robust.mmm.test: Robust Mudholkar-McDermott-Mudholkar Test for Ordered...

In lawstat: Tools for Biostatistics, Public Policy, and Law

Robust Mudholkar–McDermott–Mudholkar Test for Ordered Variances

Description

A test for a monotonic trend in variances \insertCiteMudholkar_etal_1995lawstat. The test statistic is based on a combination of the finite intersection approach and the two-sample t-test using Miller's transformation. By default, NAs are omitted.

Usage

robust.mmm.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 elements:

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

\insertAllCited

See Also

neuhauser.hothorn.test, levene.test, lnested.test, ltrend.test, mma.test

Examples

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

lawstat documentation built on April 6, 2023, 1:06 a.m.