Towards reliable empirical evidence in methodological biostatistical research: recent developments and remaining challenges

Wednesday, January 10, 2024 15:30to16:30

Anne-Laure Boulesteix

Ludwig Maximilian University (LMU) of Munich

WHEN: Wednesday, January 10, 2024, from 3:30 to 4:30 p.m.

WHERE: Hybrid | 2001 McGill College, Rm 1140 | Zoom

Note: Dr. Anne-Laure Boulesteix will present from Munich


Statisticians are often keen to analyze the statistical aspects of the so-called “replication crisis in science“. They condemn fishing expeditions and publication bias across empirical scientific fields applying statistical methods, such as health sciences. But what about good practice issues in their own - methodological - research, i.e. research considering statistical (or more generally, computational) methods as research objects? When developing and evaluating new statistical methods and data analysis tools, do statisticians and data scientists adhere to the good practice principles they promote in fields which apply statistics and data science? I argue that methodological researchers should make substantial efforts to address what may be called the replication crisis in the context of methodological research in statistics and data science, in particular by trying to avoid bias in comparison studies based on simulated or real data. I discuss topics such as publication bias, cherry-picking, and the design and necessity of neutral comparison studies, and review recent positive developments towards more reliable empirical evidence in the context of methodological biostatistical research.

Speaker bio

Anne-Laure Boulesteix obtained a diploma in engineering from the Ecole Centrale Paris, a diploma in mathematics from the University of Stuttgart (2001) and a PhD in statistics (2005) from the Ludwig Maximilian University (LMU) of Munich. After a postdoc phase in medical statistics, she joined the Medical School of the University of Munich as a junior professor (2009) and professor (2012). She is working at the interface between biostatistics, machine learning and medicine with a particular focus on metascience and evaluation of methods. She is a steering committee member of the STRATOS initiative, founding member of the LMU Open Science Center and president of the German Region of the International Biometric Society.

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