R Under development (unstable) (2025-02-12 r87715 ucrt) -- "Unsuffered Consequences" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(qountstat) > > testthat::test_check("qountstat") $Results Hypothesis p.values Signif. H0: 0 <-> 1.56 0.0748 . H0: 0 <-> 3.12 0.0001 *** H0: 0 <-> 6.25 0.0020 ** H0: 0 <-> 12.5 0.0000 *** H0: 0 <-> 25 0.0000 *** $Info Information and warnings: Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 There was under-dispersed data identified in treatment(s) 3.12 (HI: -11.2), 6.25 (HI: -10.5). HI = Hampel Identifier. There was over-dispersed data identified in treatment(s) 0 (HI: 25.6), 1.56 (HI: 37.7), 12.5 (HI: 5.8). HI = Hampel Identifier. NOEC: 0, LOEC: 1.56. Assuming that any effects are adverse. Otherwise, NOEC and LOEC should be reconsidered. $Results Simultaneous Tests for General Linear Hypotheses Multiple Comparisons of Means: Dunnett Contrasts Fit: stats::glm(formula = Counts ~ Groups, family = stats::quasipoisson(link = "identity"), data = dat) Linear Hypotheses: Estimate Std. Error z value Pr(>|z|) 1.56 - 0 == 0 3.900 2.472 1.578 0.3418 3.12 - 0 == 0 12.200 2.674 4.563 <0.001 *** 6.25 - 0 == 0 8.300 2.581 3.216 0.0058 ** 12.5 - 0 == 0 -13.000 1.997 -6.509 <0.001 *** 25 - 0 == 0 -22.400 1.676 -13.364 <0.001 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Adjusted p values reported -- single-step method) $Info Information and warnings: A treatment contained only zeros, hence, the zero.treatment.action "identity.link" was applied. $Results Simultaneous Tests for General Linear Hypotheses Multiple Comparisons of Means: Dunnett Contrasts Fit: stats::glm(formula = dat$Counts ~ Groups, family = stats::quasipoisson(link = "log"), data = dat) Linear Hypotheses: Estimate Std. Error z value Pr(>|z|) 1.56 - 0 == 0 0.15415 0.09725 1.585 0.39310 3.12 - 0 == 0 0.41961 0.09187 4.567 < 0.001 *** 6.25 - 0 == 0 0.30358 0.09408 3.227 0.00583 ** 12.5 - 0 == 0 -0.81093 0.12865 -6.303 < 0.001 *** 25 - 0 == 0 -3.15274 0.35251 -8.944 < 0.001 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Adjusted p values reported -- single-step method) $Info Information and warnings: A treatment contained only zeros, hence, the zero.treatment.action "log(x+1)" was applied. $Results Treatment p.values Signif. T1 0.19525735 . T2 0.05447276 . $Info Information and warnings: Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 NOEC: T2, LOEC: outside tested dose/concentration. Assuming that any effects are adverse. Otherwise, NOEC and LOEC should be reconsidered. Simulated p-values used. Calculating bMDD for treatment group '1.56': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 20.0 % (1/5) Step: 3 | Mean diff.: 2.00 | Test power: 60.0 % (3/5) Step: 4 | Mean diff.: 3.00 | Test power: 40.0 % (2/5) Step: 5 | Mean diff.: 4.00 | Test power: 20.0 % (1/5) Step: 6 | Mean diff.: 5.00 | Test power: 40.0 % (2/5) Step: 7 | Mean diff.: 6.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 6 (bMDD% = 26.8 %) Calculating bMDD for treatment group '3.12': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 0.0 % (0/5) Step: 3 | Mean diff.: 2.00 | Test power: 0.0 % (0/5) Step: 4 | Mean diff.: 3.00 | Test power: 20.0 % (1/5) Step: 5 | Mean diff.: 4.00 | Test power: 60.0 % (3/5) Step: 6 | Mean diff.: 5.00 | Test power: 20.0 % (1/5) Step: 7 | Mean diff.: 6.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 6 (bMDD% = 26.8 %) Calculating bMDD for treatment group '6.25': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 0.0 % (0/5) Step: 3 | Mean diff.: 2.00 | Test power: 20.0 % (1/5) Step: 4 | Mean diff.: 3.00 | Test power: 0.0 % (0/5) Step: 5 | Mean diff.: 4.00 | Test power: 60.0 % (3/5) Step: 6 | Mean diff.: 5.00 | Test power: 80.0 % (4/5) Step: 7 | Mean diff.: 6.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 5 (bMDD% = 22.3 %) Calculating bMDD for treatment group '12.5': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 0.0 % (0/5) Step: 3 | Mean diff.: 2.00 | Test power: 0.0 % (0/5) Step: 4 | Mean diff.: 3.00 | Test power: 20.0 % (1/5) Step: 5 | Mean diff.: 4.00 | Test power: 40.0 % (2/5) Step: 6 | Mean diff.: 5.00 | Test power: 60.0 % (3/5) Step: 7 | Mean diff.: 6.00 | Test power: 80.0 % (4/5) Step: 8 | Mean diff.: 7.00 | Test power: 80.0 % (4/5) Step: 9 | Mean diff.: 8.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 6 (bMDD% = 26.8 %) Calculating bMDD for treatment group '25': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 20.0 % (1/5) Step: 3 | Mean diff.: 2.00 | Test power: 0.0 % (0/5) Step: 4 | Mean diff.: 3.00 | Test power: 0.0 % (0/5) Step: 5 | Mean diff.: 4.00 | Test power: 60.0 % (3/5) Step: 6 | Mean diff.: 5.00 | Test power: 20.0 % (1/5) Step: 7 | Mean diff.: 6.00 | Test power: 60.0 % (3/5) Step: 8 | Mean diff.: 7.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 7 (bMDD% = 31.2 %) Hypothesis bMDD bMDD.percent 1 H0: 0 <-> 1.56 6 26.78571 2 H0: 0 <-> 3.12 6 26.78571 3 H0: 0 <-> 6.25 5 22.32143 4 H0: 0 <-> 12.5 6 26.78571 5 H0: 0 <-> 25 7 31.25000 Calculating bMDD for treatment group '1.56': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 0.0 % (0/5) Step: 3 | Mean diff.: 2.00 | Test power: 0.0 % (0/5) Step: 4 | Mean diff.: 3.00 | Test power: 0.0 % (0/5) Step: 5 | Mean diff.: 4.00 | Test power: 0.0 % (0/5) Step: 6 | Mean diff.: 5.00 | Test power: 60.0 % (3/5) Step: 7 | Mean diff.: 6.00 | Test power: 80.0 % (4/5) Step: 8 | Mean diff.: 7.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 6 (bMDD% = 26.8 %) Calculating bMDD for treatment group '3.12': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 0.0 % (0/5) Step: 3 | Mean diff.: 2.00 | Test power: 0.0 % (0/5) Step: 4 | Mean diff.: 3.00 | Test power: 0.0 % (0/5) Step: 5 | Mean diff.: 4.00 | Test power: 0.0 % (0/5) Step: 6 | Mean diff.: 5.00 | Test power: 20.0 % (1/5) Step: 7 | Mean diff.: 6.00 | Test power: 40.0 % (2/5) Step: 8 | Mean diff.: 7.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 7 (bMDD% = 31.2 %) Calculating bMDD for treatment group '6.25': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 0.0 % (0/5) Step: 3 | Mean diff.: 2.00 | Test power: 0.0 % (0/5) Step: 4 | Mean diff.: 3.00 | Test power: 0.0 % (0/5) Step: 5 | Mean diff.: 4.00 | Test power: 0.0 % (0/5) Step: 6 | Mean diff.: 5.00 | Test power: 0.0 % (0/5) Step: 7 | Mean diff.: 6.00 | Test power: 80.0 % (4/5) Step: 8 | Mean diff.: 7.00 | Test power: 60.0 % (3/5) Step: 9 | Mean diff.: 8.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 8 (bMDD% = 35.7 %) Calculating bMDD for treatment group '12.5': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 0.0 % (0/5) Step: 3 | Mean diff.: 2.00 | Test power: 0.0 % (0/5) Step: 4 | Mean diff.: 3.00 | Test power: 0.0 % (0/5) Step: 5 | Mean diff.: 4.00 | Test power: 20.0 % (1/5) Step: 6 | Mean diff.: 5.00 | Test power: 40.0 % (2/5) Step: 7 | Mean diff.: 6.00 | Test power: 80.0 % (4/5) Step: 8 | Mean diff.: 7.00 | Test power: 80.0 % (4/5) Step: 9 | Mean diff.: 8.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 6 (bMDD% = 26.8 %) Calculating bMDD for treatment group '25': Step: 1 | Mean diff.: 0.00 | Test power: 0.0 % (0/5) Step: 2 | Mean diff.: 1.00 | Test power: 0.0 % (0/5) Step: 3 | Mean diff.: 2.00 | Test power: 0.0 % (0/5) Step: 4 | Mean diff.: 3.00 | Test power: 0.0 % (0/5) Step: 5 | Mean diff.: 4.00 | Test power: 0.0 % (0/5) Step: 6 | Mean diff.: 5.00 | Test power: 40.0 % (2/5) Step: 7 | Mean diff.: 6.00 | Test power: 60.0 % (3/5) Step: 8 | Mean diff.: 7.00 | Test power: 100.0 % (5/5) bMDD (power > 0.8) = 7 (bMDD% = 31.2 %) Hypothesis bMDD bMDD.percent 1 H0: 0 <-> 1.56 6 26.78571 2 H0: 0 <-> 3.12 7 31.25000 3 H0: 0 <-> 6.25 8 35.71429 4 H0: 0 <-> 12.5 6 26.78571 5 H0: 0 <-> 25 7 31.25000 Calculating bMDD for treatment group 'T1': Step: 1 | Prob. diff.: 0.00 | Test power: 0.0 % (0/10) Step: 2 | Prob. diff.: 0.10 | Test power: 20.0 % (2/10) Step: 3 | Prob. diff.: 0.20 | Test power: 20.0 % (2/10) Step: 4 | Prob. diff.: 0.30 | Test power: 70.0 % (7/10) Step: 5 | Prob. diff.: 0.40 | Test power: 100.0 % (10/10) bMDD (power > 0.8) = 0.4 (bMDD% = 60.0 %) Calculating bMDD for treatment group 'T2': Step: 1 | Prob. diff.: 0.00 | Test power: 0.0 % (0/10) Step: 2 | Prob. diff.: 0.10 | Test power: 0.0 % (0/10) Step: 3 | Prob. diff.: 0.20 | Test power: 60.0 % (6/10) Step: 4 | Prob. diff.: 0.30 | Test power: 90.0 % (9/10) Step: 5 | Prob. diff.: 0.40 | Test power: 100.0 % (10/10) bMDD (power > 0.8) = 0.3 (bMDD% = 45.0 %) Hypothesis bMDD bMDD.percent 1 H0: Control <-> T1 0.4 60 2 H0: Control <-> T2 0.3 45 ... Calculating power for treatment group '1.56' ... ... Calculating power for treatment group '3.12' ... ... Calculating power for treatment group '6.25' ... ... Calculating power for treatment group '12.5' ... ... Calculating power for treatment group '25' ... Hypothesis Percent.power 1 H0: 0 <-> 1.56 70 2 H0: 0 <-> 3.12 100 3 H0: 0 <-> 6.25 100 4 H0: 0 <-> 12.5 100 5 H0: 0 <-> 25 100 ... Calculating power for treatment group '1.56' ... ... Calculating power for treatment group '3.12' ... ... Calculating power for treatment group '6.25' ... ... Calculating power for treatment group '12.5' ... ... Calculating power for treatment group '25' ... Hypothesis Percent.power 1 H0: 0 <-> 1.56 30 2 H0: 0 <-> 3.12 100 3 H0: 0 <-> 6.25 100 4 H0: 0 <-> 12.5 100 5 H0: 0 <-> 25 100 ... Calculating power for treatment group 'T1' ... ... Calculating power for treatment group 'T2' ... Hypothesis Percent.power 1 H0: Control <-> T1 10 2 H0: Control <-> T2 60 [ FAIL 0 | WARN 4 | SKIP 0 | PASS 0 ] [ FAIL 0 | WARN 4 | SKIP 0 | PASS 0 ] > > proc.time() user system elapsed 12.01 0.28 12.29