Presentation slides and recordings are now available on this page for the speakers from the Oceania Stata Conference 2025.
Chuck Huber
Causal Mediation Analysis Using Stata
Observational studies try to determine the effect of an exposure or treatment (T) on an outcome of interest (Y). Sometimes the treatment has an effect on a third variable, called a mediating variable (M), which also influences the outcome. So the treatment may have both a direct effect on the outcome (T -> Y) and an indirect effect on the outcome through its influence on the mediating variable (T -> M -> Y). The goal of causal mediation analysis is to identify and quantify these direct and indirect effects. This presentation will introduce the concepts and jargon of causal mediation analysis, demonstrate how to analyze these kinds of studies, and show how to interpret and visualize these kinds of relationships in clinical trials.
About the speaker
Chuck Huber is Director of Statistical Outreach at StataCorp and Adjunct Associate Professor of Biostatistics at the Texas A&M School of Public Health and at the New York University School of Global Public Health. In addition to working with Stata's team of software developers, he produces instructional videos for the Stata Youtube channel, writes blog entries, develops online NetCourses and gives talks about Stata at conferences and universities. Most of his current work is focused on statistical methods used by behavioral and health scientists. He has published in the areas of neurology, human and animal genetics, alcohol and drug abuse prevention, nutrition and birth defects. Dr. Huber currently teaches survey sampling at NYU and introductory biostatistics at Texas A&M where he previously taught categorical data analysis, survey data analysis, and statistical genetics.
Luis Eduardo San Martin
Ensuring Reproducibility in Stata: Insights From the World Bank's Reproducible Research Repository
The challenge of reproducing economics research has gained increased attention with the growing advocacy for open science in the field. Economics journals and research institutions are quickly adopting reproducibility guidelines, requiring authors to provide code and data for reproducing results and ensuring the trustworthiness of their findings. Presented by the Development Impact Analytics team of the World Bank, this session delves into the intricacies of achieving reproducibility in Stata works. Since the launch of the World Bank's Reproducible Research Repository, the team has conducted reproducibility verifications and curated reproducibility packages for almost a two hundred working papers and reports from diverse research teams in the organization, building up a valuable and novel experience into addressing common issues that break reproducibility in Stata analyses. The session will present an overview of the workflows and tools the team has developed in response to identified reproducibility challenges in typical Stata works, covering key topics such as controlling the versions of external dependencies and appropriately handling randomness in Stata code. The presentation will include practical strategies for enhancing the transparency and reliability of Stata-based research.
About the speaker
Luis Eduardo is a Junior Data Scientist at the World Bank's Development Impact (DIME) department, where he coordinates code reviews to ensure the reproducibility of World Bank research, creates and maintains tools and standards for research transparency, and provides data science support for DIME's project portfolio. Before joining DIME, Luis Eduardo worked as a Data Analyst for the Peruvian government and as a Research Associate for Innovations for Poverty Action. He holds an MSc in Computational Analysis and Public Policy from the University of Chicago and a BSc in Economics Engineering from Universidad Nacional de Ingenieria in Lima.
Fernando Rios-Avila
JWDID
This presentation explores Fernando's perspective on Jeff Wooldridge's DID approach, incorporating his latest Flex method. Additionally, this paper includes modifications Fernando and his coauthors developed for gravity models.
About the speaker
Fernando Rios-Avila is an economist with a strong focus on labor economics, applied econometrics, and poverty and inequality analysis. Fernando holds a Ph.D. in economics from Georgia State University and has published extensively in leading academic journals. His research emphasizes bridging advanced econometric modeling with practical tools for practitioners.
Links
Davud Rostam-Afschar
How to Run Adaptive Experiments in Stata: Causal Inference from Multi-Armed Bandits
This talk provides an introduction to batched bandit experiments. We will discuss how to simulate, interactively run, and analyze batched bandit experiments using the Stata program bbandits. We will discuss results from Monte Carlo simulations and study how to obtain valid statistical inference and correct coverage and discuss a wide range of statistics and illustrations to analyze adaptively collected data. The objective is to learn how to implement own batched bandit experiments.
About the speaker
Davud Rostam-Afschar is a professor at the University of Mannheim and academic director of the German Business Panel. He has previously held visiting research positions at UC Berkeley and Harvard University, and has conducted research and taught at the University of Hohenheim, the Free University of Berlin and the University of Potsdam. Additionally, he serves as a consultant for the European Commission and OECD. His research focuses on economics.
Amy Grant and David White
Be Bold: Use the Open-Source Features of Stata to Customise Commands to Suit Your Needs
In this paper Amy and David will present approaches that can be used by Stata users to customise both Stata and user-written commands to suit their specific needs. Amy and David have been helping customers with Stata at SDAS and have seen many customers interested in user-written commands or changing approaches to Stata commands, however, not quite able to.
About David
David is a director with SDAS. He enjoys helping his clients drive value through their data. He has been performing data analytics using various tools since the early 1990s and now primarily uses Stata for audit analytics, business analysis and data management. He is part of the team at SDAS presenting the SDAS Stata Webinar Series.
About Amy
Amy is part of the team at Survey Design and Analysis Services helping with administration, technical support and content creation. She is also studying a Bachelor of Statistics at the Australian National University.
James Hurley
Visualising and Diagnosing Spillover Within Randomised Controlled Trials Using Diagnostic Test Assessment Methods in Stata
The presentation will demonstrate the use of Stata to visualize and diagnose spillover within randomized controlled trials. In the past, techniques such as the L’abbe plot might have been used but the plots available with diagnostic test assessment methods in Stata [user written commands] are better. Spillover is crucial for the inference from RCT’s but difficult to demonstrate without use of information from outside the RCT. The data [plots and Stata codes] are available are Hurley JC. Visualizing and diagnosing spillover within randomized concurrent controlled trials through the application of diagnostic test assessment methods. BMC Medical Research Methodology. 2024 Aug 16;24(1):182.
About the speaker
James Hurley MD PhD M epidemiol, has a day job as a staff physician at Ballarat and also affiliated with the University of Melbourne (Department of rural Health). His other job is research [a hobby over the past 30 years] to research differences in infection rates in published studies of ICU patients using meta-analysis. He is also a senior editor for Journal of Antimicrobial chemotherapy.
John Kane
Sharing Stata Knowledge Online: Existing Examples and Guidance on How to Do It More Effectively
Learning and sharing Stata knowledge online can be a challenging endeavor, especially when it comes to data visualization. In his presentation, John will cover some existing resources for doing so, including the notable advantages offered by the website Medium. John will demonstrate how Stata users can use Medium—and its popular “Stata Gallery”—to learn, or share their own, valuable insights for making more effective visualizations, communicating key statistical concepts, and doing better analysis.
About the speaker
John V. Kane is an Associate Professor at New York University’s Center for Global Affairs, a Visiting Research Scholar at Stony Brook University, and an Affiliated Faculty member of New York University’s Department of Politics. He received his Ph.D. in political science and has published numerous peer-reviewed articles on public opinion, political psychology, and experimental research methodology.
Wong Keng Siong
Past Sovereign Defaults as a Predictor of Future Defaults
This study looks at the likelihood that a country that defaults once would default again by testing the statistical significance between sovereign default as dependent variable against lags of itself as the independent variable. Set up panelised probit models with Stata, the results show that a sovereign that has defaulted is very likely to default again in the next eight years following the initial default.
About the speaker
Dr Wong Keng Siong is currently Credit Risk Manager for Banks, Supranationals, Sovereigns and Fund Managers at DBS Bank. Prior to March 2019, he was the bank's Head of Country Risk Management for 11 years. He is also currently an associate instructor at the Singapore University of Social Sciences and a member of the Investment Committee of the SAFRA National Service Association.
Presentation slides coming soon...
Jan Kabatek
Single Precision Storage Default - Is It Time to Bid Farewell?
This presentation highlights another legacy issue that characterizes the current versions of Stata. The issue is that, by default, Stata stores data in single-precision data format, but performs all the calculations in double precision. When handling non-integer data, this gives rise to unexpected behaviors that undermine the presumed functions of basic logical operators (“==”, “!=”, “<”, and “>”). Jan will give several examples to illustrate the ways in which this behavior can fundamentally alter the conclusions of statistical models. Similar to his earlier presentation, this one is intended to start the conversation whether it is time to move away from the single-precision storage default, fully embracing the double-precision format.
About the speaker
Jan is a senior research fellow at the University of Melbourne's Melbourne Institute, where he uses big administrative registers to gain data-driven insights into the topics of labor, family, gender, and ageing. In addition to his research, Jan occasionally tweets Stata tips and produces custom packages to help others work with large data sets.