robust.mmm.test: Robust Mudholkar-McDermott-Mudholkar Test for Ordered...
In gel-research-group/lawstat: Tools for Biostatistics, Public Policy, and Law

Description Usage Arguments Value Author(s) References See Also Examples

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.

1	robust.mmm.test(y, group, tail = c("right", "left", "both"))

`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.

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.