Webinars
Planned
Machine Precision in Stata
Dr. Asjad Naqvi
Date:
Friday, 08. May 2026
10:00 – 11:30 CET (UTC+01:00)
Free | Online
Language of the Webinar: English
Abstract:
This webinar introduces the concept of machine precision in Stata and its implications in our daily workflows. The session will demonstrate why machine precision matters in applied work, highlighting issues such as rounding error, loss of significance, and numerical instability. Through concrete examples, we show how seemingly negligible inaccuracies can compound across data transformations, simulations, and iterative estimation procedures, potentially affecting substantive results. We will also discuss practical guidelines on diagnosing precision-related issues and choosing appropriate storage types to ensure numerical reliability and reproducibility in Stata workflows.
Archive
Working with Stata Frames
Dr. Asjad Naqvi
06. March 2026
Abstract:
Frames are a relatively new and powerful feature in Stata that allow users to work with multiple datasets simultaneously within a single session, to streamline data management and empirical workflows. This webinar introduces the core concepts of frames, such as creating, linking, and switching between datasets, and demonstrates how they can replace repetitive merges and creation of temporary datasets. Using practical examples, we show how frames support cleaner and more efficient handling of complex data structures, improve transparency and reproducibility of empirical analyses and results, and facilitate the development of more modular and efficient Stata programs and packages.
Conditional Average Treatment Effects Estimation Using Stata
Di Liu – StataCorp LLC.
04. September 2025
Abstract
Treatment effects estimate the causal effects of a treatment on an outcome. These effects may be heterogeneous. Average treatment effects conditional on a set of variables (CATEs) help us understand such heterogeneous treatment effects and, by construction, are useful for evaluating how different treatment-assignment policies impact various groups within a population.
A must-attend for anyone working with causal inference, policy evaluation, or Stata-based data analysis.