| posthoc.friedman.conover.test {PMCMR} | R Documentation |
Calculate pairwise comparisons using Conover post-hoc test for
unreplicated blocked data. This test is usually conducted post-hoc after
significant results of the friedman.test. The statistics refer to
the student-t-distribution (TDist).
posthoc.friedman.conover.test(y, ...) ## Default S3 method: posthoc.friedman.conover.test(y, groups, blocks, p.adjust.method = p.adjust.methods, ...)
y |
either a numeric vector of data values, or a data matrix. |
groups |
a vector giving the group for the corresponding elements of |
blocks |
a vector giving the block for the corresponding elements
of |
p.adjust.method |
Method for adjusting p values
(see |
... |
further arguments to be passed to or from methods. |
A one-way ANOVA with repeated measures that is also referred to as ANOVA with unreplicated block design can also be conducted via the friedman.test. The consequent post-hoc pairwise multiple comparison test according to Conover is conducted with this function.
If y is a matrix, than the columns refer to the treatment and the rows indicate the block.
See vignette("PMCMR") for details.
A list with class "PMCMR"
method |
The applied method. |
data.name |
The name of the data. |
p.value |
The two-sided p-value according to the student-t-distribution. |
statistic |
The estimated quantiles of the student-t-distribution. |
p.adjust.method |
The applied method for p-value adjustment. |
This function does not test for ties.
Thorsten Pohlert
W. J. Conover and R. L. Iman (1979), On multiple-comparisons procedures, Tech. Rep. LA-7677-MS, Los Alamos Scientific Laboratory.
W. J. Conover (1999), Practical nonparametric Statistics, 3rd. Edition, Wiley.
friedman.test,
posthoc.friedman.nemenyi.test,
TDist
p.adjust
##
## Sachs, 1997, p. 675
## Six persons (block) received six different diuretics
## (A to F, treatment).
## The responses are the Na-concentration (mval)
## in the urine measured 2 hours after each treatment.
##
y <- matrix(c(
3.88, 5.64, 5.76, 4.25, 5.91, 4.33, 30.58, 30.14, 16.92,
23.19, 26.74, 10.91, 25.24, 33.52, 25.45, 18.85, 20.45,
26.67, 4.44, 7.94, 4.04, 4.4, 4.23, 4.36, 29.41, 30.72,
32.92, 28.23, 23.35, 12, 38.87, 33.12, 39.15, 28.06, 38.23,
26.65),nrow=6, ncol=6,
dimnames=list(1:6,c("A","B","C","D","E","F")))
print(y)
friedman.test(y)
posthoc.friedman.conover.test(y=y, p.adjust="none")