MultiDimen_test {CNPS}

Multivariate Permutation Test and Paired Comparisons

Description

Performs multivariate permutation tests, including paired tests.

Usage

MultiDimen_test (data , stat = "HT",pair=FALSE, method_p = "sampling",rank = FALSE,
diff = FALSE , samplenum = 1000)

Arguments

data

a matrix or data frame of data values.

stat

a character string specifying the statistic, must be one of "HT" (default), "tmax", "tmaxabs", "wsum", "zmax", "zmaxabs".

pair

a logical indicating whether you want a paired test.

method_p

a character string specifying the method of calculating p-value, must be one of "sampling" (default), " asymptotic", "exact".

rank

a logical indicating whether you want Wilcoxon test.

diff

a logical indicating whether you want to present which variables are different.

samplenum

a number specifying the number of sampling.

Details

The test can be used for multivariate permutation test and multivariate paired comparisons.

When doing multivariate paired comparisons, that is pair = TRUE, the statistic wsum is not suitable. Meanwhile, asymptotic method can only be used when statistic is HT. Besides, the second last column of the data must only contain two unique numbers to represent the two samples; the last column represents different pairs.

When doing multivariate permutation test, that is pair = FALSE, the statistic zmax and zmaxabs are not suitable. Meanwhile, the last column of the data must only contain 0 and 1 to represent the two samples. Besides, asymptotic method can not be used when statistic is tmax or tmaxabs.

Value

method

the test which is used.

score

a character string describing the score used for test.

stat

the test statistic.

pval

p-value for the test.

alternative

a character string describing the alternative hypothesis.

addition

a character string describing which variable is different in two samples.(presents only if pair = FALSE)

Author(s)

Jiasheng Zhang, Feng Yu, Yangyang Zhang, Siwei Deng. Tutored by YuKun Liu and Dongdong Xiang.

References

Higgins, J. J. (2004). An introduction to modern nonparametric statistics. Pacific Grove, CA: Brooks/Cole.

Examples

## Multivariate permutation test
data = matrix(c(6.81, 6.16, 5.92, 5.86, 5.80, 5.39,
              6.68, 6.30, 6.12, 5.71, 6.09, 5.28,
              6.34, 6.22, 5.90, 5.38, 5.20, 5.46,
              6.68, 5.24, 5.83, 5.49, 5.37, 5.43,
              6.79, 6.28, 6.23, 5.85, 5.56, 5.38,
              6.85, 6.51, 5.95, 6.06, 6.31, 5.39,
              6.64, 5.91, 5.59, 5.41, 5.24, 5.23,
              6.57, 5.89, 5.32, 5.41, 5.32, 5.30,
              6.84, 6.01, 5.34, 5.31, 5.38, 5.45,
              6.71, 5.60, 5.29, 5.37, 5.26, 5.41,
              6.58, 5.63, 5.38, 5.44, 5.17, 6.62,
              6.68, 6.04, 5.62, 5.31, 5.41, 5.44),
              nrow = 12,ncol = 6,byrow = TRUE
)
data=as.matrix(data)
index=c(rep(0,6),rep(1,6))
data = cbind(data,index)
x = MultiDimen_test(data ,  rank = FALSE ,  method_p = "sampling", samplenum = 100
, stat = "HT",diff = TRUE )
y = MultiDimen_test(data ,  rank = FALSE ,  method_p = "sampling", samplenum = 100
, stat = "tmax",diff = TRUE)
z = MultiDimen_test(data ,  rank = TRUE , method_p = "sampling"  , stat = "HT"
, samplenum = 100,diff = TRUE)

## Multivaraite paired comparisons
data = matrix(c(82, 60,  72, 62,
                75, 71,  70, 68,
                85, 59,  87, 64,
                90, 77,  87, 78),
              nrow = 4,ncol = 4,byrow = TRUE
)
x = data[,c(1,2)]
y = data[,c(3,4)]
data = cbind(rbind(x,y) , c(0,0,1,1) , c(1,2,1,2))
MultiDimen_test(data , method_p = "exact" , pair = TRUE)