# parametric t-tests Code df_1 Output # A tibble: 4 x 15 mu statistic df.error p.value method alternative effectsize 1 0.25 0.242 55 0.810 One Sample t-test two.sided Cohen's d 2 0.25 0.242 55 0.595 One Sample t-test less Hedges' g 3 0.25 0.242 55 0.405 One Sample t-test greater Cohen's d 4 0.25 0.242 55 0.810 One Sample t-test two.sided Hedges' g estimate conf.level conf.low conf.high conf.method conf.distribution n.obs 1 0.0323 0.89 -0.181 0.246 ncp t 56 2 0.0319 0.99 -0.308 0.371 ncp t 56 3 0.0323 0.9 -0.188 0.252 ncp t 56 4 0.0319 0.5 -0.0572 0.121 ncp t 56 expression 1 2 3 4 --- Code df_2_between Output # A tibble: 4 x 18 parameter1 parameter2 mean.parameter1 mean.parameter2 statistic df.error 1 wt am 3.77 2.41 5.26 30 2 wt am 3.77 2.41 5.49 29.2 3 wt am 3.77 2.41 5.26 30 4 wt am 3.77 2.41 5.49 29.2 p.value method alternative effectsize estimate conf.level 1 0.0000113 Two Sample t-test two.sided Cohen's d 1.93 0.89 2 1.00 Welch Two Sample t-test less Hedges' g 1.88 0.99 3 0.00000563 Two Sample t-test greater Cohen's d 1.93 0.9 4 0.00000627 Welch Two Sample t-test two.sided Hedges' g 1.88 0.5 conf.low conf.high conf.method conf.distribution n.obs expression 1 1.23 2.61 ncp t 32 2 -Inf 2.86 ncp t 32 3 1.36 Inf ncp t 32 4 1.58 2.15 ncp t 32 --- Code df_2_within Output # A tibble: 4 x 16 term group statistic df.error p.value method alternative 1 desire condition 3.61 89 0.000500 Paired t-test two.sided 2 desire condition 3.61 89 0.000500 Paired t-test two.sided 3 desire condition 3.61 89 0.000500 Paired t-test two.sided 4 desire condition 3.61 89 0.000500 Paired t-test two.sided effectsize estimate conf.level conf.low conf.high conf.method 1 Cohen's d 0.381 0.89 0.205 0.554 ncp 2 Hedges' g 0.378 0.99 0.0978 0.656 ncp 3 Cohen's d 0.381 0.9 0.200 0.559 ncp 4 Hedges' g 0.378 0.5 0.304 0.450 ncp conf.distribution n.obs expression 1 t 90 2 t 90 3 t 90 4 t 90 --- Code df_3_between Output # A tibble: 4 x 14 statistic df df.error p.value 1 4.14 3 52 0.0105 2 2.63 3 11.1 0.102 3 4.14 3 52 0.0105 4 2.63 3 11.1 0.102 method effectsize estimate 1 One-way analysis of means Eta2 0.193 2 One-way analysis of means (not assuming equal variances) Omega2 0.245 3 One-way analysis of means Eta2 0.193 4 One-way analysis of means (not assuming equal variances) Omega2 0.245 conf.level conf.low conf.high conf.method conf.distribution n.obs expression 1 0.89 0.0585 1 ncp F 56 2 0.8 0 1 ncp F 56 3 0.9 0.0545 1 ncp F 56 4 0.5 0.0974 1 ncp F 56 --- Code df_3_within Output # A tibble: 2 x 18 term sumsq sum.squares.error df df.error meansq statistic p.value 1 condition 233. 984. 2.63 229. 4.30 20.6 8.27e-11 2 condition 233. 984. 2.63 229. 4.30 20.6 8.27e-11 method effectsize estimate 1 ANOVA estimation for factorial designs using 'afex' Eta2 (partial) 0.191 2 ANOVA estimation for factorial designs using 'afex' Omega2 (partial) 0.0783 conf.level conf.low conf.high conf.method conf.distribution n.obs expression 1 0.89 0.136 1 ncp F 88 2 0.9 0.0362 1 ncp F 88