Simultaneous systems

• three-stage least squares regression
• two-stage least squares regression
• LIML estimation
• GMM estimation
• Tests of instrumental relevance
• Tests of overidentifying restrictions
  
• linear constraints within & across equations
• models with selection

Seemingly unrelated regression

• linear constraints within & across equations

Fractional polynomial regression

• mean adjustment to variables
• component-residual plots

• Production and cost frontiers
• Half-normal, exponential, and truncated-normal distributions
• modelling of conditional heteroskedasticity
  

Quantile regression

• median regression
• least absolute deviations (LAD)
• regression of any quantile
• Koenker and Bassett or bootstrapped standard errors

Linear mixed models

• multilevel random effects
• BLUP estimation
• Residual-error structures for linear models
• Standard errors of BLUPs

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

• Estimated marginal means
  
• Marginal and partial effects
  
• Average marginal and partial effects
  
• Least-squares means
  
• Predictive margins
  
• Adjusted predictions, means, and effects
  
• Contrasts of margins*
• Pairwise comparisons of margins*
• Profile plots*
• Graphs of margins and marginal effects*

• 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 in odds-ratio metric
  
• Contrasts of means, intercepts, and slopes
  
• Graphs of contrasts
  
• Interaction plots
  

Regression

• Ordinary, constrained, instrumental variables, censored, and errors in variables
  
• influence statistics and fit diagnostics
  • Ramsey regression specification error test for omitted variables
  • variance-inflation factors
  • Cook's distance
  • COVRATIO
  • DFBETAs
  • DFITs
  • diagonal elements of hat matrix
  • residuals, standardized residuals, studentized residuals
  • standard errors of the forecast, prediction, and residuals
  • Welsch distance
    
• tests for heteroskedasticity
  • Cook and Weisberg
  • Sroetzer's rank test
  • information matrix test
  • Cameron and Trevedi's decomposition
  • White's test
    
• tests for autocorrelation
  • Durbin-Watson
  • Durbin-Watson d statistic
  • Breusch-Godfrey
  • ARCH LM test
    
• diagnostic plots
  • added variable (leverage) plot
  • component plus residual plot
  • leverage vs. squared residual plot
  • residual vs fitted plot
  • residual vs predictor
    
• Nested logit models
  
• Fixed- and random-effects models for panel data
• traditional, robust (Huber/White/sandwich), bootstrap, or jackknife standard errors
• robust regression
• graph estimates and confidence intervals
• Newey–West estimator of variance
• variance-weighted least squares
• GLM
• GLS for cross-sectional time-series data
• list estimates and confidence intervals

• 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