r語言中如何進(jìn)行兩組獨(dú)立樣本秩和檢驗(yàn)?tecdat.cn

安裝所需的包

wants <- c("coin") has <- wants %in% rownames(installed.packages()) if(any(!has)) install.packages(wants[!has])>

一個樣本

測試

set.seed(123) medH0 <- 30 DV <- sample(0:100, 20, replace=TRUE) DV <- DV[DV != medH0] N <- length(DV) (obs <- sum(DV > medH0))

[1] 15

(pGreater <- 1-pbinom(obs-1, N, 0.5))

[1] 0.02069

(pTwoSided <- 2 * pGreater)

[1] 0.04139

威爾科克森排檢驗(yàn)

IQ <- c(99, 131, 118, 112, 128, 136, 120, 107, 134, 122) medH0 <- 110

wilcox.test(IQ, alternative="greater", mu=medH0, conf.int=TRUE)

Wilcoxon signed rank testdata: IQ V = 48, p-value = 0.01855 alternative hypothesis: true location is greater than 110 95 percent confidence interval:113.5 Inf sample estimates: (pseudo)median 121

兩個獨(dú)立樣本

測試

Nj <- c(20, 30) DVa <- rnorm(Nj[1], mean= 95, sd=15) DVb <- rnorm(Nj[2], mean=100, sd=15) wIndDf <- data.frame(DV=c(DVa, DVb), IV=factor(rep(1:2, Nj), labels=LETTERS[1:2]))

查看每組中低于或高于組合數(shù)據(jù)中位數(shù)的個案數(shù)。

library(coin) median_test(DV ~ IV, distribution="exact", data=wIndDf)

Exact Median Testdata: DV by IV (A, B) Z = 1.143, p-value = 0.3868 alternative hypothesis: true mu is not equal to 0

Wilcoxon秩和檢驗(yàn)（曼 - 惠特尼檢疫）

wilcox.test(DV ~ IV, alternative="less", conf.int=TRUE, data=wIndDf)

Wilcoxon rank sum testdata: DV by IV W = 202, p-value = 0.02647 alternative hypothesis: true location shift is less than 0 95 percent confidence interval:-Inf -1.771 sample estimates: difference in location -9.761

library(coin) wilcox_test(DV ~ IV, alternative="less", conf.int=TRUE, distribution="exact", data=wIndDf)

Exact Wilcoxon Mann-Whitney Rank Sum Testdata: DV by IV (A, B) Z = -1.941, p-value = 0.02647 alternative hypothesis: true mu is less than 0 95 percent confidence interval:-Inf -1.771 sample estimates: difference in location -9.761

兩個依賴樣本

測試

N <- 20 DVpre <- rnorm(N, mean= 95, sd=15) DVpost <- rnorm(N, mean=100, sd=15) wDepDf <- data.frame(id=factor(rep(1:N, times=2)), DV=c(DVpre, DVpost), IV=factor(rep(0:1, each=N), labels=c("pre", "post")))

medH0 <- 0 DVdiff <- aggregate(DV ~ id, FUN=diff, data=wDepDf) (obs <- sum(DVdiff$DV < medH0))

[1] 7

(pLess <- pbinom(obs, N, 0.5))

[1] 0.1316

排名威爾科克森檢驗(yàn)

wilcoxsign_test(DV ~ IV | id, alternative="greater", distribution="exact", data=wDepDf)

Exact Wilcoxon-Signed-Rank Testdata: y by x (neg, pos) stratified by block Z = 2.128, p-value = 0.01638 alternative hypothesis: true mu is greater than 0

分離（自動）加載的包

try(detach(package:coin)) try(detach(package:modeltools)) try(detach(package:survival)) try(detach(package:mvtnorm)) try(detach(package:splines)) try(detach(package:stats4))

總結(jié)

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