Blossom (version 1.4)

mrbp: Multiresponse permutation procedures for randomized blocks

Description

Multiresponse permutation procedures for randomized blocks (MRBP) are used for univariate and multivariate analyses of grouped data in a complete randomized block design.

Usage

mrbp(variables, group, block, data, expon = 1, exact = FALSE, number.perms, commens = TRUE, align = TRUE, save.test)

Arguments

variables

the names of response variables to be used in the analysis. If more than one is used these are specified using the form c(var1,var2,...).

group

the name of the grouping variable to be used in the analysis.

block

the name of the blocking variable to be used in the analysis.

data

the data.frame or matrix containing columns with names matching all values supplied in the variables, group, and block arguments. Alternatively, if none of variables, group, and block are supplied, it is assumed that the first column is the grouping column, the second is the block column, and all remaining columns are variables to be used in the analysis.

expon

allows selection of alternative exponents in distance calculations.

exact

a logical value indicating whether to perform an exact test. This is only available for

number.perms

number of permutations used if a Monte Carlo resampling procedure is selected.

commens

a logical value indicating whether to perform multivariable commensuration. Commensuration can only be done when there is more than one variable.

align

A logical indicating whether the data should be aligned so that the median of all blocks is equal.

save.test

A logical indicating whether to save Monte Carlo resampling values of the test statistic (Delta).

Value

mrbp returns an object of class MRBPObj.The functions summary as well as print can be used to obtain a summary of the test.Generic accessor functions pvalue and ResampVals can be used to obtain the p-value and Monte Carlo resampled test statistic values respectively.

Details

The value chosen to align each block is selected to make the block medians all equal to zero. Blossom aligns each block by default. If there is more than one response variable then Blossom adjusts or commensurates variables by their average Euclidean distance by default as in mrbp.

References

Mielke, P.W., Jr., and K.J. Berry. 2001. Permutation methods: A distance function approach. Springer-Verlag.

See Also

pvalue and ResampVals

Examples

BiomassExamp <- mrbp(data = mrbp1,commens = FALSE,align = FALSE,save.test = TRUE)
summary(BiomassExamp)
#this just demonstrates another way of specifying the analysis 
BiomassExamp <- mrbp(variables = c(spp1,spp2,spp3),group = trtmt,block = block,data = mrbp1)