mrbp: Multiresponse permutation procedures for randomized blocks
In Blossom: Statistical Comparisons with Distance-Function Based Permutation Tests

Description Usage Arguments Details Value References See Also Examples

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

1 2	mrbp(variables, group, block, data, expon = 1, exact = FALSE, number.perms, commens = TRUE, align = TRUE, save.test)

`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 <10 group combinations.
`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).

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.

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.

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

pvalue and ResampVals

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)

	Multiresponse Randomized Block Procedure (MRBP) 

Call: 
mrbp(data = mrbp1, commens = FALSE, align = FALSE, save.test = TRUE) 

Specification of Analysis:
	Response Variables      :  spp1 spp2 spp3
	Number of Observations  :  18
	Grouping Variable       :  trtmt 
	   Number of Groups     :  6
	Blocking Variable       :  block 
	   Number of Blocks     :  3
	Distance Exponent       :  1

Group Summary: 
  Group Value  Group Size
            1           3
            2           3
            3           3
            4           3
            5           3
            6           3

	Data are not aligned within blocks
	Variables are not commensurated

 Results: 
	Delta Observed                :  7.689301
	Delta Expected                :  9.220918
	Delta Variance                :  0.9176017
	Delta Skewness                :  -0.6031743
	Agreement measure among blocks:  0.1661024
	Standardized test statistic   :  -1.598906
	Probability (Pearson Type III)
	of a smaller or equal delta   :  0.06763839.
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Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1