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  • Tables
  • Bayesian econometrics: VAR, DSGE, IRF, dynamic forecasts, and panel-data models
  • Faster Stata
  • Difference-in-differences (DID) and DDD models
  • Interval-censored Cox model
  • PyStata—Python/Stata integration
  • Jupyter Notebook with Stata
  • Multivariate meta-analysis
  • Bayesian multilevel models: nonlinear, joint, SEM-like, and more
  • Treatment-effects lasso estimation
  • Lasso
  • Truly reproducible reporting
  • Meta-analysis
  • Python integration
  • Bayesian analysis: multiple chains, Bayesian predictions, Gelman–Rubin convergence diagnostic
  • Choice models
  • Import from SAS and SPSS
  • Panel-data models for endogenous covariates, sample selection, and treatment
  • Nonparametric series regression
  • Multiple datasets in memory, Do-File Editor autocompletion and syntax highlighting, and Mac's Dark mode
  • Extended regression models (ERMs)—models for endogenous covariates, sample selection, and treatment
  • Latent class analysis (LCA)
  • bayes prefix for Bayesian estimation
  • Markdown and dynamic documents
  • Linearized DSGE models
  • Finite mixture models
  • Spatial autoregressive models
  • Interval-censored parametric survival models
  • Nonlinear mixed-effects models
  • Create Word documents from Stata and use transparencies in Stata graphs
  • Bayesian analysis
  • Item response theory (IRT)
  • Unicode
  • Treatment effects: survival outcomes, endogenous treatments, balance diagnostics
  • Integration with Excel
  • Multilevel survival models
  • SEM with survey data, Satorra–Bentler adjustments, and survival data
  • Multilevel models for survey data
  • Markov switching models
  • Power and sample size: contingency tables, Cochran–Mantel–Haenszel test, survival analysis, ...
  • Treatment effects: IPW, PS matching, regression adjustment (RA), IPWRA, doubly-robust methods
  • Multilevel models for count, ordinal, categorical, and other outcomes
  • Forecasting
  • Panel-data models for ordinal and categorical outcomes
  • Long strings
  • Generalized SEM—SEM for binary, count, ordinal, and other outcomes; multilevel SEM
  • Power and sample size for tests of means, proportions, variances, correlations, ANOVA
  • Effect sizes
  • Models for censored continuous outcomes
  • Project manager
  • Structural equation modeling (SEM)
  • Multiple imputation: chained equations, conditional imputation, imputation within groups
  • Contour plots
  • Excel import/export
  • ROC analysis
  • Contrasts
  • Pairwise comparisons
  • Margins plot
  • Multilevel models: residual covariance structures, robust SEs, weights
  • Unobserved components model (UCM)
  • Multiple imputation: univariate imputation, multivariate imputation, Control Panel
  • Generalized method of moments (GMM)
  • Fonts in graphics: italic, bold, Greek letters
  • PDF documentation
  • Variables Manager
  • Factor variables
  • Marginal analysis
  • Competing-risks regression
  • State-space models
  • Dynamic-factor models
  • Graph Editor
  • Exact logistic and exact Poisson regression
  • Linear models with endogenous regressors: GMM, LIML, and 2SLS estimation
  • Dynamic panel-data models
  • svy prefix supports 27 new estimators
  • Multilevel logistic and Poisson models
  • Power analysis for survival analysis: log-rank test, Cox model, exponential test
  • Multivariate analysis: discriminant analysis, multidimensional scaling, correspondence analysis
  • Choice models: random-utility nested logit, McFadden's choice model
  • Date and time variables