[1] von Davier's research focuses on developing advanced psychometric models and methodologies for analyzing complex educational and survey data.
[14] von Davier obtained a master's degree in psychology with honors from the Faculty of Mathematics and Science (Mathematisch-Naturwissenschaftlichen Fakultät) at CAU Kiel University in 1993.
[15] von Davier's career began as an Assistant Research Scientist at the Institute for Science Education (IPN) at Kiel University.
He then was awarded a Postdoctoral Fellowship at Educational Testing Service (ETS) in Princeton, NJ, where he developed item fit measures for complex IRT models.
[16] In 2004, von Davier became a Senior Research Scientist at the Center for Global Assessment in Princeton, where he led initiatives focused on evaluating outcomes-based models.
[29][30][40] von Davier has authored and co-authored over 150 publications in peer-reviewed journals, edited books, monographs, and research report series.
Allan S. Cohen commented in the Journal of the American Statistical Association, "This book, published in honor of the retirement of Jürgen Rost, is an edited volume of 22 invited chapters written by eminent researchers in the field of item response theory (IRT).
The three editors have done an excellent job identifying a group of prominent scholars whose expertise ranges from international testing and behavioral statistics to educational policy.
"[43] Alongside Randy E. Bennett, von Davier published Advancing Human Assessment: The Methodological, Psychological and Policy Contributions of ETS in 2017, detailing the advancements in human assessment made by ETS, covering measurement and statistics, education policy, psychology, and the development of widely used educational surveys and methodologies.
"[44] In his highly cited studies, von Davier wrote the practices researchers can use for analyzing and reporting data from large-scale international assessments, addressing common issues and statistical complexities to ensure unbiased results.
[45] He emphasized the importance of correctly using plausible values in large-scale survey data analysis to avoid biased estimates and underscored the need to follow established procedures and guidelines.