robust.mmm.test {lawstat}

Robust Mudholkar–McDermott–Mudholkar Test for Ordered Variances

Description

A test for a monotonic trend in variances (Mudholkar et al. 1995). 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

Mudholkar GS, McDermott MP, Mudholkar A (1995). “Robust finite-intersection tests for homogeneity of ordered variances.” Journal of Statistical Planning and Inference, 43(1-2), 185–195. doi:10.1016/0378-3758(94)00018-Q.

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