R Under development (unstable) (2018-08-14 r75146) -- "Unsuffered Consequences"
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> ### Regression tests for mid-p confidence intervals and mid-p-values
>
> set.seed(290875)
> library("coin")
Loading required package: survival
> 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))
[1] 0.4835
99 percent confidence interval:
0.4705882 0.4964275
> pci <- attr(p, "conf.int")
> stopifnot(pci[1] < 0.486 & pci[2] > 0.486)
> (mp <- midpvalue(ct_m))
[1] 0.25755
99 percent confidence interval:
0.2463534 0.2688772
> 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))
[1] 0.2419
99 percent confidence interval:
0.2309447 0.2531023
> pci <- attr(p, "conf.int")
> stopifnot(pci[1] < 0.243 & pci[2] > 0.243)
> (mp <- midpvalue(it_m_s_gr))
[1] 0.1288
99 percent confidence interval:
0.1203477 0.1376053
> 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))
[1] 0.2847
99 percent confidence interval:
0.273131 0.296475
> pci <- attr(p, "conf.int")
> stopifnot(pci[1] < 0.2860 & pci[2] > 0.2860)
> (mp <- midpvalue(ct_m))
[1] 0.15175
99 percent confidence interval:
0.1427229 0.1612083
> 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))
[1] 0.0557
99 percent confidence interval:
0.04995533 0.06187217
> pci <- attr(p, "conf.int")
> stopifnot(pci[1] < 0.0544 & pci[2] > 0.0544)
> (mp <- midpvalue(ct_m))
[1] 0.0302
99 percent confidence interval:
0.02601100 0.03483585
> 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))
[1] 0.0643
99 percent confidence interval:
0.05814061 0.07087830
> pci <- attr(p, "conf.int")
> stopifnot(pci[1] < 0.0629 & pci[2] > 0.0629)
> (mp <- midpvalue(ct_m))
[1] 0.0444
99 percent confidence interval:
0.03930789 0.04992546
> 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))
[1] 0.0746
99 percent confidence interval:
0.06798612 0.08162261
> pci <- attr(p, "conf.int")
> stopifnot(pci[1] < 0.0703 & pci[2] > 0.0703)
> (mp <- midpvalue(mt_m))
[1] 0.04125
99 percent confidence interval:
0.03629541 0.04654098
> 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))
[1] 0.0504
99 percent confidence interval:
0.04493012 0.05630272
> pci <- attr(p, "conf.int")
> stopifnot(pci[1] < 0.0525 & pci[2] > 0.0525)
> (mp <- midpvalue(mt_m))
[1] 0.03345
99 percent confidence interval:
0.02898979 0.03825402
> 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))
>
> proc.time()
user system elapsed
1.62 0.14 1.78
Generated by dwww version 1.15 on Sat May 18 14:51:40 CEST 2024.