modarres, R. (1993). Testing the equality of dependent variables. Biometrical Journal 7, 785-790.

Osorio, F., and Galea, M. (2015). Statistical inference in multivariate analysis using the t-distribution. Unpublished manuscript.

Examples

data(examScor)
fit <- studentFit(examScor, family = Student(eta = .25))
fit

z <- homogeneity.test(fit, test = "LRT")
z