# parametric t-test works (between-subjects without NAs) Code select(df1, -expression) Output # A tibble: 1 x 17 parameter1 parameter2 mean.parameter1 mean.parameter2 statistic df.error 1 len supp 20.7 17.0 1.92 58 p.value method alternative effectsize estimate conf.level conf.low 1 0.0604 Two Sample t-test two.sided Cohen's d 0.495 0.99 -0.184 conf.high conf.method conf.distribution n.obs 1 1.17 ncp t 60 --- Code df1[["expression"]] Output [[1]] list(italic("t")["Student"] * "(" * 58 * ")" == "1.91527", italic(p) == "0.06039", widehat(italic("d"))["Cohen"] == "0.49452", CI["99%"] ~ "[" * "-0.18354", "1.16839" * "]", italic("n")["obs"] == "60") # parametric t-test works (between-subjects with NAs) Code select(df1, -expression) Output # A tibble: 1 x 17 parameter1 parameter2 mean.parameter1 mean.parameter2 statistic df.error 1 len supp 20.7 17.0 1.92 55.3 p.value method alternative effectsize estimate conf.level 1 0.0606 Welch Two Sample t-test two.sided Hedges' g 0.488 0.9 conf.low conf.high conf.method conf.distribution n.obs 1 0.0599 0.911 ncp t 60 --- Code df1[["expression"]] Output [[1]] list(italic("t")["Welch"] * "(" * 55.309 * ")" == "1.915", italic(p) == "0.061", widehat(italic("g"))["Hedges"] == "0.488", CI["90%"] ~ "[" * "0.060", "0.911" * "]", italic("n")["obs"] == "60") # parametric t-test works (within-subjects without NAs) Code select(df1, -expression) Output # A tibble: 1 x 15 term group statistic df.error p.value method alternative 1 value condition 34.8 149 1.85e-73 Paired t-test two.sided effectsize estimate conf.level conf.low conf.high conf.method 1 Hedges' g 2.83 0.5 2.70 2.95 ncp conf.distribution n.obs 1 t 150 --- Code df1[["expression"]] Output [[1]] list(italic("t")["Student"] * "(" * 149 * ")" == "34.8152", italic(p) == "1.8496e-73", widehat(italic("g"))["Hedges"] == "2.8283", CI["50%"] ~ "[" * "2.6996", "2.9462" * "]", italic("n")["pairs"] == "150") # parametric t-test works (within-subjects with NAs) Code select(df1, -expression) Output # A tibble: 1 x 15 term group statistic df.error p.value method alternative 1 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 0.95 0.166 0.594 ncp conf.distribution n.obs 1 t 90 --- Code df1[["expression"]] Output [[1]] list(italic("t")["Student"] * "(" * 89 * ")" == "3.613", italic(p) == "5.000e-04", widehat(italic("d"))["Cohen"] == "0.381", CI["95%"] ~ "[" * "0.166", "0.594" * "]", italic("n")["pairs"] == "90")