robust.mmm.test {lawstat} | R Documentation |
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.
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 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. |
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. |
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. |
Kimihiro Noguchi, Yulia R. Gel
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.
neuhauser.hothorn.test
, levene.test
, lnested.test
,
ltrend.test
, mma.test
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