Rate My Professor Ton de Waal

De Waal's research specializations encompass statistical data editing, imputation methods under edit restrictions, integration of data from multiple sources, correction of sample selection bias in big data and nonprobability samples, statistical disclosure control, and quality measures for multisource statistics. He has authored or co-authored key works such as the Handbook of Statistical Data Editing and Imputation (2011, Wiley), Elements of Statistical Disclosure Control (2001, with Leon Willenborg), Multi‐source Statistics: Basic Situations and Methods (2020), Correcting Selection Bias in Big Data by Pseudo-Weighting (2023, with An-Chiao Liu and Sander Scholtus), and recent contributions including the preface to a special issue on integrating data from multiple sources (2025, Journal of Official Statistics) and papers on pseudo-weighting variance and performance measures for bias correction. With over 40 journal articles, three books, three reports, and chapters to his name, de Waal's publications have garnered substantial citations and shaped methodologies employed by statistical offices globally. His influence extends to international forums through keynotes, webinars, and coordination of sections in the International Association of Survey Statisticians.