Manisha Desai

Manisha Desai, PhD, Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science, Stanford University School of Medicine


Research Description: Dr. Desai is the founder and director of the Stanford Quantitative Sciences Unit (QSU), a biostatistical unit created in 2009 of over 20 faculty, PhD-, and Masters-level staff to provide the statistical infrastructure for large-scale research projects at the School of Medicine. The group maintains a portfolio of over 50 projects.  Prior to her appointment at Stanford, Dr. Desai was a member of the faculty in the Department of Biostatistics at Columbia University from 2000 to 2009, where she advised students, mentored junior faculty and collaborated with investigators at the Herbert Irving Comprehensive Cancer Center in the design and analysis of studies. She was also co-Director of the Cancer Epidemiology and Biostatistics Training Program and served as PI on the Biostatistics Core for a U54 Partnership award between Columbia University and Long Island University. In her position at Stanford, she leads the statistical studies on a variety of medical studies that pose methodological challenges. The areas of her statistical expertise include the handling of missing data, the modeling of correlated data, the design of clinical studies, and methods for analyzing epidemiologic studies. Dr. Desai collaborates with multiple Stanford DRC members listed below. Dr. Desai will serve as associate director of the Clinical & Translational Core, where she will provide biostatistical and data management support for the Stanford DRC.

Selected relevant publications (Stanford DRC Members in BOLD):

  1. LeBlanc ES, Waring M, Kapphahn K, Stefanick M, Desai M, Parikh N, Robinson J, Liu S, Anderson
  2. M, Parker D, Aroda V, Sullivan S, Woods N, Lewis C. Reproductive history and risk of type 2 diabetes mellitus in postmenopausal women: Findings from the Women's Health Initiative. Menopause 2016. Jul 25 [Epub ahead of print] PMID:27465714
  3. Desai M, Pieper K, Mahaffey K. Challenges and Solutions to Pre- and Post-Randomization Subgroup Analyses.  Curr Cardiol Rep 16(10):531, 2014.
  4. Desai M, Bryson SW, Robinson T. On the use of robust estimators for standard errors in the presence of clustering when clustering membership is misspecified. Contemp Clin Trials 2013; 34(2):248-56.
  5. Robinson TN, Matheson D, Desai M, Wilson DM, Weintraub DL, Haskell WL, McClain A, McClure S, A Banda J, Sanders LM, Haydel KF, Killen JD. Family, community and clinic collaboration to treat overweight and obese children: Stanford GOALS-A randomized controlled trial of a three-year, multi-component, multi-level, multi-setting intervention. Contemp Clin Trials 36(2):421-435, 2013.