Description:

Department of Statistics Spring 2019 Seminar Series

Talk Title: How non-ignorable is the selection bias in non-probability samples? An illustration of new measures using a large genetic study on Facebook

Speaker: Brady T. West, Research Associate Professor in the Survey Methodology Program, Survey Research Center at the Institute for Social Research, University of Michigan-Ann Arbor

Time: 11:00am

Abstract: Survey researchers are currently evaluating the utility of "big data" that are not selected by probability sampling. Existing indices of the degree of departure of non-probability samples from representative probability samples, such as the R-Indicator, are agnostic about the relationship between the inclusion probability and survey outcomes, which is crucial to understanding the risk of selection bias in non-probability samples. We describe simple model-based indices of the degree of departure from ignorable selection for estimates of means, proportions, and regression coefficients that correct this deficiency. We then use simulation studies to evaluate the ability of the proposed indices and other existing indices to detect non-ignorable selection bias. Finally, we apply the proposed indices to data from the Genes for Good project at the University of Michigan, which recruits a non-probability sample of study volunteers via Facebook, using genetic data from the Health and Retirement Study as a population benchmark.

Location: Department of Statistics, Room B02, 2006 Sheridan Rd, Evanston 60208