Virtual Workshop Series

Fall Virtual Workshop Series

PAA is excited to introduce the new virtual workshop series! Please see the workshops that will be presented in Fall 2026, click to be taken to description and registration link. 

• Population and Environment Research (2 Parts)

• Studying Mortality using Harmonized National Health Interview Survey Linked Mortality File Data (NHIS-LMF) from IPUMS

• Randomized Controlled Trials (RCTs) in Population and Reproductive Health: From Research Design to Policy Impact

• Whose Data Counts? Improving Demographic Data Quality and Use Through Participatory Measurement

• Nonparametric Decompositions in Stata with Applications to the Demographic and Health Surveys

Registration Rates for a single workshop

• Regular/Emeritus
• Member: $125
• Non-Member: $175
• Student
• Member: $75
• Non-Member: $125
• LMIC
• Member: $75
• Non-Member: $125

Registrants will receive the Zoom link to their e-mail 2 days prior to the event. Please note there is a $25 cancellation fee.

Population and Environment Research (2 Parts)  |  Register now

You must register for each Part separately.

Part 1: Three Applications of Public Population Data 
Tuesday, October 6, 1:00 - 4:00 pm ET

• Organizer: Sara Ronnkvist, Kansas Geological Survey, University of Kansas
• Description: Despite recent advances in data availability, the barriers for investigating the interactions between demographic processes and environmental phenomena remain high.  For example, publicly available demographic data often include no or coarse spatial identifiers which often makes it unfeasible to merge with finer scale environmental data. In this workshop, we will discuss various approaches to using publicly available data to study a variety of environmental demography topics, including health and aging. The overall goal of this workshop is to reduce barriers to population and environment research by highlighting research that uses free and easily accessible data.

Part 2: Linking Gridded Environmental Data to Public Population Data
Tuesday, October 13, 1:00 - 4:00 pm ET

• Organizer: Alex Mikulas, University of Colorado Boulder/CACHE
• Description: In this second of two linked sessions, participants will learn the practical steps for finding, processing, and linking environmental data to public population-level datasets, health and aging surveys, and other demographic datasets. The workshop emphasizes the technical aspects of integrating continuous (gridded) geospatial data with population data that are not easily compatible with gridded data. Instead, population data often identify locations using geospatial points, mailing addresses, or administrative boundaries (like census tracts or counties). Participants will gain hands-on experience coding in R Studio and will receive multiple resources for spatial data processing.

Studying Mortality using Harmonized National Health Interview Survey Linked Mortality File Data (NHIS-LMF) from IPUMS  |  Register now

• When: October 14, 2026, 10:00 am - 1:00 pm ET
• Organizer: Julia Drew, University of Minnesota, Twin Cities
• Description: The mission of IPUMS (ipums.org) is to democratize access to data by allowing researchers to leverage publicly available datasets to answer a broad range of topics. This workshop will introduce harmonized IPUMS versions of the National Health Interview Survey (NHIS) (available at nhis.ipums.org), including linkages between the NHIS and the National Death Index (NDI). The NHIS is the leading source of information on the health of the US population. It covers health status and behaviors, health care access, and sociodemographic characteristics such as age, sex, race/ethnicity, sexual orientation, and immigration status. The National Center for Health Statistics, which collects the NHIS, has linked NHIS survey records to the NDI, a digital repository of all death certificates from local vital statistics offices, to create a data resource known as the Linked Mortality File (LMF). Survey linked mortality data such as the LMF fill a critical knowledge gap about the correlates of mortality.

  In this workshop, we will first introduce the IPUMS NHIS data, focusing on our harmonization approach and the mortality variables derived from the LMF. We will then overview the demographic groups historically included/excluded from official mortality statistics and discuss how linked population survey-death certificate data can fill in gaps in official mortality statistics and address broader mortality-related questions. Last, we will lead workshop participants through a hands-on activity of calculating mortality statistics using the harmonized NHIS-LMF data from IPUMS.

Randomized Controlled Trials (RCTs) in Population and Reproductive Health: From Research Design to Policy Impact  |  Register now

• When: October 15, 2026, 10:00 am - 1:00 pm ET
• Organizer: Zubaria Andlib, RCTXImpact
• Description: Randomized controlled trials (RCTs) have become one of the most influential research designs for generating causal evidence in population health, reproductive health, family planning, maternal and child health, and public policy. Despite their growing importance, many population researchers have limited formal training in designing, implementing, analyzing, and reporting RCTs.

  This interactive three-hour virtual workshop provides a practical introduction to conducting high-quality RCTs in population and reproductive health research. Participants will learn how to formulate research questions, design randomized interventions, calculate sample sizes, manage implementation challenges, analyze treatment effects, address attrition and non-compliance, and interpret findings for academic publication and policy decision-making.

  Using real-world examples from fertility, maternal health, family planning, adolescent health, digital health, behavioral interventions, and social protection programs, participants will gain practical tools that can immediately be applied to their own research. The workshop combines lectures, case studies, interactive discussions, and live demonstrations using Stata and R. By the end of the workshop, participants will have a clear roadmap for designing an RCT and developing a publication-quality research paper suitable for submission to leading journals in population and reproductive health.

Whose Data Counts? Improving Demographic Data Quality and Use Through Participatory Measurement  |  Register now

• When: October 20, 2026, 1:00 - 4:00 pm ET
• Organizer: Susan Jenkins, Data Foundation
• Description: Accurate and respectful measurement of demographic information is fundamental to high-quality population research, yet researchers increasingly face challenges related to population diversity, multiracial and multiethnic identities, measurement error, and the demand for more detailed demographic data. This interactive workshop explores how demographic classification decisions, question design, and analytic approaches influence data quality, validity, comparability, and the usefulness of research findings.
  
  

  Participants will learn practical strategies for improving demographic data collection and analysis through respondent-centered design, participatory measurement approaches, and thoughtful use of disaggregated and intersectional analyses. Through case studies, hands-on exercises, and group discussions, attendees will examine sources of measurement error, redesign demographic questions, evaluate analytic tradeoffs, and develop approaches for transparent and responsible interpretation of demographic findings.
  
  Participants will leave with tools and frameworks that can be applied immediately to strengthen demographic measurement, reduce misclassification, improve analytic validity, and produce more accurate, useful, and policy-relevant population statistics.

Nonparametric Decompositions in Stata with Applications to the Demographic and Health Surveys  |  Register now

• When: October 28, 2026, 1:00 - 4:00 pm ET
• Organizer: Diane Coffey, University of Texas, Austin
• Description: This workshop will cover Kitagawa and the DiNardo, LeMieux, Fortin (Econometrica, 1996) reweighting decompositions using examples from Demographic and Health Survey Data.  Such decompositions are best suited to research questions of the form: Group A differs from Group B in the distribution/mean/other statistic of variable X.  How much of that difference in X remains if we match/hold constant/account for the difference in variable(s) Y (and Z)?  Kitagawa decompositions allow the researcher to transparently decompose a difference in means into two components; DLF decompositions allow researchers to decompose differences in a wider set of statistics (such as distributions) and to account for a larger number of explanatory variables.  We will contrast the methods with the Oaxaca-Blinder decomposition but not cover the latter in depth.
  The workshop will discuss several examples in which the presenters and co-authors have applied nonparametric decomposition methods to Demographic and Health Survey data to understand differences in health outcomes.  Among other examples, we will show that differences in infant mortality can across social groups in India can be explained by sanitation exposure, and that differences in neonatal mortality between babies born in different facility types in India cannot be explained by factors related to the risk profile of the birth.  We will present Stata .do files for the examples we discuss and make them available to participants.  We will invite participants to share their own research questions to consider these methods’ suitability for answering those questions.