About the faculty


Paul Dickman
is Professor of Biostatistics at the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet. He conducts research in epidemiology and biostatistics with a focus on cancer epidemiology and register-based epidemiology. Professor Dickman has long been interested in the analysis of cancer patient survival, the topic of his 1997 doctoral thesis where he studied with Professor Timo Hakulinen. His primary interests lie in statistical methods for estimating and modelling relative survival. He has published widely in the field of cancer patient survival, is a coauthor of the Stata strs command for estimating and modelling relative survival, and taught courses in cancer survival analysis in eight different countries.

 

Paul Lambert is Professor of Biostatistics in the Department of Health Sciences at the University of Leicester. Paul currently is seconded (30% FTE) to the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet. Paul's main research interest has been in developing methods for modelling relative survival. In particular modelling time-dependent covariate effects, incorporating period analysis in statistical models, and the estimation and modelling of 'cure' in population-based cancer studies. He is particularly keen on the use of flexible parametric survival models for both standard and relative survival. These offer a number of advantages in terms of communication of results, for example quantifying absolute levels of risk as well as relative risk. He has developed software in Stata to fit cure models for relative survival (strsmix and strsnmix) and also flexible parametric models (stpm2). Paul is coauthor of the book Flexible Parametric Survival Analysis Using Stata: Beyond the Cox Model.

 

Teaching assistants

Sandra Eloranta is a biostatistician at the Clinical Epidemiology Unit at the Department of Medicine, Karolinska Institutet, and a senior statistical advisor at Scandinavian Development Services. She did her PhD training at the Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet on the topic of statistical methods for estimating population-based cancer patient survival. The main focus of her PhD work was on developing methods for studying excess mortality among cancer patients from causes other than cancer in a competing risk setting. Sandra's main research interests today are patient survival and survivorship issues after hematological malignancies. She has co-authored more than 40 scientific papers on cancer survival and is an experienced teacher; for example, she is a regular teacher at the Clinical Research Schools for oncologists, psychiatrists and odontologists at Karolinska Institutet. Among other teaching activities she has been been teaching and organising courses on survival analysis for epidemiologists, statistical methods for cancer patients survival, competing risks and real-world evidence studies. Sandra will teach a 1-day course on Survival Analysis with Competing Risks with Stata® on the Sunday prior to the course.

Michael Crowther is a post-doctoral biostatistician, currently with a joint position at the Department of Health Sciences, University of Leicester, and the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet. His PhD thesis centred on the development of methods for the analysis of survival data and joint longitudinal-survival data, with a focus on flexible and parametric frameworks. He has also developed methods for simulating complex survival data. He has first authored 12 methodological papers in the areas of survival analysis, joint longitudinal-survival analysis and meta-analysis, including articles describing user friendly Stata® software, allowing the methods to be directly used in practice. He has experience in teaching at the postgraduate level, developing and running short courses on joint modelling and in the design of simulation studies for evaluating statistical methods. He is currently working in the areas of multi-state models and multilevel relative survival analysis. Michael will teach a 1-day course on Joint Models for Longitudinal and Survival Data with Stata® on the Sunday prior to the course.

Hannah Bower is a doctoral student in the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet under the supervision of Paul Lambert. Her PhD focuses on developing and applying a survival measure called the loss in expectation of life. This involves modelling relative survival from population-based registry data using flexible parametric survival models. She has been a teaching assistant for the course `Statistical methods for population-based cancer survival analysis’ in 2015, and for the doctoral course `Survival analysis for epidemiologists’ at Karolinska Institutet.