原文链接
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)
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Wilcoxon signed rank test
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data: IQ
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V = 48, p-value = 0.01855
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alternative hypothesis: true location is greater than 110
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95 percent confidence interval:
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113.5 Inf
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sample estimates:
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(pseudo)median
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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)
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Exact Median Test
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data: DV by IV (A, B)
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Z = 1.143, p-value = 0.3868
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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)
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Wilcoxon rank sum test
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data: DV by IV
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W = 202, p-value = 0.02647
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alternative hypothesis: true location shift is less than 0
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95 percent confidence interval:
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-Inf -1.771
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sample estimates:
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difference in location
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-9.761
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library(coin)
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wilcox_test(DV ~ IV, alternative="less", conf.int=TRUE,
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distribution="exact", data=wIndDf)
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Exact Wilcoxon Mann-Whitney Rank Sum Test
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data: DV by IV (A, B)
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Z = -1.941, p-value = 0.02647
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alternative hypothesis: true mu is less than 0
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95 percent confidence interval:
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-Inf -1.771
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sample estimates:
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difference in location
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-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)
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Exact Wilcoxon-Signed-Rank Test
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data: y by x (neg, pos)
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stratified by block
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Z = 2.128, p-value = 0.01638
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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))