# `pairwise_comparisons()` works for between-subjects design Code df1 Output # A tibble: 6 x 6 group1 group2 p.value p.adjust.method test expression 1 carni herbi 1 Bonferroni Student's t 2 carni insecti 1 Bonferroni Student's t 3 carni omni 1 Bonferroni Student's t 4 herbi insecti 1 Bonferroni Student's t 5 herbi omni 0.979 Bonferroni Student's t 6 insecti omni 1 Bonferroni Student's t --- Code df1[["expression"]] Output [[1]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[2]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[3]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[4]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[5]] list(italic(p)["Bonferroni" - adj.] == "0.98") [[6]] list(italic(p)["Bonferroni" - adj.] == "1.00") --- Code df2 Output # A tibble: 6 x 9 group1 group2 statistic p.value alternative distribution p.adjust.method 1 carni herbi 2.17 1 two.sided q Bonferroni 2 carni insecti -2.17 1 two.sided q Bonferroni 3 carni omni 1.10 1 two.sided q Bonferroni 4 herbi insecti -2.41 1 two.sided q Bonferroni 5 herbi omni -1.87 1 two.sided q Bonferroni 6 insecti omni 2.19 1 two.sided q Bonferroni test expression 1 Games-Howell 2 Games-Howell 3 Games-Howell 4 Games-Howell 5 Games-Howell 6 Games-Howell --- Code df2[["expression"]] Output [[1]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[2]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[3]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[4]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[5]] list(italic(p)["Bonferroni" - adj.] == "1.00") [[6]] list(italic(p)["Bonferroni" - adj.] == "1.00") --- Code df3 Output # A tibble: 6 x 9 group1 group2 statistic p.value alternative distribution p.adjust.method 1 carni herbi 0.582 0.561 two.sided z None 2 carni insecti 1.88 0.0595 two.sided z None 3 carni omni 1.14 0.254 two.sided z None 4 herbi insecti 1.63 0.102 two.sided z None 5 herbi omni 0.717 0.474 two.sided z None 6 insecti omni 1.14 0.254 two.sided z None test expression 1 Dunn 2 Dunn 3 Dunn 4 Dunn 5 Dunn 6 Dunn --- Code df3[["expression"]] Output [[1]] list(italic(p)[unadj.] == "0.56") [[2]] list(italic(p)[unadj.] == "0.06") [[3]] list(italic(p)[unadj.] == "0.25") [[4]] list(italic(p)[unadj.] == "0.10") [[5]] list(italic(p)[unadj.] == "0.47") [[6]] list(italic(p)[unadj.] == "0.25") --- Code df4 Output # A tibble: 6 x 10 group1 group2 estimate conf.level conf.low conf.high p.value p.adjust.method 1 carni herbi -0.0323 0.95 -0.248 0.184 0.790 FDR 2 carni insecti 0.0451 0.95 -0.0484 0.139 0.552 FDR 3 carni omni 0.00520 0.95 -0.114 0.124 0.898 FDR 4 herbi insecti 0.0774 0.95 -0.133 0.288 0.552 FDR 5 herbi omni 0.0375 0.95 -0.182 0.257 0.790 FDR 6 insecti omni -0.0399 0.95 -0.142 0.0625 0.552 FDR test expression 1 Yuen's trimmed means 2 Yuen's trimmed means 3 Yuen's trimmed means 4 Yuen's trimmed means 5 Yuen's trimmed means 6 Yuen's trimmed means --- Code df4[["expression"]] Output [[1]] list(italic(p)["FDR" - adj.] == "0.79") [[2]] list(italic(p)["FDR" - adj.] == "0.55") [[3]] list(italic(p)["FDR" - adj.] == "0.90") [[4]] list(italic(p)["FDR" - adj.] == "0.55") [[5]] list(italic(p)["FDR" - adj.] == "0.79") [[6]] list(italic(p)["FDR" - adj.] == "0.55") --- Code df5 Output # A tibble: 3 x 6 group1 group2 p.value p.adjust.method test expression 1 PG PG-13 0.316 Holm Student's t 2 PG R 0.00283 Holm Student's t 3 PG-13 R 0.00310 Holm Student's t --- Code df5[["expression"]] Output [[1]] list(italic(p)["Holm" - adj.] == "0.32") [[2]] list(italic(p)["Holm" - adj.] == "2.83e-03") [[3]] list(italic(p)["Holm" - adj.] == "3.10e-03") --- Code df6 Output # A tibble: 6 x 9 group1 group2 statistic p.value alternative distribution p.adjust.method 1 carni herbi 2.17 1 two.sided q Holm 2 carni insecti -2.17 1 two.sided q Holm 3 carni omni 1.10 1 two.sided q Holm 4 herbi insecti -2.41 1 two.sided q Holm 5 herbi omni -1.87 1 two.sided q Holm 6 insecti omni 2.19 1 two.sided q Holm test expression 1 Games-Howell 2 Games-Howell 3 Games-Howell 4 Games-Howell 5 Games-Howell 6 Games-Howell --- Code df6[["expression"]] Output [[1]] list(italic(p)["Holm" - adj.] == "1.00") [[2]] list(italic(p)["Holm" - adj.] == "1.00") [[3]] list(italic(p)["Holm" - adj.] == "1.00") [[4]] list(italic(p)["Holm" - adj.] == "1.00") [[5]] list(italic(p)["Holm" - adj.] == "1.00") [[6]] list(italic(p)["Holm" - adj.] == "1.00") # dropped levels are not included Code df1 Output # A tibble: 1 x 9 group1 group2 statistic p.value alternative distribution p.adjust.method 1 carni omni 1.10 0.447 two.sided q None test expression 1 Games-Howell --- Code df1[["expression"]] Output [[1]] list(italic(p)[unadj.] == "0.45") # data without NAs Code df Output # A tibble: 3 x 6 group1 group2 p.value p.adjust.method test expression 1 setosa versicolor 1.32e-15 FDR Student's t 2 setosa virginica 6.64e-32 FDR Student's t 3 versicolor virginica 2.77e- 9 FDR Student's t --- Code df[["expression"]] Output [[1]] list(italic(p)["FDR" - adj.] == "1.32e-15") [[2]] list(italic(p)["FDR" - adj.] == "6.64e-32") [[3]] list(italic(p)["FDR" - adj.] == "2.77e-09") # `pairwise_comparisons()` works for within-subjects design - NAs Code df1 Output # A tibble: 6 x 6 group1 group2 p.value p.adjust.method test expression 1 HDHF HDLF 3.18e- 3 Bonferroni Student's t 2 HDHF LDHF 4.21e- 1 Bonferroni Student's t 3 HDHF LDLF 3.95e-12 Bonferroni Student's t 4 HDLF LDHF 3.37e- 1 Bonferroni Student's t 5 HDLF LDLF 7.94e- 3 Bonferroni Student's t 6 LDHF LDLF 1.33e- 8 Bonferroni Student's t --- Code df1[["expression"]] Output [[1]] list(italic(p)["Bonferroni" - adj.] == "0.003") [[2]] list(italic(p)["Bonferroni" - adj.] == "0.421") [[3]] list(italic(p)["Bonferroni" - adj.] == "3.950e-12") [[4]] list(italic(p)["Bonferroni" - adj.] == "0.337") [[5]] list(italic(p)["Bonferroni" - adj.] == "0.008") [[6]] list(italic(p)["Bonferroni" - adj.] == "1.331e-08") --- Code df2 Output # A tibble: 6 x 9 group1 group2 statistic p.value alternative distribution p.adjust.method 1 HDHF HDLF 4.78 1.44e- 5 two.sided t BY 2 HDHF LDHF 2.44 4.47e- 2 two.sided t BY 3 HDHF LDLF 8.01 5.45e-13 two.sided t BY 4 HDLF LDHF 2.34 4.96e- 2 two.sided t BY 5 HDLF LDLF 3.23 5.05e- 3 two.sided t BY 6 LDHF LDLF 5.57 4.64e- 7 two.sided t BY test expression 1 Durbin-Conover 2 Durbin-Conover 3 Durbin-Conover 4 Durbin-Conover 5 Durbin-Conover 6 Durbin-Conover --- Code df2[["expression"]] Output [[1]] list(italic(p)["BY" - adj.] == "1.436e-05") [[2]] list(italic(p)["BY" - adj.] == "0.045") [[3]] list(italic(p)["BY" - adj.] == "5.447e-13") [[4]] list(italic(p)["BY" - adj.] == "0.050") [[5]] list(italic(p)["BY" - adj.] == "0.005") [[6]] list(italic(p)["BY" - adj.] == "4.635e-07") --- Code df3 Output # A tibble: 6 x 11 group1 group2 estimate conf.level conf.low conf.high p.value p.crit 1 HDHF HDLF 1.03 0.95 0.140 1.92 0.00999 0.0127 2 HDHF LDHF 0.454 0.95 -0.104 1.01 0.0520 0.025 3 HDHF LDLF 1.95 0.95 1.09 2.82 0.000000564 0.00851 4 HDLF LDHF -0.676 0.95 -1.61 0.256 0.0520 0.05 5 HDLF LDLF 0.889 0.95 0.0244 1.75 0.0203 0.0169 6 LDHF LDLF 1.35 0.95 0.560 2.14 0.000102 0.0102 p.adjust.method test expression 1 Hommel Yuen's trimmed means 2 Hommel Yuen's trimmed means 3 Hommel Yuen's trimmed means 4 Hommel Yuen's trimmed means 5 Hommel Yuen's trimmed means 6 Hommel Yuen's trimmed means --- Code df3[["expression"]] Output [[1]] list(italic(p)["Hommel" - adj.] == "0.010") [[2]] list(italic(p)["Hommel" - adj.] == "0.052") [[3]] list(italic(p)["Hommel" - adj.] == "5.642e-07") [[4]] list(italic(p)["Hommel" - adj.] == "0.052") [[5]] list(italic(p)["Hommel" - adj.] == "0.020") [[6]] list(italic(p)["Hommel" - adj.] == "1.017e-04") --- Code df4 Output # A tibble: 6 x 18 group1 group2 term effectsize estimate conf.level conf.low 1 HDHF HDLF Difference Bayesian t-test 1.10 0.95 0.488 2 HDHF LDHF Difference Bayesian t-test 0.450 0.95 -0.0551 3 HDHF LDLF Difference Bayesian t-test 2.13 0.95 1.62 4 HDLF LDHF Difference Bayesian t-test -0.649 0.95 -1.32 5 HDLF LDLF Difference Bayesian t-test 0.976 0.95 0.380 6 LDHF LDLF Difference Bayesian t-test 1.66 0.95 1.15 conf.high pd prior.distribution prior.location prior.scale bf10 1 1.72 1 cauchy 0 0.707 4.16e+ 1 2 0.951 0.954 cauchy 0 0.707 5.83e- 1 3 2.63 1 cauchy 0 0.707 1.20e+10 4 0.0583 0.968 cauchy 0 0.707 6.98e- 1 5 1.60 0.999 cauchy 0 0.707 1.81e+ 1 6 2.15 1 cauchy 0 0.707 4.81e+ 6 conf.method log_e_bf10 n.obs expression test 1 ETI 3.73 88 Student's t 2 ETI -0.539 88 Student's t 3 ETI 23.2 88 Student's t 4 ETI -0.359 88 Student's t 5 ETI 2.90 88 Student's t 6 ETI 15.4 88 Student's t --- Code df4[["expression"]] Output [[1]] list(log[e] * (BF["01"]) == "-3.73") [[2]] list(log[e] * (BF["01"]) == "0.54") [[3]] list(log[e] * (BF["01"]) == "-23.21") [[4]] list(log[e] * (BF["01"]) == "0.36") [[5]] list(log[e] * (BF["01"]) == "-2.90") [[6]] list(log[e] * (BF["01"]) == "-15.39") # `pairwise_comparisons()` works for within-subjects design - without NAs Code df1 Output # A tibble: 3 x 6 group1 group2 p.value p.adjust.method test expression 1 Wine A Wine B 0.732 None Student's t 2 Wine A Wine C 0.0142 None Student's t 3 Wine B Wine C 0.000675 None Student's t --- Code df1[["expression"]] Output [[1]] list(italic(p)[unadj.] == "0.732") [[2]] list(italic(p)[unadj.] == "0.014") [[3]] list(italic(p)[unadj.] == "6.754e-04") --- Code df2 Output # A tibble: 3 x 9 group1 group2 statistic p.value alternative distribution p.adjust.method 1 Wine A Wine B 1.05 0.301 two.sided t None 2 Wine A Wine C 3.66 0.000691 two.sided t None 3 Wine B Wine C 2.62 0.0123 two.sided t None test expression 1 Durbin-Conover 2 Durbin-Conover 3 Durbin-Conover --- Code df2[["expression"]] Output [[1]] list(italic(p)[unadj.] == "0.301") [[2]] list(italic(p)[unadj.] == "6.915e-04") [[3]] list(italic(p)[unadj.] == "0.012") --- Code df3 Output # A tibble: 3 x 11 group1 group2 estimate conf.level conf.low conf.high p.value p.crit 1 Wine A Wine B 0.0214 0.95 -0.0216 0.0645 0.195 0.05 2 Wine A Wine C 0.114 0.95 0.0215 0.207 0.00492 0.0169 3 Wine B Wine C 0.0821 0.95 0.00891 0.155 0.00878 0.025 p.adjust.method test expression 1 None Yuen's trimmed means 2 None Yuen's trimmed means 3 None Yuen's trimmed means --- Code df3[["expression"]] Output [[1]] list(italic(p)[unadj.] == "0.195") [[2]] list(italic(p)[unadj.] == "0.005") [[3]] list(italic(p)[unadj.] == "0.009") --- Code df4 Output # A tibble: 3 x 18 group1 group2 term effectsize estimate conf.level conf.low 1 Wine A Wine B Difference Bayesian t-test 0.00721 0.95 -0.0418 2 Wine A Wine C Difference Bayesian t-test 0.0755 0.95 0.0127 3 Wine B Wine C Difference Bayesian t-test 0.0693 0.95 0.0303 conf.high pd prior.distribution prior.location prior.scale bf10 1 0.0562 0.624 cauchy 0 0.707 0.235 2 0.140 0.990 cauchy 0 0.707 3.71 3 0.110 1.00 cauchy 0 0.707 50.5 conf.method log_e_bf10 n.obs expression test 1 ETI -1.45 22 Student's t 2 ETI 1.31 22 Student's t 3 ETI 3.92 22 Student's t --- Code df4[["expression"]] Output [[1]] list(log[e] * (BF["01"]) == "1.45") [[2]] list(log[e] * (BF["01"]) == "-1.31") [[3]] list(log[e] * (BF["01"]) == "-3.92") # additional arguments are passed to underlying methods Code df1 Output # A tibble: 6 x 6 group1 group2 p.value p.adjust.method test expression 1 HDHF HDLF 2.65e- 4 None Student's t 2 HDHF LDHF 3.51e- 2 None Student's t 3 HDHF LDLF 3.29e-13 None Student's t 4 HDLF LDHF 9.72e- 1 None Student's t 5 HDLF LDLF 6.62e- 4 None Student's t 6 LDHF LDLF 1.11e- 9 None Student's t --- Code df1[["expression"]] Output [[1]] list(italic(p)[unadj.] == "2.65e-04") [[2]] list(italic(p)[unadj.] == "0.04") [[3]] list(italic(p)[unadj.] == "3.29e-13") [[4]] list(italic(p)[unadj.] == "0.97") [[5]] list(italic(p)[unadj.] == "6.62e-04") [[6]] list(italic(p)[unadj.] == "1.11e-09") --- Code df2 Output # A tibble: 6 x 6 group1 group2 p.value p.adjust.method test expression 1 HDHF HDLF 1.00 None Student's t 2 HDHF LDHF 0.965 None Student's t 3 HDHF LDLF 1.00 None Student's t 4 HDLF LDHF 0.0281 None Student's t 5 HDLF LDLF 0.999 None Student's t 6 LDHF LDLF 1.00 None Student's t --- Code df2[["expression"]] Output [[1]] list(italic(p)[unadj.] == "1.00") [[2]] list(italic(p)[unadj.] == "0.96") [[3]] list(italic(p)[unadj.] == "1.00") [[4]] list(italic(p)[unadj.] == "0.03") [[5]] list(italic(p)[unadj.] == "1.00") [[6]] list(italic(p)[unadj.] == "1.00") --- Code df3 Output # A tibble: 3 x 6 group1 group2 p.value p.adjust.method test expression 1 4 6 0.995 None Student's t 2 4 8 1.00 None Student's t 3 6 8 0.997 None Student's t --- Code df3[["expression"]] Output [[1]] list(italic(p)[unadj.] == "0.99") [[2]] list(italic(p)[unadj.] == "1.00") [[3]] list(italic(p)[unadj.] == "1.00") --- Code df4 Output # A tibble: 3 x 6 group1 group2 p.value p.adjust.method test expression 1 4 6 0.00532 None Student's t 2 4 8 0.000000103 None Student's t 3 6 8 0.00258 None Student's t --- Code df4[["expression"]] Output [[1]] list(italic(p)[unadj.] == "5.32e-03") [[2]] list(italic(p)[unadj.] == "1.03e-07") [[3]] list(italic(p)[unadj.] == "2.58e-03")