Addressing missing data in R: understudied contexts, lots of missingness, hundreds of variables by Mayari Montes de Oca Visit https://rstats.ai/nyr/ to learn more. Abstract: Mayarí will talk about the importance of addressing missing data and of her practical experience when handling the non-response from a longitudinal study with Syrian refugee populations. After a rapid overview of multiple imputation, she will talk about some of the main challenges of addressing non-response comprehensively for data that caters to multiple analyses and researchers; in contexts where little is known about the DGP of each variable, missing data is prevalent, and hundreds of potentially important features are collected. She will share some of the software and settings that were helpful throughout the process, such as the Boruta, randomForest, mice, and miceadds packages. Lastly, she will illustrate the importance of transparency in analysis results regarding the uncertainty brought in by the missing data. Bio: Mayarí Montes de Oca is an applied statistician passionate about using data to reduce poverty and opportunity gaps. Her efforts focus on addressing missing data and causal inference questions to generate robust impact evaluations of social interventions. Some of her main interests involve non-parametric techniques and Bayesian modeling to approach both missing data and causal inference problems. Mayarí holds a M.Sc. in Applied Statistics for Social Science Research (A3SR) from NYU Steinhardt, and a BA in Economics from the Center for Research and Teaching in Economics (CIDE). She worked at Global TIES for Children from 2016 to 2021 as a Research Scientist on the “Education in Emergencies: Evidence for Action” (3EA) project; where she also assembled and trained the organization’s first data processing and verification team, systems, and protocols. Before coming to New York she worked at the Mexican Ministry of Finance (SHCP), evaluating Public Health, and National Security projects. She has also served as a consultant on survey and missing data projects for New York University and for the City University of New York. Twitter: https://twitter.com/Mayari_MOca Presented at the 2021 New York R Conference (September 10, 2021)