R Under development (unstable) (2018-03-28 r74482) -- "Unsuffered Consequences"
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> ### Regression tests for actual test size
>
> set.seed(290875)
> library("coin")
Loading required package: survival
> isequal <- coin:::isequal
> options(useFancyQuotes = FALSE)
>
>
> ### Berger and Ivanova (2001, p. 352, Tab 14.1)
> tab <- as.table(matrix(c(12, 3, 10, 19), ncol = 2))
>
> ### Berger and Ivanova (2001, p. 355, Tab 14.2)
> ct <- cmh_test(tab, distribution = "exact", alternative = "less",
+ scores = list(Var2 = 0:1))
> stopifnot(isequal(round(pvalue(ct), 4), 0.0049))
> stopifnot(isequal(round(size(ct, alpha = 0.05), 4), 0.0273))
>
> ### Additional results
> stopifnot(isequal(round(size(ct, alpha = 0.05, type = "mid-p-value"), 4), 0.0273))
>
> ct <- cmh_test(tab, distribution = "approximate", alternative = "less",
+ scores = list(Var2 = 0:1))
> stopifnot(isequal(round(pvalue(ct), 4), 0.0045))
> stopifnot(isequal(round(size(ct, alpha = 0.05), 4), 0.0254))
> stopifnot(isequal(round(size(ct, alpha = 0.05, type = "mid-p-value"), 4), 0.0254))
>
>
> ### Berger and Ivanova (2001, p. 358, Tab 14.3)
> tab <- as.table(matrix(c(12, 3, 3, 7, 7, 12), ncol = 3))
>
> ### Berger and Ivanova (2001, p. 360, Fig. 14.3, Fig 14.4)
> ct_0 <- cmh_test(tab, distribution = "exact", alternative = "less",
+ scores = list(Var2 = c(0, 0, 1)))
> stopifnot(isequal(round(pvalue(ct_0), 4), 0.1116))
> stopifnot(isequal(round(size(ct_0, alpha = 0.05), 4), 0.0333))
>
> ct_0.5 <- cmh_test(tab, distribution = "exact", alternative = "less",
+ scores = list(Var2 = c(0, 0.5, 1)))
> stopifnot(isequal(round(pvalue(ct_0.5), 4), 0.0126))
> stopifnot(isequal(round(size(ct_0.5, alpha = 0.05), 4), 0.0296))
>
> ct_1 <- cmh_test(tab, distribution = "exact", alternative = "less",
+ scores = list(Var2 = c(0, 1, 1)))
> stopifnot(isequal(round(pvalue(ct_1), 4), 0.0049))
> stopifnot(isequal(round(size(ct_1, alpha = 0.05), 4), 0.0273))
>
> ### Additional results
> stopifnot(isequal(round(size(ct_0, alpha = 0.05, type = "mid-p-value"), 4), 0.0333))
> stopifnot(isequal(round(size(ct_0.5, alpha = 0.05, type = "mid-p-value"), 4), 0.0619))
> stopifnot(isequal(round(size(ct_1, alpha = 0.05, type = "mid-p-value"), 4), 0.0273))
>
> ct_0 <- cmh_test(tab, distribution = "approximate", alternative = "less",
+ scores = list(Var2 = c(0, 0, 1)))
> stopifnot(isequal(round(pvalue(ct_0), 4), 0.1072))
> stopifnot(isequal(round(size(ct_0, alpha = 0.05), 4), 0.0315))
> stopifnot(isequal(round(size(ct_0, alpha = 0.05, type = "mid-p-value"), 4), 0.0315))
>
> ct_0.5 <- cmh_test(tab, distribution = "approximate", alternative = "less",
+ scores = list(Var2 = c(0, 0.5, 1)))
> stopifnot(isequal(round(pvalue(ct_0.5), 4), 0.0116))
> stopifnot(isequal(round(size(ct_0.5, alpha = 0.05), 4), 0.0307))
> stopifnot(isequal(round(size(ct_0.5, alpha = 0.05, type = "mid-p-value"), 4), 0.0614))
>
> ct_1 <- cmh_test(tab, distribution = "approximate", alternative = "less",
+ scores = list(Var2 = c(0, 1, 1)))
> stopifnot(isequal(round(pvalue(ct_1), 4), 0.0055))
> stopifnot(isequal(round(size(ct_1, alpha = 0.05), 4), 0.0263))
> stopifnot(isequal(round(size(ct_1, alpha = 0.05, type = "mid-p-value"), 4), 0.0263))
>
>
> ### Berger and Ivanova (2001, p. 364, Tab. 14.4)
> tab <- as.table(array(c(4, 0, 14, 19, 11, 1, 15, 25), dim = c(2, 2, 2)))
>
> ### Berger and Ivanova (2001, p. 367, Fig. 14.8)
> ct <- cmh_test(tab, distribution = "exact", alternative = "less",
+ scores = list(Var2 = 0:1))
> stopifnot(isequal(round(pvalue(ct), 4), 0.0001))
> stopifnot(isequal(round(size(ct, alpha = 0.05), 4), 0.0229))
>
> ### Additional results
> stopifnot(isequal(round(size(ct, alpha = 0.05, type = "mid-p-value"), 4), 0.0229))
>
> ct <- cmh_test(tab, distribution = "approximate", alternative = "less",
+ scores = list(Var2 = 0:1))
> stopifnot(isequal(round(pvalue(ct), 4), 0.0001))
> stopifnot(isequal(round(size(ct, alpha = 0.05), 4), 0.0229))
> stopifnot(isequal(round(size(ct, alpha = 0.05, type = "mid-p-value"), 4), 0.0749))
>
>
> ### Berger and Ivanova (2002, p. 269)
> tab <- as.table(matrix(c(11, 7, 2, 7, 2, 6), ncol = 3))
>
> ### Berger and Ivanova (2002, p. 277, Tab. 14.2, last line, first line)
> ct_0 <- cmh_test(tab, distribution = "exact", alternative = "less",
+ scores = list(Var2 = c(0, 0, 1)))
> stopifnot(isequal(round(pvalue(ct_0), 3), 0.228))
> stopifnot(isequal(round(size(ct_0, alpha = 0.05), 3), 0.005))
>
> ct_0.5 <- cmh_test(tab, distribution = "exact", alternative = "less",
+ scores = list(Var2 = c(0, 0.5, 1)))
> stopifnot(isequal(round(pvalue(ct_0.5), 3), 0.038))
> stopifnot(isequal(round(size(ct_0.5, alpha = 0.05), 3), 0.038))
>
> ct_1 <- cmh_test(tab, distribution = "exact", alternative = "less",
+ scores = list(Var2 = c(0, 1, 1)))
> stopifnot(isequal(round(pvalue(ct_1), 3), 0.028))
> stopifnot(isequal(round(size(ct_1, alpha = 0.05), 3), 0.028))
>
> ### Additional results
> stopifnot(isequal(round(size(ct_0, alpha = 0.05, type = "mid-p-value"), 3), 0.055))
> stopifnot(isequal(round(size(ct_0.5, alpha = 0.05, type = "mid-p-value"), 3), 0.038))
> stopifnot(isequal(round(size(ct_1, alpha = 0.05, type = "mid-p-value"), 3), 0.028))
>
> ct_0 <- cmh_test(tab, distribution = "approximate", alternative = "less",
+ scores = list(Var2 = c(0, 0, 1)))
> stopifnot(isequal(round(pvalue(ct_0), 3), 0.233))
> stopifnot(isequal(round(size(ct_0, alpha = 0.05), 3), 0.006))
> stopifnot(isequal(round(size(ct_0, alpha = 0.05, type = "mid-p-value"), 3), 0.058))
>
> ct_0.5 <- cmh_test(tab, distribution = "approximate", alternative = "less",
+ scores = list(Var2 = c(0, 0.5, 1)))
> stopifnot(isequal(round(pvalue(ct_0.5), 3), 0.039))
> stopifnot(isequal(round(size(ct_0.5, alpha = 0.05), 3), 0.039))
> stopifnot(isequal(round(size(ct_0.5, alpha = 0.05, type = "mid-p-value"), 3), 0.039))
>
> ct_1 <- cmh_test(tab, distribution = "approximate", alternative = "less",
+ scores = list(Var2 = c(0, 1, 1)))
> stopifnot(isequal(round(pvalue(ct_1), 3), 0.027))
> stopifnot(isequal(round(size(ct_1, alpha = 0.05), 3), 0.027))
> stopifnot(isequal(round(size(ct_1, alpha = 0.05, type = "mid-p-value"), 3), 0.027))
>
>
> ### Neuhäuser (2012, p. 30, Tab. 2.7)
> y_1 <- rnorm(10); x_1 <- factor(rep(1:2, c(5, 5)))
> y_2 <- rnorm(12); x_2 <- factor(rep(1:2, c(6, 6)))
> y_3 <- rnorm(14); x_3 <- factor(rep(1:2, c(7, 7)))
> y_4 <- rnorm(16); x_4 <- factor(rep(1:2, c(8, 8)))
> y_5 <- rnorm(18); x_5 <- factor(rep(1:2, c(9, 9)))
> y_6 <- rnorm(20); x_6 <- factor(rep(1:2, c(10, 10)))
> y_7 <- rnorm(13); x_7 <- factor(rep(1:2, c(8, 5)))
> y_8 <- rnorm(16); x_8 <- factor(rep(1:2, c(9, 7)))
> y_9 <- rnorm(15); x_9 <- factor(rep(1:2, c(10, 5)))
>
> wt_1 <- wilcox_test(y_1 ~ x_1, distribution = "exact")
> stopifnot(isequal(round(size(wt_1, alpha = 0.05), 4), 0.0317))
>
> wt_2 <- wilcox_test(y_2 ~ x_2, distribution = "exact")
> stopifnot(isequal(round(size(wt_2, alpha = 0.05), 4), 0.0411))
>
> wt_3 <- wilcox_test(y_3 ~ x_3, distribution = "exact")
> stopifnot(isequal(round(size(wt_3, alpha = 0.05), 4), 0.0379))
>
> wt_4 <- wilcox_test(y_4 ~ x_4, distribution = "exact")
> stopifnot(isequal(round(size(wt_4, alpha = 0.05), 4), 0.0499))
>
> wt_5 <- wilcox_test(y_5 ~ x_5, distribution = "exact")
> stopifnot(isequal(round(size(wt_5, alpha = 0.05), 4), 0.0400))
>
> wt_6 <- wilcox_test(y_6 ~ x_6, distribution = "exact")
> stopifnot(isequal(round(size(wt_6, alpha = 0.05), 4), 0.0433))
>
> wt_7 <- wilcox_test(y_7 ~ x_7, distribution = "exact")
> stopifnot(isequal(round(size(wt_7, alpha = 0.05), 4), 0.0451))
>
> wt_8 <- wilcox_test(y_8 ~ x_8, distribution = "exact")
> stopifnot(isequal(round(size(wt_8, alpha = 0.05), 4), 0.0418))
>
> wt_9 <- wilcox_test(y_9 ~ x_9, distribution = "exact")
> stopifnot(isequal(round(size(wt_9, alpha = 0.05), 4), 0.0400))
>
> ### Additional results
> stopifnot(isequal(round(size(wt_1, alpha = 0.05, type = "mid-p-value"), 4), 0.0556))
> stopifnot(isequal(round(size(wt_2, alpha = 0.05, type = "mid-p-value"), 4), 0.0411))
> stopifnot(isequal(round(size(wt_3, alpha = 0.05, type = "mid-p-value"), 4), 0.0530))
> stopifnot(isequal(round(size(wt_4, alpha = 0.05, type = "mid-p-value"), 4), 0.0499))
> stopifnot(isequal(round(size(wt_5, alpha = 0.05, type = "mid-p-value"), 4), 0.0503))
> stopifnot(isequal(round(size(wt_6, alpha = 0.05, type = "mid-p-value"), 4), 0.0524))
> stopifnot(isequal(round(size(wt_7, alpha = 0.05, type = "mid-p-value"), 4), 0.0451))
> stopifnot(isequal(round(size(wt_8, alpha = 0.05, type = "mid-p-value"), 4), 0.0549))
> stopifnot(isequal(round(size(wt_9, alpha = 0.05, type = "mid-p-value"), 4), 0.0553))
>
> wt_1 <- wilcox_test(y_1 ~ x_1, distribution = "approximate")
> stopifnot(isequal(round(size(wt_1, alpha = 0.05), 4), 0.0353))
> stopifnot(isequal(round(size(wt_1, alpha = 0.05, type = "mid-p-value"), 4), 0.0582))
>
> wt_2 <- wilcox_test(y_2 ~ x_2, distribution = "approximate")
> stopifnot(isequal(round(size(wt_2, alpha = 0.05), 4), 0.0388))
> stopifnot(isequal(round(size(wt_2, alpha = 0.05, type = "mid-p-value"), 4), 0.0388))
>
> wt_3 <- wilcox_test(y_3 ~ x_3, distribution = "approximate")
> stopifnot(isequal(round(size(wt_3, alpha = 0.05), 4), 0.0386))
> stopifnot(isequal(round(size(wt_3, alpha = 0.05, type = "mid-p-value"), 4), 0.0530))
>
> wt_4 <- wilcox_test(y_4 ~ x_4, distribution = "approximate")
> stopifnot(isequal(round(size(wt_4, alpha = 0.05), 4), 0.0373))
> stopifnot(isequal(round(size(wt_4, alpha = 0.05, type = "mid-p-value"), 4), 0.0508))
>
> wt_5 <- wilcox_test(y_5 ~ x_5, distribution = "approximate")
> stopifnot(isequal(round(size(wt_5, alpha = 0.05), 4), 0.0498))
> stopifnot(isequal(round(size(wt_5, alpha = 0.05, type = "mid-p-value"), 4), 0.0498))
>
> wt_6 <- wilcox_test(y_6 ~ x_6, distribution = "approximate")
> stopifnot(isequal(round(size(wt_6, alpha = 0.05), 4), 0.0477))
> stopifnot(isequal(round(size(wt_6, alpha = 0.05, type = "mid-p-value"), 4), 0.0477))
>
> wt_7 <- wilcox_test(y_7 ~ x_7, distribution = "approximate")
> stopifnot(isequal(round(size(wt_7, alpha = 0.05), 4), 0.0414))
> stopifnot(isequal(round(size(wt_7, alpha = 0.05, type = "mid-p-value"), 4), 0.0414))
>
> wt_8 <- wilcox_test(y_8 ~ x_8, distribution = "approximate")
> stopifnot(isequal(round(size(wt_8, alpha = 0.05), 4), 0.0438))
> stopifnot(isequal(round(size(wt_8, alpha = 0.05, type = "mid-p-value"), 4), 0.0438))
>
> wt_9 <- wilcox_test(y_9 ~ x_9, distribution = "approximate")
> stopifnot(isequal(round(size(wt_9, alpha = 0.05), 4), 0.0402))
> stopifnot(isequal(round(size(wt_9, alpha = 0.05, type = "mid-p-value"), 4), 0.0549))
>
> proc.time()
user system elapsed
1.42 0.12 1.53
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