pairwise_test {CNPS}

Paired Comparisons

Description

Detects differences between two related samples.

Usage

pairwise_test(x, y, alternative = "greater", score = "wilcoxon", method_p = "asymptotic",
method_asymptotic = "norm", method_wilcoxon = "type1", samplenum = 1000,
conf.level.sample = 0.95, samplemethod = "R")

Arguments

x

numeric vectors of data values and should have the same length

y

numeric vectors of data values and should have the same length

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided", "greater"(default) or "less"

score

determines scoring systems and must be one of "original", "wilcoxon" or "sign"

method_p

a string indicating what method to use for p-value. "sampling" represents sampling; "asymptotic" represents using large sample approximations; "exact" represents Iterate through all combinations

method_asymptotic

determines the asymptotic distribution and should be one of "norm" or "binomial"(only for method_p="sign")

method_wilcoxon

indicates the way to compute wilcoxon ranks when the ties are 0 and could be one of "type1" or "type2"

samplenum

the number of SRS samples

conf.level.sample

p-value confidence level for SRS sampling

samplemethod

a discrete value indicating the method of sampling. "S" represents sample function sampling; "R" represents Put-back sampling

Details

If score="sign", then method_p must be "asymptotic". Three scoring systems can use the normal approximation but only "sign" can use binomial approximation. Namely, the argument method_asymptotic can be selected as "binomial" only if method_p="sign". And method_wilcoxon indicates the method to deal with ties. "type1" means ranking with zeros and "type2" means ranking without zeros.

Value

A list with following components

method

the test uesd

score

the score which is used

stat

the statistic of the data under the given scoring system

conf.int

the confidence interval for p-value(only if method_p = "sampling")

pval

p-value for the test

null.value

a character string describing the alternative hypothesis

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

x1=c(1530, 2130,2940,1960,2270)
x2=c(1290, 2250,2430,1900,2120)
pairwise_test(x1 , x2)
pairwise_test(x1 , x2 , method_p = "sampling" , samplenum = 4000)
pairwise_test(x1 , x2 , method_p = "asymptotic" , method_asymptotic = "norm")