Effect Size and Confidence Interval Calculator
Format numbers for APA-style reporting
Confidence interval for R^2 (exported helper)
Cohen's d for Paired t Using the Average SD Denominator
Cohen's d from t for Paired Samples Using the SD of Difference Scores
Cohen's d for Paired t Using the SD of Difference Scores
Cohen's d for Paired t Controlling for Correlation (Repeated Measures)
General interface for Cohen's d
Cohen's d from t for Independent Samples (Pooled SD)
Cohen's d for Independent Samples Using the Pooled SD
Cohen's d (SMD) for Independent Proportions (Binary Outcomes)
Cohen's d from t for One-Sample t-Test
Cohen's d for One-Sample t from Summary Stats
r and Coefficient of Determination (R2) from d
Cohen's d for Z-test from Population Mean and SD
Cohen's d from z-statistic for Z-test
for Between Subjects with Control Group SD Denominator
for ANOVA from and Sum of Squares
and Coefficient of Determination (R) for ANOVA from
for ANOVA from and Sum of Squares
for ANOVA from and Sum of Squares
Corrected for Independent
(Partial Generalized Eta-Squared) for Mixed Design ANOVA ...
(Partial Generalized Eta-Squared) for Repeated-Measures A...
Cohen's h for Independent Proportions
Odds Ratio from 2x2 Table
for ANOVA from
omega^2 for One-Way and Multi-Way ANOVA from F
omega^2_G (Generalized Omega Squared) for Multi-Way and Mixed ANOVA fr...
omega^2_p (Partial Omega Squared) for Between-Subjects ANOVA from F
omega^2_p (Partial Omega Squared) for Repeated Measures ANOVA from F
r to Coefficient of Determination (R) from F
r-family effect size wrapper
V for Chi-Square
Measure of the Effect ('MOTE') is an effect size calculator, including a wide variety of effect sizes in the mean differences family (all versions of d) and the variance overlap family (eta, omega, epsilon, r). 'MOTE' provides non-central confidence intervals for each effect size, relevant test statistics, and output for reporting in APA Style (American Psychological Association, 2010, <ISBN:1433805618>) with 'LaTeX'. In research, an over-reliance on p-values may conceal the fact that a study is under-powered (Halsey, Curran-Everett, Vowler, & Drummond, 2015 <doi:10.1038/nmeth.3288>). A test may be statistically significant, yet practically inconsequential (Fritz, Scherndl, & Kühberger, 2012 <doi:10.1177/0959354312436870>). Although the American Psychological Association has long advocated for the inclusion of effect sizes (Wilkinson & American Psychological Association Task Force on Statistical Inference, 1999 <doi:10.1037/0003-066X.54.8.594>), the vast majority of peer-reviewed, published academic studies stop short of reporting effect sizes and confidence intervals (Cumming, 2013, <doi:10.1177/0956797613504966>). 'MOTE' simplifies the use and interpretation of effect sizes and confidence intervals.