This add-in ingests estimates from an ordinary least squares report (produced by Fit Model) and saves a table of model effect estimates, F-ratios, p-values, and three measures of effect size as formula columns (Eta Squared, Partial Eta Squared, Omega Squared). If pairwise analyses are present with 'Ordered Difference' reports available, a combined data table of estimates including pairwise effect sizes (Cohen's d) will be generated, including (as of v.0.06) confidence intervals for Cohen's d. If no pairwise analyses are present this add-in will issue a prompt to add these to the selected report. As of v0.07, False Discovery Rate adjusted p-Values (Benjamini-Hochberg adjustment) are also written to the tables.
Instructions (after installing add-in):
Fit an ordinary least squares model using Analyze > Fit Model
Go to Add-Ins > Calculate Effect Sizes > From Least Squares Report (Fit Model)
If more than one Fit Model Least Squares report is open, a dialog will appear to select which analysis to use.
For models with a categorical factor:
If pairwise analyses (e.g. Student's t-test) and "Ordered Differences' reports are available, Cohen's d including confidence intervals for available pairwise effects will be calculated and saved to a combined data table
If no pairwise analyses have been produced (or "Ordered Differences' reports have not been produced) a prompt will appear to add these analyses and calculate these effect sizes.Output:
Table of model effects, effect sizes, and False Discovery Rate adjusted p-Value.
If requested, table of pairwise effect sizes, confidence intervals, and False Discovery Rate adjusted p-Values.
Note: Overall model statistics are saved to each table as table variables for use in formulas or additional measures of model fit you may wish to add.
This add-in provides estimated effect sizes, confidence intervals, and FDR adjusted p-values for ordinary least squares models (models with random effects are not supported).
Effect Sizes Produced:
Model Effect Sizes:
Partial Eta Squared
Negative values of omega squared are possible and are automatically set to 0
Pairwise Effect Size:
note: In multifactor models, as well as one-factor models with more than two levels, the pooled within-cell error term of the model (RMSE) is used as SDpooled for calculating pairwise effect sizes. In these cases, it is typical to refer to the resulting effect sizes as Root Mean Square Standardized Effects (RMSSE). This is appropriate (and preferable) since the RMSE is the most statistically efficient (lowest variance) estimator of the population sigma in cases where the assumption of homogeneity of variance has not been violated.
v0.03 - Added Cohen's d calculation for pairwise differences, and dialog to produce pairwise analyses if not present
v0.04 - Added code to suppress prompt to add pairwise comparisons for models without categorical factor
v0.05 - Fixed defect for running on Windows (Fit Least Squares reports were not detected). Added support dialog for selecting from available Least Squares reports:
v0.06 - Added support for confidence intervals around Cohen's D
v.0.07 - Added support for False Discovery Rate p-Values