Andrew Merceris a senior research methodologist at Pew Research Center. He is an expert on nonprobability survey methods, survey nonresponse and statistical analysis, and his research focuses on methods of identifying and correcting bias in survey samples, as well as on the use of machine learning for survey data. He leads the Center’s research on nonprobability samples and co-authored several reports and publications on the subject. He has also authored blog posts and analyses making methodological concepts such as margin of error and oversampling accessible to a general audience. Prior to joining the Center, Mercer was a senior survey methodologist at Westat. He received a bachelor’s degree in political science from Carleton College and master’s and doctoral degrees in survey methodology from the University of Maryland. His research has been published in Public Opinion Quarterly and the Journal of Survey Statistics and Methodology.