mma.test {lawstat}

Mudholkar–McDermott–Aumont Test for Ordered Variances for Normal Samples

Description

Test for a monotonic trend in variances for normal samples. The test statistic is based on a combination of the finite intersection approach and the classical F (variance ratio) test (Mudholkar et al. 1993). By default, NAs are omitted.

Usage

mma.test(y, group, tail = c("right", "left", "both"))

Arguments

y

a numeric vector of data values.

group

factor of the data.

tail

the default option is "right", corresponding to an increasing trend in variances as the one-sided alternative; "left" corresponds to a decreasing trend in variances, and "both" corresponds to any (increasing or decreasing) monotonic trend in variances as the two-sided alternative.

Value

A list with the following components:

T

the statistic and p-value of the test based on the Tippett p-value combination.

F

the statistic and p-value of the test based on the Fisher p-value combination.

N

the statistic and p-value of the test based on the Liptak p-value combination.

L

the statistic and p-value of the test based on the Mudholkar–George p-value combination.

Each of the list elements is a list of class "htest" with the following elements:

statistic

the value of the test statistic.

p.value

the p-value of the test.

method

type of test performed.

data.name

a character string giving the name of the data.

Author(s)

Kimihiro Noguchi, Yulia R. Gel

References

Mudholkar GS, McDermott MP, Aumont J (1993). “Testing homogeneity of ordered variances.” Metrika, 40(1), 271–281. doi:10.1007/BF02613691.

See Also

neuhauser.hothorn.test, levene.test, lnested.test, ltrend.test, robust.mmm.test

Examples

data(pot)
mma.test(pot[, "obs"], pot[, "type"], tail = "left")$N