About Me
I'm a clinical statistician in the San Francisco Bay Area.
I began my industry career in 2006 as a research statistician at Abbott Labs (now AbbVie), focusing on the statistical aspects of clinical pharmacology in drug development. I consider myself incredibly fortunate to have had this experience, as many fellow statisticians never have the opportunity to work specifically on early-phase clinical studies in their entire careers. My industry journey continued into late-phase drug development after I joined Allergan (now AbbVie) in 2010. Since then, I have worked at Amgen and various small biotech firms in the San Francisco Bay Area. My industry experience spans several therapeutic areas, notably hepatology, oncology and ophthalmology.
I received my Ph.D. in statistics from the University of Illinois at Chicago and completed my bachelor’s and master’s degrees in mathematics at Beijing Normal University.
Expertise & Research Interests
Expertise/Research Interests
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Adaptive designs: group sequential, adaptive sample size (event number) re-estimation, Bayesian adaptive MTD dose-finding (phase I oncology), and Bayesian adaptive randomization, etc.
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Linear mixed-effects models and repeated measurements
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Optimal crossover designs
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Phase II dose-finding designs under model uncertainty
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Statistical modeling and simulations (including Bayesian approaches)
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Selected Publications
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​Yan, Z, Yang, M (2024). Statistical considerations in model-based dose finding for binary responses under model uncertainty. Statistics in Medicine 43 (12), 2472-2485.
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Yan, Z (2013). The impact of baseline covariates on the effciency of statistical analyses of crossover designs. Statistics in Medicine 32 (6), 956-963.
About This Blog
I’ll share my insights and perspectives on statistical topics that I find interesting. While the subjects will vary, my primary focus will be on statistical concepts, methodologies, and their practical applications, occasionally touching upon regulatory guidelines. When possible, I'll also tackle some controversial issues, despite potential challenges.
This blog aims to enhance the understanding of statistics and its applications in drug development. I'll prioritize statistical rigor and practical relevance while avoiding any "inspirational" but meaningless fluff.
It's hard to predict how often I'll be blogging, but I'm committed to sharing new content as much as possible.