lawstat (version 3.2)

robust.mmm.test: Robust Mudholkar-McDermott-Mudholkar test for ordered variances

Description

The function performs a test for a monotonic trend in variances. 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 alternatives; "left" corresponds to a decreasing trend in variances, and "both" corresponds to any (increasing or decreasing) monotonic trend in variances as the two-sided alternatves.

Value

A list with the following vector 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 vector components contains the following numeric components.

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.

References

Mudholkar, G. S., McDermott, M. P., & Mudholkar, A. (1995). Robust finite-intersection tests for homogeneity of ordered variances. Journal of Statistical Planning and Inference 43, 185-195.

See Also

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

Examples

# NOT RUN {
data(pot)
robust.mmm.test(pot[,"obs"], pot[,"type"], tail="left")$N

##   Mudholkar et al. (1995) test (left-tailed)
##
## data:  pot[, "obs"] 
## Test Statistic (N) = 7.4079, p-value = 8.109e-08

# }