Stata 18 May 2026

Navigating the Future of Data Science: An In-Depth Look at Stata 18

Stata 18 simplifies the transition from analysis to publication-ready documents. Stata 18

Panel/Longitudinal Data

  • Dynamic Panel Models with xtdpdgmm (GMM estimators for linear dynamic panel data).
  • Fractional outcome models for panel data (xtfereg).

Bayesian Meta-Analysis

Meta-analysts rejoice. bayes: meta allows you to combine evidence from multiple studies with full control over prior distributions. This is particularly useful in pharmaceutical research, where regulatory agencies increasingly expect Bayesian synthesis of evidence. Navigating the Future of Data Science: An In-Depth

Features:

  • One-Stop Shop: Users can create tables containing summary statistics, regression results, and frequencies in a single command sequence.
  • Customization: It offers granular control over formatting (decimal places, fonts, colors) without needing external packages like estout or outreg2.
  • Export: Tables can be exported to Word, Excel, PDF, HTML, and LaTeX seamlessly.
  • Programmability: The syntax allows for the creation of "table programs," enabling users to apply the same formatting style across multiple datasets easily.

Group Sequential Designs: Essential for clinical trials, enabling the analysis of data at interim points to decide if a study should continue. Dynamic Panel Models with xtdpdgmm (GMM estimators for

import stata
stata.run("regress mpg weight")
stata.get_return("r(table)")

2. Major New Statistical Features

Causal Inference

  • Difference-in-Differences (DiD): New didregress and xtdidregress commands handle multiple time periods, variation in treatment timing, and include robust estimators (Callaway-Sant’Anna, Sun-Abraham). Built-in parallel trends and placebo tests.
  • Regression Discontinuity: rdrobust and rdbwselect are now integrated, supporting fuzzy and sharp designs with robust bias-corrected inference.