安装所需的包
wants <- c("coin") has <- wants %in% rownames(installed.packages()) if(any(!has)) install.packages(wants[!has])>
一个样本
测试
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威尔科克森排检验
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 两个独立样本
测试
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]))
查看每组中低于或高于组合数据中位数的个案数。
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秩和检验（曼 - 惠特尼检疫）
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 两个依赖样本
测试
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排名威尔科克森检验
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 分离（自动）加载的包
try(detach(package:coin)) try(detach(package:modeltools)) try(detach(package:survival)) try(detach(package:mvtnorm)) try(detach(package:splines)) try(detach(package:stats4))
