ANOVA / ANCOVA

• Balanced and unbalanced designs
• Missing cells
• Factorial, nested, Latin square, and mixed designs
• Repeated measures
• Box, Greenhouse–Geisser, and Huynh–Feldt corrections

EFFECT SIZES

• Eta-squared—η²
• Epsilon-squared—ε²
• Omega-squared—ω²
• Confidence intervals

POSTESTIMATION AFTER ANOVA

• Tests for effects, including pooling and nonresidual error terms
• Tests for expressions involving the coefficients of the underlying regression model
• Bonferroni, Holm, and Šidák adjustments for multiple tests
• Ability to display symbolic forms
• Predictions and influence statistics
  • Expected values
  • Residuals, standardized residuals, studentized residuals
  • Standard error of the prediction or residuals
  • Leverage
  • Cook’s D
  • COVRATIO
  • DFBETAs
  • Diagonal of hat matrix
  • Welsch distance
• Diagnostic plots
  • Residual versus fitted
  • Added-variable plot
  • Component plus residual
  • Augmented component plus residual
  • Residual versus predictor
  • Leverage versus squared residual

MANOVA

• Multivariate test statistics
  • Wilks’ lambda
  • Pillai’s trace
  • Lawley–Hotelling trace
  • Roy’s largest root
• Balanced and unbalanced designs
• Missing cells
• Factorial, nested, Latin square, and mixed designs
• Repeated measures

POSTESTIMATION AFTER MANOVA

• Multivariate tests (Wilks’ lambda, Pillai’s trace, etc.) for
  • Terms from the model
  • Pooled terms
  • Terms (or pooled terms) tested using other terms (or pooled terms) as the error term
  • Linear combinations of the underlying design matrix
• Wald tests of expressions involving the coefficients of the underlying regression model
• Predictions
  • Point estimates
  • Standard error of point estimates
  • Residuals
• Combinations of estimators
  • Linear and nonlinear
  • Confidence intervals

POSTESTIMATION SELECTOR

• View and run all postestimation features for your command
• Automatically updated as estimation commands are run

FACTOR VARIABLES

• Automatically create indicators based on categorical variables
• Form interactions among discrete and continuous variables
• Include polynomial terms
• Perform contrasts of categories/levels

• The basics
• Interactions
• More interactions

MARGINAL ANALYSIS

• Estimated marginal means
• Marginal and partial effects
• Average marginal and partial effects
• Least-squares means
• Predictive margins
• Adjusted predictions, means, and effects
• Works with multiple outcomes simultaneously
• Contrasts of margins
• Pairwise comparisons of margins
• Profile plots
• Interaction plots
• Graphs of margins and marginal effects

• Categorical variables
• Continuous variables
• Interactions

• A single categorical variable
• A single continuous variable
• Interactions of categorical variables
• Interactions of categorical and continuous variables
• Interactions of two continuous variables

CONTRASTS

• Analysis of main effects, simple effects, interaction effects, partial interaction effects, and nested effects
• Comparisons against reference groups, of adjacent levels, or against the grand mean
• Orthogonal polynomials
• Helmert contrasts
• Custom contrasts
• ANOVA-style tests
• Contrasts of nonlinear responses
• Multiple-comparison adjustments
• Balanced and unbalanced data
• Contrasts of means, intercepts, and slopes
• Graphs of contrasts

PAIRWISE COMPARISONS

• Compare estimated means, intercepts, and slopes
• Compare marginal means, intercepts, and slopes
• Balanced and unbalanced data
• Nonlinear responses
• Multiple-comparison adjustments: Bonferroni, Šidák, Scheffé, Tukey HSD, Duncan, and Student–Newman–Keuls adjustments
• Group comparisons that are significant
• Graphs of pairwise comparisons