Fixed- and random-effects models

• linear model with panel-level effects and i.i.d. errors
• linear model with panel-level effects and AR(1) errors
• GLS and ML estimators
• robust and cluster-robust standard errors

Specification tests

• Hausman specification test
• Breusch and Pagan Lagrange multiplier test for random effects

• Arellano–Bond estimator
• Arellano–Bover/Blundell–Bond system
• Opening, closing, and embedded gaps
• Serially correlated disturbances
• Complete control over instrument list
• Predetermined variables
• Tests for autocorrelation and of overidentifying restrictions
  

Panel-corrected standard errors (PCSE) for linear cross-sectional models

Two-stage least squares panel data estimators

• between-2SLS estimator
• within-2SLS estimator
• Balestra–Varadharajan–Krishnakumar G2SLS estimator
• Baltagi EC2SLS estimator
• all with balanced or exogenously balanced panels

Stochastic Frontier Models

• time-invariant models
• time-varying decay model
• Battese–Coelli parameterization of time effects
• estimates of technical efficiency and inefficiency

Regressors correlated with individual–level effects

• Haussman–Taylor instrumental varaible estimators
• Amemiya–MaCurdy instrumenal variable estimators

Factor variables

• 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*
  

• 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
  

Panel-data unit-root tests

• Im–Pesaran–Shin
  
• Levin–Lin–Chu
  
• Hadri
• Breitung
  
• Fisher-type (combining p-values)
  
• Harris–Tzavalis
  

Summary statistics and tabulations

• statistics within and between panels
• pattern of panel participation

Random-effects regression for binary and count-dependent variables

• interval regression
• tobit
  
• probit
• logistic regression
• complementary log-log regression
• Poisson regression (Gaussian random-effects)
• Poisson regression (gamma random-effects)
• negative binomial regression
• linear parameter constraints

Conditional fixed-effects regression for binary and count-dependent variables

• logit regression
• Poisson regression
• negative binomial regression

Panel-data line plots

• graphs by panel
• overlaid panels

GEE estimation of general linear models/

• 6 distribution families
• 9 links
• 7 correlation structures
• specific models include:
• probit model with panel-correlation structure
• Poisson model with panel-correlation structure

Population-averaged regression

• complementary log-log regression
• logit regression
• negative binomial regression
• Poisson regression
• probit regression
• linear models regression

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