### Regression tests for mid-p confidence intervals and mid-p-values set.seed(290875) library("coin") isequal <- coin:::isequal options(useFancyQuotes = FALSE) ### ### Mid-p confidence intervals ### ### Berry and Armitage (1995, p. 420) mpci <- coin:::confint_binom(5, 20, level = 0.95, method = "mid-p") stopifnot(isequal(round(mpci, 3), c(0.098, 0.470))) ### Agresti and Gottard (2001, p. 369) mpci <- coin:::confint_binom(4, 10, level = 0.95, method = "mid-p") stopifnot(isequal(round(mpci, 3), c(0.142, 0.709))) mpci <- coin:::confint_binom(0, 10, level = 0.95, method = "mid-p") stopifnot(isequal(round(mpci[1], 3), 0)) mpci <- coin:::confint_binom(10, 10, level = 0.95, method = "mid-p") stopifnot(isequal(round(mpci[2], 3), 1)) ### Newcombe (1998, p. 861, Tab. I) mpci <- coin:::confint_binom(81, 263, level = 0.95, method = "mid-p") stopifnot(isequal(round(mpci, 4), c(0.2544, 0.3658))) mpci <- coin:::confint_binom(15, 148, level = 0.95, method = "mid-p") stopifnot(isequal(round(mpci, 4), c(0.0601, 0.1581))) mpci <- coin:::confint_binom(0, 20, level = 0.95, method = "mid-p") stopifnot(isequal(round(mpci, 4), c(0.0000, 0.1391))) mpci <- coin:::confint_binom(1, 29, level = 0.95, method = "mid-p") stopifnot(isequal(round(mpci, 4), c(0.0017, 0.1585))) ### ### Mid-p-pvalues ### ### Data from Hwang and Yang (2001, p. 810) tea <- matrix(c(3, 1, 1, 3), nrow = 2, byrow = TRUE) ### Results from Hwang and Yang (2001, p. 810) ct_e <- chisq_test(as.table(tea), distribution = "exact") stopifnot(isequal(round(pvalue(ct_e), 3), 0.486)) stopifnot(isequal(round(midpvalue(ct_e), 3), 0.257)) it_e_s <- independence_test(as.table(tea), distribution = "exact", teststat = "scalar") stopifnot(isequal(pvalue(it_e_s), pvalue(ct_e))) stopifnot(isequal(midpvalue(it_e_s), midpvalue(ct_e))) it_e_q <- independence_test(as.table(tea), distribution = "exact", teststat = "quad") stopifnot(isequal(pvalue(it_e_q), pvalue(ct_e))) stopifnot(isequal(midpvalue(it_e_q), midpvalue(ct_e))) it_e_s_gr <- independence_test(as.table(tea), distribution = "exact", teststat = "scalar", alternative = "greater") stopifnot(isequal(round(pvalue(it_e_s_gr), 3), 0.243)) stopifnot(isequal(round(midpvalue(it_e_s_gr), 4), 0.1286)) # p = 0.1285 according to Hwang and Yang (2001) ### Additional results: Monte Carlo set.seed(290875) ct_m <- chisq_test(as.table(tea), distribution = "approximate") (p <- pvalue(ct_m)) pci <- attr(p, "conf.int") stopifnot(pci[1] < 0.486 & pci[2] > 0.486) (mp <- midpvalue(ct_m)) mpci <- attr(mp, "conf.int") stopifnot(mpci[1] < 0.257 & mpci[2] > 0.257) set.seed(290875) it_m_s <- independence_test(as.table(tea), distribution = approximate(nresample = 10000), teststat = "scalar") stopifnot(isequal(pvalue(it_m_s), pvalue(ct_m))) stopifnot(isequal(midpvalue(it_m_s), midpvalue(ct_m))) set.seed(290875) it_m_q <- independence_test(as.table(tea), distribution = approximate(nresample = 10000), teststat = "quad") stopifnot(isequal(pvalue(it_m_q), pvalue(ct_m))) stopifnot(isequal(midpvalue(it_m_q), midpvalue(ct_m))) set.seed(290875) it_m_s_gr <- independence_test(as.table(tea), distribution = approximate(nresample = 10000), teststat = "scalar", alternative = "greater") (p <- pvalue(it_m_s_gr)) pci <- attr(p, "conf.int") stopifnot(pci[1] < 0.243 & pci[2] > 0.243) (mp <- midpvalue(it_m_s_gr)) mpci <- attr(mp, "conf.int") stopifnot(mpci[1] < 0.1286 & mpci[2] > 0.1286) ### Data from Lydersen and Laake (2003, p. 3862) davis <- matrix(c(3, 6, 2, 19), nrow = 2, byrow = TRUE) ### Results from Lydersen and Laake (2003, p. 3863, Tab. II) ct_e <- chisq_test(as.table(davis), distribution = "exact") stopifnot(isequal(round(pvalue(ct_e), 4), 0.2860)) stopifnot(isequal(round(midpvalue(ct_e), 4), 0.1527)) it_e_s <- independence_test(as.table(davis), distribution = "exact", teststat = "scalar") stopifnot(isequal(pvalue(it_e_s), pvalue(ct_e))) stopifnot(isequal(midpvalue(it_e_s), midpvalue(ct_e))) it_e_q <- independence_test(as.table(davis), distribution = "exact", teststat = "quad") stopifnot(isequal(pvalue(it_e_q), pvalue(ct_e))) stopifnot(isequal(midpvalue(it_e_q), midpvalue(ct_e))) ### Additional results: Monte Carlo set.seed(290875) ct_m <- chisq_test(as.table(davis), distribution = "approximate") (p <- pvalue(ct_m)) pci <- attr(p, "conf.int") stopifnot(pci[1] < 0.2860 & pci[2] > 0.2860) (mp <- midpvalue(ct_m)) mpci <- attr(mp, "conf.int") stopifnot(mpci[1] < 0.1527 & mpci[2] > 0.1527) set.seed(290875) it_m_s <- independence_test(as.table(davis), distribution = approximate(nresample = 10000), teststat = "scalar") stopifnot(isequal(pvalue(it_m_s), pvalue(ct_m))) stopifnot(isequal(midpvalue(it_m_s), midpvalue(ct_m))) set.seed(290875) it_m_q <- independence_test(as.table(davis), distribution = approximate(nresample = 10000), teststat = "quad") stopifnot(isequal(pvalue(it_m_q), pvalue(ct_m))) stopifnot(isequal(midpvalue(it_m_q), midpvalue(ct_m))) ### Data from Lydersen, Fagerland and Laake (2009, p. 1160, Tab. I) cardiac <- matrix(c(1, 33, 7, 27), nrow = 2, byrow = TRUE) ### Results from Lydersen, Fagerland and Laake (2009, pp. 1171--1172) ct_e <- chisq_test(as.table(cardiac), distribution = "exact") stopifnot(isequal(round(pvalue(ct_e), 4), 0.0544)) stopifnot(isequal(round(midpvalue(ct_e), 4), 0.0297)) it_e_s <- independence_test(as.table(cardiac), distribution = "exact", teststat = "scalar") stopifnot(isequal(pvalue(it_e_s), pvalue(ct_e))) stopifnot(isequal(midpvalue(it_e_s), midpvalue(ct_e))) it_e_q <- independence_test(as.table(cardiac), distribution = "exact", teststat = "quad") stopifnot(isequal(pvalue(it_e_q), pvalue(ct_e))) stopifnot(isequal(midpvalue(it_e_q), midpvalue(ct_e))) ### Additional results: Monte Carlo set.seed(290875) ct_m <- chisq_test(as.table(cardiac), distribution = approximate(nresample = 10000)) (p <- pvalue(ct_m)) pci <- attr(p, "conf.int") stopifnot(pci[1] < 0.0544 & pci[2] > 0.0544) (mp <- midpvalue(ct_m)) mpci <- attr(mp, "conf.int") stopifnot(mpci[1] < 0.0297 & mpci[2] > 0.0297) set.seed(290875) it_m_s <- independence_test(as.table(cardiac), distribution = approximate(nresample = 10000), teststat = "scalar") stopifnot(isequal(pvalue(it_m_s), pvalue(ct_m))) stopifnot(isequal(midpvalue(it_m_s), midpvalue(ct_m))) set.seed(290875) it_m_q <- independence_test(as.table(cardiac), distribution = approximate(nresample = 10000), teststat = "quad") stopifnot(isequal(pvalue(it_m_q), pvalue(ct_m))) stopifnot(isequal(midpvalue(it_m_q), midpvalue(ct_m))) ### Data from Lydersen, Fagerland and Laake (2009, p. 1160, Tab. II) exfoliative <- matrix(c( 0, 16, 15, 57), nrow = 2, byrow = TRUE) ### Results from Lydersen, Fagerland and Laake (2009, p. 1173) ct_e <- chisq_test(as.table(exfoliative), distribution = "exact") stopifnot(isequal(round(pvalue(ct_e), 4), 0.0629)) stopifnot(isequal(round(midpvalue(ct_e), 4), 0.0447)) it_e_s <- independence_test(as.table(exfoliative), distribution = "exact", teststat = "scalar") stopifnot(isequal(pvalue(it_e_s), pvalue(ct_e))) stopifnot(isequal(midpvalue(it_e_s), midpvalue(ct_e))) it_e_q <- independence_test(as.table(exfoliative), distribution = "exact", teststat = "quad") stopifnot(isequal(pvalue(it_e_q), pvalue(ct_e))) stopifnot(isequal(midpvalue(it_e_q), midpvalue(ct_e))) ### Additional results: Monte Carlo set.seed(290875) ct_m <- chisq_test(as.table(exfoliative), distribution = approximate(nresample = 10000)) (p <- pvalue(ct_m)) pci <- attr(p, "conf.int") stopifnot(pci[1] < 0.0629 & pci[2] > 0.0629) (mp <- midpvalue(ct_m)) mpci <- attr(mp, "conf.int") stopifnot(mpci[1] < 0.0447 & mpci[2] > 0.0447) set.seed(290875) it_m_s <- independence_test(as.table(exfoliative), distribution = approximate(nresample = 10000), teststat = "scalar") stopifnot(isequal(pvalue(it_m_s), pvalue(ct_m))) stopifnot(isequal(midpvalue(it_m_s), midpvalue(ct_m))) set.seed(290875) it_m_q <- independence_test(as.table(exfoliative), distribution = approximate(nresample = 10000), teststat = "quad") stopifnot(isequal(pvalue(it_m_q), pvalue(ct_m))) stopifnot(isequal(midpvalue(it_m_q), midpvalue(ct_m))) ### Data from Fagerland, Lydersen and Laake (2013, p. 2, Tab. 1) ahr <- matrix(c(1, 1, 7, 12), nrow = 2, byrow = TRUE) ### Results from Fagerland, Lydersen and Laake (2013, p. 7, Tab. 6) mt_e <- mh_test(as.table(ahr), distribution = "exact") stopifnot(isequal(round(pvalue(mt_e), 4), 0.0703)) stopifnot(isequal(round(midpvalue(mt_e), 4), 0.0391)) st_e_s <- symmetry_test(as.table(ahr), distribution = "exact", teststat = "scalar") stopifnot(isequal(pvalue(st_e_s), pvalue(mt_e))) stopifnot(isequal(midpvalue(st_e_s), midpvalue(mt_e))) st_e_q <- symmetry_test(as.table(ahr), distribution = "exact", teststat = "quad") stopifnot(isequal(pvalue(st_e_q), pvalue(mt_e))) stopifnot(isequal(midpvalue(st_e_q), midpvalue(mt_e))) ### Additional results: Monte Carlo set.seed(290875) mt_m <- mh_test(as.table(ahr), distribution = approximate(nresample = 10000)) (p <- pvalue(mt_m)) pci <- attr(p, "conf.int") stopifnot(pci[1] < 0.0703 & pci[2] > 0.0703) (mp <- midpvalue(mt_m)) mpci <- attr(mp, "conf.int") stopifnot(mpci[1] < 0.0391 & mpci[2] > 0.0391) set.seed(290875) st_m_s <- symmetry_test(as.table(ahr), distribution = approximate(nresample = 10000), teststat = "scalar") stopifnot(isequal(pvalue(st_m_s), pvalue(mt_m))) stopifnot(isequal(midpvalue(st_m_s), midpvalue(mt_m))) set.seed(290875) st_m_q <- symmetry_test(as.table(ahr), distribution = approximate(nresample = 10000), teststat = "quad") stopifnot(isequal(pvalue(st_m_q), pvalue(mt_m))) stopifnot(isequal(midpvalue(st_m_q), midpvalue(mt_m))) ### Data from Fagerland, Lydersen and Laake (2013, p. 2, Tab. 2) therapy <- matrix(c(59, 6, 16, 80), nrow = 2, byrow = TRUE) ### Results from Fagerland, Lydersen and Laake (2013, p. 7, Tab. 6) mt_e <- mh_test(as.table(therapy), distribution = "exact") stopifnot(isequal(round(pvalue(mt_e), 4), 0.0525)) stopifnot(isequal(round(midpvalue(mt_e), 4), 0.0347)) st_e_s <- symmetry_test(as.table(therapy), distribution = "exact", teststat = "scalar") stopifnot(isequal(pvalue(st_e_s), pvalue(mt_e))) stopifnot(isequal(midpvalue(st_e_s), midpvalue(mt_e))) st_e_q <- symmetry_test(as.table(therapy), distribution = "exact", teststat = "quad") stopifnot(isequal(pvalue(st_e_q), pvalue(mt_e))) stopifnot(isequal(midpvalue(st_e_q), midpvalue(mt_e))) ### Additional results: Monte Carlo set.seed(290875) mt_m <- mh_test(as.table(therapy), distribution = approximate(nresample = 10000)) (p <- pvalue(mt_m)) pci <- attr(p, "conf.int") stopifnot(pci[1] < 0.0525 & pci[2] > 0.0525) (mp <- midpvalue(mt_m)) mpci <- attr(mp, "conf.int") stopifnot(mpci[1] < 0.0347 & mpci[2] > 0.0347) set.seed(290875) st_m_s <- symmetry_test(as.table(therapy), distribution = approximate(nresample = 10000), teststat = "scalar") stopifnot(isequal(pvalue(st_m_s), pvalue(mt_m))) stopifnot(isequal(midpvalue(st_m_s), midpvalue(mt_m))) set.seed(290875) st_m_q <- symmetry_test(as.table(therapy), distribution = approximate(nresample = 10000), teststat = "quad") stopifnot(isequal(pvalue(st_m_q), pvalue(mt_m))) stopifnot(isequal(midpvalue(st_m_q), midpvalue(mt_m))) ### Data from Barnard (1989, p. 1470) barnard50 <- matrix(c(5, 0, 0, 5), nrow = 2, byrow = TRUE) barnard51 <- matrix(c(5, 0, 1, 4), nrow = 2, byrow = TRUE) barnard52 <- matrix(c(5, 0, 2, 3), nrow = 2, byrow = TRUE) barnard53 <- matrix(c(5, 0, 3, 2), nrow = 2, byrow = TRUE) barnard54 <- matrix(c(5, 0, 4, 1), nrow = 2, byrow = TRUE) ## barnard55 <- matrix(c(5, 0, ## 5, 0), ## nrow = 2, byrow = TRUE) barnard40 <- matrix(c(4, 1, 0, 5), nrow = 2, byrow = TRUE) barnard41 <- matrix(c(4, 1, 1, 4), nrow = 2, byrow = TRUE) barnard42 <- matrix(c(4, 1, 2, 3), nrow = 2, byrow = TRUE) barnard43 <- matrix(c(4, 1, 3, 2), nrow = 2, byrow = TRUE) barnard44 <- matrix(c(4, 1, 4, 1), nrow = 2, byrow = TRUE) barnard45 <- matrix(c(4, 1, 5, 0), nrow = 2, byrow = TRUE) barnard30 <- matrix(c(3, 2, 0, 5), nrow = 2, byrow = TRUE) barnard31 <- matrix(c(3, 2, 1, 4), nrow = 2, byrow = TRUE) barnard32 <- matrix(c(3, 2, 2, 3), nrow = 2, byrow = TRUE) barnard33 <- matrix(c(3, 2, 3, 2), nrow = 2, byrow = TRUE) barnard34 <- matrix(c(3, 2, 4, 1), nrow = 2, byrow = TRUE) barnard35 <- matrix(c(3, 2, 5, 0), nrow = 2, byrow = TRUE) barnard20 <- matrix(c(2, 3, 0, 5), nrow = 2, byrow = TRUE) barnard21 <- matrix(c(2, 3, 1, 4), nrow = 2, byrow = TRUE) barnard22 <- matrix(c(2, 3, 2, 3), nrow = 2, byrow = TRUE) barnard23 <- matrix(c(2, 3, 3, 2), nrow = 2, byrow = TRUE) barnard24 <- matrix(c(2, 3, 4, 1), nrow = 2, byrow = TRUE) barnard25 <- matrix(c(2, 3, 5, 0), nrow = 2, byrow = TRUE) barnard10 <- matrix(c(1, 4, 0, 5), nrow = 2, byrow = TRUE) barnard11 <- matrix(c(1, 4, 1, 4), nrow = 2, byrow = TRUE) barnard12 <- matrix(c(1, 4, 2, 3), nrow = 2, byrow = TRUE) barnard13 <- matrix(c(1, 4, 3, 2), nrow = 2, byrow = TRUE) barnard14 <- matrix(c(1, 4, 4, 1), nrow = 2, byrow = TRUE) barnard15 <- matrix(c(1, 4, 5, 0), nrow = 2, byrow = TRUE) ## barnard00 <- matrix(c(0, 5, ## 0, 5), ## nrow = 2, byrow = TRUE) barnard01 <- matrix(c(0, 5, 1, 4), nrow = 2, byrow = TRUE) barnard02 <- matrix(c(0, 5, 2, 3), nrow = 2, byrow = TRUE) barnard03 <- matrix(c(0, 5, 3, 2), nrow = 2, byrow = TRUE) barnard04 <- matrix(c(0, 5, 4, 1), nrow = 2, byrow = TRUE) barnard05 <- matrix(c(0, 5, 5, 0), nrow = 2, byrow = TRUE) ### Results from Barnard (1989, p. 1471, Tab. III; p. 1474, Tab. IV) it50_e <- independence_test(as.table(barnard50), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it50_e), 4), 0.0040)) stopifnot(isequal(round(midpvalue(it50_e), 4), 0.0020)) it51_e <- independence_test(as.table(barnard51), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it51_e), 4), 0.0238)) stopifnot(isequal(round(midpvalue(it51_e), 4), 0.0119)) it52_e <- independence_test(as.table(barnard52), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it52_e), 4), 0.0833)) stopifnot(isequal(round(midpvalue(it52_e), 4), 0.0417)) it53_e <- independence_test(as.table(barnard53), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it53_e), 4), 0.2222)) stopifnot(isequal(round(midpvalue(it53_e), 4), 0.1111)) it54_e <- independence_test(as.table(barnard54), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it54_e), 4), 0.5000)) stopifnot(isequal(round(midpvalue(it54_e), 4), 0.2500)) ## it55_e <- independence_test(as.table(barnard55), ## distribution = "exact", ## alternative = "greater") ## stopifnot(isequal(round(pvalue(it55_e), 4), 1.0000)) ## stopifnot(isequal(round(midpvalue(it55_e), 4), 0.5000)) it40_e <- independence_test(as.table(barnard40), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it40_e), 4), 0.0238)) stopifnot(isequal(round(midpvalue(it40_e), 4), 0.0119)) it41_e <- independence_test(as.table(barnard41), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it41_e), 4), 0.1032)) stopifnot(isequal(round(midpvalue(it41_e), 4), 0.0536)) it42_e <- independence_test(as.table(barnard42), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it42_e), 4), 0.2619)) stopifnot(isequal(round(midpvalue(it42_e), 4), 0.1429)) it43_e <- independence_test(as.table(barnard43), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it43_e), 4), 0.5000)) stopifnot(isequal(round(midpvalue(it43_e), 4), 0.2917)) it44_e <- independence_test(as.table(barnard44), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it44_e), 4), 0.7778)) stopifnot(isequal(round(midpvalue(it44_e), 4), 0.5000)) it45_e <- independence_test(as.table(barnard45), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it45_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it45_e), 4), 0.7500)) it30_e <- independence_test(as.table(barnard30), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it30_e), 4), 0.0833)) stopifnot(isequal(round(midpvalue(it30_e), 4), 0.0417)) it31_e <- independence_test(as.table(barnard31), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it31_e), 4), 0.2619)) stopifnot(isequal(round(midpvalue(it31_e), 4), 0.1429)) it32_e <- independence_test(as.table(barnard32), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it32_e), 4), 0.5000)) stopifnot(isequal(round(midpvalue(it32_e), 4), 0.3016)) it33_e <- independence_test(as.table(barnard33), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it33_e), 4), 0.7381)) stopifnot(isequal(round(midpvalue(it33_e), 4), 0.5000)) it34_e <- independence_test(as.table(barnard34), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it34_e), 4), 0.9167)) stopifnot(isequal(round(midpvalue(it34_e), 4), 0.7083)) it35_e <- independence_test(as.table(barnard35), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it35_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it35_e), 4), 0.8889)) it20_e <- independence_test(as.table(barnard20), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it20_e), 4), 0.2222)) stopifnot(isequal(round(midpvalue(it20_e), 4), 0.1111)) it21_e <- independence_test(as.table(barnard21), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it21_e), 4), 0.5000)) stopifnot(isequal(round(midpvalue(it21_e), 4), 0.2917)) it22_e <- independence_test(as.table(barnard22), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it22_e), 4), 0.7381)) stopifnot(isequal(round(midpvalue(it22_e), 4), 0.5000)) it23_e <- independence_test(as.table(barnard23), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it23_e), 4), 0.8968)) stopifnot(isequal(round(midpvalue(it23_e), 4), 0.6984)) it24_e <- independence_test(as.table(barnard24), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it24_e), 4), 0.9762)) stopifnot(isequal(round(midpvalue(it24_e), 4), 0.8571)) it25_e <- independence_test(as.table(barnard25), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it25_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it25_e), 4), 0.9583)) it10_e <- independence_test(as.table(barnard10), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it10_e), 4), 0.5000)) stopifnot(isequal(round(midpvalue(it10_e), 4), 0.2500)) it11_e <- independence_test(as.table(barnard11), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it11_e), 4), 0.7778)) stopifnot(isequal(round(midpvalue(it11_e), 4), 0.5000)) it12_e <- independence_test(as.table(barnard12), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it12_e), 4), 0.9167)) stopifnot(isequal(round(midpvalue(it12_e), 4), 0.7083)) it13_e <- independence_test(as.table(barnard13), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it13_e), 4), 0.9762)) stopifnot(isequal(round(midpvalue(it13_e), 4), 0.8571)) it14_e <- independence_test(as.table(barnard14), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it14_e), 4), 0.9960)) stopifnot(isequal(round(midpvalue(it14_e), 4), 0.9464)) it15_e <- independence_test(as.table(barnard15), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it15_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it15_e), 4), 0.9881)) ## it00_e <- independence_test(as.table(barnard00), ## distribution = "exact", ## alternative = "greater") ## stopifnot(isequal(round(pvalue(it00_e), 4), 1.0000)) ## stopifnot(isequal(round(midpvalue(it00_e), 4), 0.5000)) it01_e <- independence_test(as.table(barnard01), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it01_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it01_e), 4), 0.7500)) it02_e <- independence_test(as.table(barnard02), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it02_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it02_e), 4), 0.8889)) it03_e <- independence_test(as.table(barnard03), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it03_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it03_e), 4), 0.9583)) it04_e <- independence_test(as.table(barnard04), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it04_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it04_e), 4), 0.9881)) it05_e <- independence_test(as.table(barnard05), distribution = "exact", alternative = "greater") stopifnot(isequal(round(pvalue(it05_e), 4), 1.0000)) stopifnot(isequal(round(midpvalue(it05_e), 4), 0.9980))
Generated by dwww version 1.15 on Sun Jun 16 16:23:51 CEST 2024.