Hosted by the GPH Department of Biostatistics
The scientific method has been undermined over the past two decades for lack of replicability, especially being a cross disciplinary crisis. Great efforts have been invested to study and enhance results’ replicability, starting with the study design, its implementation, through the development of analysis tools, and finally offering replicability metrics. Although the problems are the same across fields of science, the specific challenges and techniques are field-specific and therefore require special solutions per field.
In this talk, Dr. Iman Jaljuli, research scholar at Memorial Sloan Kettering, will discuss the cross-disciplinary crisis of a lack of replicability, with a specific focus on two fields. The first is experimentation with mouse models, which led to the need to develop a scheme for improved unbiased estimation of interaction variance in ANOVA models with unbalanced group sizes. The second is meta-analyses of clinical-trials, where the concern is about assessing replicability of intervention effects.
About the Speaker:
Dr. Iman Jaljuli has a PhD in Statistics from Tel-Aviv University under the supervision of Prof. Benjamini where she studied replicability in the field of animal phenotyping and clinical trials with focus on mixed-effects models, namely, linear-mixed models and meta-analyses. Dr. Jaljuli's current research focuses on developing statistical tools for assessing and enhancing study replicability in cancer research, with emphasis on high-dimensional genomics data. She is now working on developing decision rules for treatment allocation plans based on patient biomarkers.