Frontiers in Biostatistics Seminar
Tuesday January 16, 2023 @ 1pm ET
Center for Life Sciences Building, Room 11081
Roderick Little, PhD
Richard D. Remington Distinguished University Professor of Biostatistics
Professor, Department of Statistics
Research Professor, Institute for Social Research
University of Michigan School of Public Health
Abstract: I review methods for handling missing data in empirical studies. I define missing data, provide a taxonomy of main approaches to analysis, including complete-case and available-case analysis, weighting, maximum likelihood (ML), Bayes, single and multiple imputation (MI), and augmented inverse-probability weighting (AIPW). Assumptions about the missingness mechanism are key to the performance of alternative methods; I define missingness mechanisms, which play a key role in the performance of methods. Approaches to robust inference, and to inference when the mechanism is potentially missing not at random, are discussed. I’ll also discuss recent developments in the treatment of missing data in interventional studies, as evidenced by the International Council for Harmonization E9 Addendum on estimands.
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