| homogeneity.test {MVT} | R Documentation |
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")
Arguments
object |
object of class |
test |
test statistic to be used. One of "LRT" (default), "Wald", "score" or "gradient". |
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.
Examples
data(examScor)
fit <- studentFit(examScor, family = Student(eta = .25))
fit
z <- homogeneity.test(fit, test = "LRT")
z