hist.sim.power.ttest <- function(x, color.hline = "orange", ...){
iter <- x$SetUp$iter
alpha <- x$SetUp$sig.level
DF <- data.frame(pvalue = c(x$Classical$H1$pvalue,
x$Welch$H1$pvalue,
x$Hsu$H1$pvalue),
test = c(rep("Classical two-sample t-test", iter),
rep("Welch two-sample t-test", iter),
rep("Hsu two-sample t-test", iter)),
hypothesis = rep("H1", 3*iter))
if(!is.null(x$Classical$H0)){
DF1 <- data.frame(pvalue = c(x$Classical$H0$pvalue,
x$Welch$H0$pvalue,
x$Hsu$H0$pvalue),
test = c(rep("Classical two-sample t-test", iter),
rep("Welch two-sample t-test", iter),
rep("Hsu two-sample t-test", iter)),
hypothesis = rep("H0", 3*iter))
DF <- rbind(DF, DF1)
}
DF$test <- factor(DF$test, levels = c("Classical two-sample t-test",
"Welch two-sample t-test",
"Hsu two-sample t-test"))
if(!is.null(x$Classical$H0)){
Lab <- round(c(sum(x$Classical$H1$pvalue < alpha)/nrow(x$Classical$H1),
sum(x$Welch$H1$pvalue < alpha)/nrow(x$Welch$H1),
sum(x$Hsu$H1$pvalue < alpha)/nrow(x$Hsu$H1),
sum(x$Classical$H0$pvalue < alpha)/nrow(x$Classical$H0),
sum(x$Welch$H0$pvalue < alpha)/nrow(x$Welch$H0),
sum(x$Hsu$H0$pvalue < alpha)/nrow(x$Hsu$H0)), 4)
Lab[1:3] <- paste("emp. power:", Lab[1:3])
Lab[4:6] <- paste("emp. type-I-error:", Lab[4:6])
DF.text <- data.frame(test = rep(c("Classical two-sample t-test",
"Welch two-sample t-test",
"Hsu two-sample t-test"), 2),
hypothesis = c(rep("H1", 3), rep("H0", 3)),
label = Lab)
gg <- ggplot(data = DF, aes_string(x = "pvalue")) +
geom_histogram(aes_string(y = "after_stat(density)"), binwidth = 0.01) +
geom_hline(yintercept = 1.0, color = color.hline) + xlab("p value") +
geom_text(data = DF.text, aes_string(x = 0.5, y = Inf, label = "label"),
vjust = 2, inherit.aes = FALSE) +
facet_grid(hypothesis ~ test, scales = "free_y")
}else{
Lab <- round(c(sum(x$Classical$H1$pvalue < alpha)/nrow(x$Classical$H1),
sum(x$Welch$H1$pvalue < alpha)/nrow(x$Welch$H1),
sum(x$Hsu$H1$pvalue < alpha)/nrow(x$Hsu$H1)), 4)
Lab <- paste("emp. power:", Lab)
DF.text <- data.frame(test = c("Classical two-sample t-test",
"Welch two-sample t-test",
"Hsu two-sample t-test"),
hypothesis = rep("H1", 3),
label = Lab)
gg <- ggplot(data = DF, aes_string(x = "pvalue")) +
geom_histogram(aes_string(y = "after_stat(density)"), binwidth = 0.01) +
geom_text(data = DF.text, aes_string(x = 0.5, y = Inf, label = "label"),
vjust = 2, inherit.aes = FALSE) +
geom_hline(yintercept = 1.0, color = color.hline) + xlab("p value") +
facet_grid(~ test)
}
gg
}
hist.sim.power.wtest <- function(x, color.hline = "orange", ...){
iter <- x$SetUp$iter
sig.level <- x$SetUp$sig.level
approximate <- x$SetUp$approximate
if(approximate){
DF <- data.frame(pvalue = c(x$Exact$H1$pvalue,
x$Asymptotic$H1$pvalue,
x$Approximate$H1$pvalue),
test = c(rep("Exact Wilcoxon-Mann-Whitney test", iter),
rep("Asymptotic Wilcoxon-Mann-Whitney test", iter),
rep("Approximate Wilcoxon-Mann-Whitney test", iter)),
hypothesis = rep("H1", 3*iter))
}else{
DF <- data.frame(pvalue = c(x$Exact$H1$pvalue,
x$Asymptotic$H1$pvalue),
test = c(rep("Exact Wilcoxon-Mann-Whitney test", iter),
rep("Asymptotic Wilcoxon-Mann-Whitney test", iter)),
hypothesis = rep("H1", 2*iter))
}
if(!is.null(x$Exact$H0)){
if(approximate){
DF1 <- data.frame(pvalue = c(x$Exact$H0$pvalue,
x$Asymptotic$H0$pvalue,
x$Approximate$H0$pvalue),
test = c(rep("Exact Wilcoxon-Mann-Whitney test", iter),
rep("Asymptotic Wilcoxon-Mann-Whitney test", iter),
rep("Approximate Wilcoxon-Mann-Whitney test", iter)),
hypothesis = rep("H0", 3*iter))
}else{
DF1 <- data.frame(pvalue = c(x$Exact$H0$pvalue,
x$Asymptotic$H0$pvalue),
test = c(rep("Exact Wilcoxon-Mann-Whitney test", iter),
rep("Asymptotic Wilcoxon-Mann-Whitney test", iter)),
hypothesis = rep("H0", 2*iter))
}
DF <- rbind(DF, DF1)
}
if(approximate){
DF$test <- factor(DF$test, levels = c("Exact Wilcoxon-Mann-Whitney test",
"Asymptotic Wilcoxon-Mann-Whitney test",
"Approximate Wilcoxon-Mann-Whitney test"))
}else{
DF$test <- factor(DF$test, levels = c("Exact Wilcoxon-Mann-Whitney test",
"Asymptotic Wilcoxon-Mann-Whitney test"))
}
if(!is.null(x$Exact$H0)){
if(approximate){
Lab <- round(c(sum(x$Exact$H1$pvalue < sig.level)/iter,
sum(x$Asymptotic$H1$pvalue < sig.level)/iter,
sum(x$Approximate$H1$pvalue < sig.level)/iter,
sum(x$Exact$H0$pvalue < sig.level)/iter,
sum(x$Asymptotic$H0$pvalue < sig.level)/iter,
sum(x$Approximate$H0$pvalue < sig.level)/iter), 4)
Lab[1:3] <- paste("emp. power:", Lab[1:3])
Lab[4:6] <- paste("emp. type-I-error:", Lab[4:6])
DF.text <- data.frame(test = rep(c("Exact Wilcoxon-Mann-Whitney test",
"Asymptotic Wilcoxon-Mann-Whitney test",
"Approximate Wilcoxon-Mann-Whitney test"), 2),
hypothesis = c(rep("H1", 3), rep("H0", 3)),
label = Lab)
}else{
Lab <- round(c(sum(x$Exact$H1$pvalue < sig.level)/iter,
sum(x$Asymptotic$H1$pvalue < sig.level)/iter,
sum(x$Exact$H0$pvalue < sig.level)/iter,
sum(x$Asymptotic$H0$pvalue < sig.level)/iter), 4)
Lab[1:2] <- paste("emp. power:", Lab[1:2])
Lab[3:4] <- paste("emp. type-I-error:", Lab[3:4])
DF.text <- data.frame(test = rep(c("Exact Wilcoxon-Mann-Whitney test",
"Asymptotic Wilcoxon-Mann-Whitney test"), 2),
hypothesis = c(rep("H1", 2), rep("H0", 2)),
label = Lab)
}
gg <- ggplot(data = DF, aes_string(x = "pvalue")) +
geom_histogram(aes_string(y = "after_stat(density)"), binwidth = 0.01) +
geom_hline(yintercept = 1.0, color = color.hline) + xlab("p value") +
geom_text(data = DF.text, aes_string(x = 0.5, y = Inf, label = "label"),
vjust = 2, inherit.aes = FALSE) +
facet_grid(hypothesis ~ test, scales = "free_y")
}else{
if(approximate){
Lab <- round(c(sum(x$Exact$H1$pvalue < sig.level)/iter,
sum(x$Asymptotic$H1$pvalue < sig.level)/iter,
sum(x$Approxmiate$H1$pvalue < sig.level)/iter), 4)
Lab <- paste("emp. power:", Lab)
DF.text <- data.frame(test = c("Exact Wilcoxon-Mann-Whitney test",
"Asymptotic Wilcoxon-Mann-Whitney test",
"Approximate Wilcoxon-Mann-Whitney test"),
hypothesis = rep("H1", 3),
label = Lab)
}else{
Lab <- round(c(sum(x$Exact$H1$pvalue < sig.level)/iter,
sum(x$Asymptotic$H1$pvalue < sig.level)/iter), 4)
Lab <- paste("emp. power:", Lab)
DF.text <- data.frame(test = c("Exact Wilcoxon-Mann-Whitney test",
"Asymptotic Wilcoxon-Mann-Whitney test"),
hypothesis = rep("H1", 2),
label = Lab)
}
gg <- ggplot(data = DF, aes_string(x = "pvalue")) +
geom_histogram(aes_string(y = "after_stat(density)"), binwidth = 0.01) +
geom_text(data = DF.text, aes_string(x = 0.5, y = Inf, label = "label"),
vjust = 2, inherit.aes = FALSE) +
geom_hline(yintercept = 1.0, color = color.hline) + xlab("p value") +
facet_grid(~ test)
}
gg
}
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