friedmanmc: Multiple comparisons after Friedman test

In pgirmess: Spatial Analysis and Data Mining for Field Ecologists

Multiple comparisons after Friedman test

Description

Test of multiple comparison after Friedman test

Usage

friedmanmc(y, groups, blocks,alpha=0.05)

Arguments

y	a numeric vector of data values, or a data matrix
groups	a vector giving the group for the corresponding elements of 'y' if this is a vector; ignored if 'y' is a matrix. If not a factor object, it is coerced to one.
blocks	a vector giving the block for the corresponding elements of 'y' if this is a vector; ignored if 'y' is a matrix. If not a factor object, it is coerced to one.
alpha	the significiance level

Details

Method for formula still not implemented. Formula 7.5a (Siegel & Castellan, 1988 p 180-181) can lead to p-values larger than 1 when differences between groups are small. Eventually, they are set to NA and a warning is generated.

Value

A list of class 'mc' with the following items:

statistic	statistics used
alpha	the significance level
dif.com	a data.frame with observed and critical differences, statistical significance at the alpha risk (true/false) and p-value

References

Siegel & Castellan (1988) Non parametric statistics for the behavioural sciences. Mc Graw Hill Int. Edt.

See Also

friedman.test; for other functions about median multiple comparison see package 'PMCMRplus'

Examples

  data(siegelp179)
  attach(siegelp179)
  
  friedman.test(score,treatment,block)
  friedmanmc(score,treatment,block)
  friedmanmc(score,treatment,block,alpha=0.01)
  
  mymatrix<-matrix(score,nc=3)
  friedman.test(mymatrix)
  friedmanmc(mymatrix)
  detach(siegelp179)
  

pgirmess documentation built on April 8, 2023, 1:12 a.m.