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Type 'q()' to quit R. > ### 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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