{"id":45359,"date":"2025-04-08T11:07:00","date_gmt":"2025-04-08T11:07:00","guid":{"rendered":"https:\/\/dpc-software.de\/introducing-stata-19\/"},"modified":"2026-10-05T08:55:22","modified_gmt":"2026-10-05T08:55:22","slug":"introducing-stata-19","status":"publish","type":"post","link":"https:\/\/dpc-software.de\/en\/introducing-stata-19\/","title":{"rendered":"Introducing Stata 19"},"content":{"rendered":"\n

The wait is over \u2013 Stata 19 is officially here!
This major update brings a host of powerful new features that will enhance your work \u2013 whether you’re conducting cutting-edge research, policy analysis, or advanced data modeling.
We are excited to introduce the new functionalities. Here’s a quick look at what’s new: <\/p>\n\n

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  1. Machine learning via H2O: Ensemble decision trees<\/li>\n\n\n\n
  2. Conditional average treatment effects (CATE)<\/li>\n\n\n\n
  3. High-dimensional fixed effects (HDFE)<\/li>\n\n\n\n
  4. Bayesian variable selection for linear regression<\/li>\n\n\n\n
  5. Marginal Cox PH model for interval-censored multiple-event data<\/li>\n\n\n\n
  6. Meta-analysis for correlations<\/li>\n\n\n\n
  7. Correlated random-effects (CRE) model<\/li>\n\n\n\n
  8. Panel-data vector autoregressive (VAR) model<\/li>\n\n\n\n
  9. Bayesian bootstrap and replicate weights<\/li>\n\n\n\n
  10. Control-function linear and probit models<\/li>\n\n\n\n
  11. Bayesian quantile regression via asymmetric Laplace likelihood<\/li>\n\n\n\n
  12. Inference robust to weak instruments<\/li>\n\n\n\n
  13. SVAR models via instrumental variables<\/li>\n\n\n\n
  14. Instrumental-variables local-projection IRFs<\/li>\n\n\n\n
  15. Mundlak specification test<\/li>\n\n\n\n
  16. Latent class model-comparison statistics<\/li>\n\n\n\n
  17. Do-file Editor: Autocompletion, templates, and more<\/li>\n\n\n\n
  18. Graphics: Bar graph CIs, heat maps, and more<\/li>\n\n\n\n
  19. Tables: Easier tabulations, exporting, and more<\/li>\n<\/ol>\n\n

    This is just the beginning. Stata 19 also brings: <\/p>\n\n