Statistics in Medicine

Statistics in Medicine Welcomes New Editor-in-Chief

Statistics in Medicine is pleased to welcome Rebecca Betensky as a new member of our editorial team. Dr. Betensky joins Robert Platt, Nigel Stallard, Ben Van Calster and Paul Albert (Tutorials Editor) as an Editor-in-Chief on the journal. Dr. Betensky replaces Lisa McShane, whose term as an Editor-in-Chief ended in 2024. Wiley and the entire Statistics in Medicine editorial team would like to thank Lisa for her service, leadership and dedication to the journal.

Dr. Betensky is Professor of Biostatistics and Chair of the Biostatistics Department at the New York University School of Global Public Health. Prior to joining NYU, she was Professor of Biostatistics at the Harvard T. H. Chan School of Public Health and Biostatistician at Massachusetts General Hospital. Her research focuses on methods for survival data, design of clinical trials, biomarker discovery, and multiple testing. Much of her work is motivated by problems that arise in her collaborations in Alzheimer’s disease, multiple sclerosis, and multiple system atrophy. Dr. Betensky is the statistical editor of Annals of Neurology and a statistical reviewer for New England Journal of Medicine Evidence.

Statistics in Medicine Welcomes New Tutorials Editor

Statistics in Medicine is pleased to welcome Paul Albert as the newest member of our editorial team. Dr Albert joins Robert Platt, and Nigel Stallard and Ben Van Calster as the Tutorials Editor on the journal. 

Dr Albert has 35 years of experience at the National Institutes of Health holding scientific and leadership positions at different institutes. He currently is Director and Senior Investigator of the Biostatistics Branch in the Division of Cancer Epidemiology and Genetics at the National Cancer Institute.  In this capacity, he leads a research group with 12 principal investigators and between 15-20 post-doctoral, pre-doctoral, and post-bac fellows. His personal research focuses on methods development for biomarker and longitudinal studies and their application to cancer epidemiology. He leads work on the development and application of hidden Markov models in cancer epidemiology and genetics, and on the development of novel methodology for analyzing chemical mixture data and its application to population-based cancer studies. He continues to have an active research agenda in the use of group-testing methodology with applications to clinical medicine and epidemiological research. Dr Albert has been an associate editor for major journals in biostatistics including Statistics in Medicine, Biometrics, and Statistics in the Biosciences. Until recently, he was co-section editor for biometrical methodology in the New England Journal of Statistics in the Data Sciences. He serves as a statistical editor of the American Journal of Obstetrics and Gynecology.

Statistics in Medicine Welcomes New Editor-in-Chief

Statistics in Medicine is pleased to welcome Ben Van Calster as a new member of our editorial team. Dr Van Calster joins Robert Platt, and Nigel Stallard as an Editor-in-Chief on the journal. Dr Van Calster replaces Els Goetghebeur who retired as an Editor-in-Chief in 2022. Wiley and the entire Statistics in Medicine editorial team would like to thank Els for her service, leadership and dedication to the journal. 

Ben Van Calster, PhD, is Associate Professor at KU Leuven (Department of Development and Regeneration) and Leiden University Medical Center (Department of Biomedical Data Sciences). He is also the statistician of the Research Ethics Committee of the University Hospitals KU Leuven. He obtained an MA in Psychology, MSc in Statistics, and PhD in Engineering (Biomedical Data Processing), all from KU Leuven. He was visiting professor at the Erasmus Medical Center in Rotterdam and at Boston University. Dr. Van Calster serves on the Editorial Board of Medical Decision Making, and is Associate Editor of Diagnostic and Prognostic Research. He is a member of the STRATOS initiative, where he is co-chair of the Topic Group on ‘Evaluating Diagnostic Tests and Prediction Models’.

His statistical research deals with methods to develop and validate prediction models based on regression and machine learning algorithms, with focus on calibration, decision curve analysis, and multinomial outcomes. On the applied side, he develops and validates prediction models to diagnose ovarian malignancy, ectopic pregnancy, and other gynecological outcomes. He is the statistician of the International Ovarian Tumor Analysis (IOTA) consortium (www.iotagroup.org), and developer of the ADNEX and M6 models. He also works on research quality and reporting.