agricolae (version 1.2-8)

Median.test: Median test. Multiple comparisons

Description

A nonparametric test for several independent samples. The median test is designed to examine whether several samples came from populations having the same median.

Usage

Median.test(y,trt,alpha=0.05,correct=TRUE,simulate.p.value = FALSE, group = TRUE, 
main = NULL,console=TRUE)

Arguments

y

Variable response

trt

Treatments

alpha

error type I

correct

a logical indicating whether to apply continuity correction when computing the test statistic for 2 groups. The correction will not be bigger than the differences themselves. No correction is done if simulate.p.value = TRUE.

simulate.p.value

a logical indicating whether to compute p-values by Monte Carlo simulation

group

TRUE or FALSE

main

Title

console

logical, print output

Value

statistics

Statistics of the model

parameters

Design parameters

medians

Statistical summary of the study variable

comparison

Comparison between treatments

groups

Formation of treatment groups

Details

The data consist of k samples of possibly unequal sample size. Greater: is the number of values that exceed the median of all data and LessEqual: is the number less than or equal to the median of all data.

References

Practical Nonparametrics Statistics. W.J. Conover, 1999

See Also

BIB.test, DAU.test, duncan.test, durbin.test, friedman, HSD.test, kruskal, LSD.test, PBIB.test, REGW.test, scheffe.test, SNK.test, waerden.test, waller.test, plot.group

Examples

# NOT RUN {
library(agricolae)
# example 1
data(corn)
out<-with(corn,Median.test(observation,method,console=FALSE))
z<-bar.err(out$medians,variation = "range",ylim=c(0,120),
           space=2,border=4,col=3,density=10,angle=45)
# example 2
out<-with(corn,Median.test(observation,method,console=FALSE,group=FALSE))
print(out$comparison)
# }