Pamela A. Shaw, PhD, MS


“My research focuses on the development of statistical methods for the proper design and analysis of clinical trials and complex epidemiologic investigations. Specific areas of interest include survival analysis, methods to address measurement error, infectious disease, aging research, cancer, and physical activity and nutritional epidemiology.”

Pamela A. Shaw, PhD, MS

Senior Biostatistics Investigator, Kaiser Permanente Washington Health Research Institute


Pamela Shaw, PhD, MS, is a biostatistician with expertise in clinical trials, design and analysis of complex epidemiologic studies, measurement error, and survival analysis. Dr. Shaw’s current statistical research includes a focus on methodology to correct for covariate and outcome measurement error, with application to studies reliant on electronic health records and large observational cohort studies.  She is currently applying these methods to study the relationship between maternal weight trajectories during pregnancy and early childhood outcomes, as well as to identify risk factors for poor outcomes in several cohorts of patients with HIV/AIDS.

Dr. Shaw is also involved in studies of aging, behavioral intervention studies, and the use of biomarkers to calibrate self-reported nutritional intake and physical activity. She is co-investigator in a clinical trial that will assess whether an anti-inflammatory diet can improve cognition in a middle-aged (40- to 65-year-old) multi-ethnic urban population relative to a usual diet. She is an investigator for the Adult Changes in Thought (ACT) study, a joint project between Kaiser Permanente Washington Health Research Institute and the University of Washington that focuses on risk factors for dementia, including Alzheimer's disease, and declines in memory and thinking. For this study, she is collaborating with other ACT investigators to understand the best way to quantify patterns of physical activity in the 24-hour day and its association with health outcomes.

Before joining KPWHRI as a senior investigator, Dr. Shaw was an associate professor of biostatistics in the University of Pennsylvania Perelman School of Medicine. At UPenn she taught in the biostatistics graduate program and was the lead statistician for several early phase clinical trials, including studies of CART19, a novel CAR T cell immune therapy for the treatment of acute lymphocytic leukemia and other blood cancers, as well as clinical trials that evaluated the efficacy of behavioral economic interventions to increase healthy behaviors.  She co-authored the textbook Essentials of Probability Theory for Statisticians (CRC Press 2016).

Prior to UPenn, she was a mathematical statistician in the Biostatistics Research Branch at the National Institute of Allergy and Infectious Diseases, where she was lead statistician for several clinical and basic science studies of human infectious and immunologic disease.

Dr. Shaw is an adjunct associate professor in the Department of Biostatistics, Epidemiology and Informatics at the University of Pennsylvania and an affiliate professor in the Department of Biology and Wildlife at the University of Alaska Fairbanks. She is associate editor for Statistics in Medicine. She serves as a member for several clinical trial data safety monitoring boards and as a member of the Bone, Reproductive and Urologic Drugs Advisory Committee for the U.S. Food and Drug Administration. She is a member of the International Biometric Society and fellow of the American Statistical Association.

She completed a Bachelor of Arts in mathematics and French at Grinnell College, and a Master of Science in mathematics and a doctorate in biostatistics at the University of Washington.

Recent Publications

Duan R, Liang CJ, Shaw PA, Tang CY, Chen Y. Testing the missing at random assumption in generalized linear models in the presence of instrumental variables.  Scand Stat Theory Appl. 2024;51(1):334-354. doi: 10.1111/sjos.12685. Epub 2023 Aug 7.  PubMed

Boe LA, Shaw PA. An augmented likelihood approach for the Cox proportional hazards model with interval-censored auxiliary and validated outcome data-with application to the Hispanic Community Health Study/Study of Latinos.  Stat Methods Med Res. 2023 Jun 29:9622802231181233. doi: 10.1177/09622802231181233. [Epub ahead of print]. PubMed

Boe LA, Mossavar-Rahmani Y, Sotres-Alvarez D, Daviglus ML, Durazo-Arvizu RA, Thyagarajan B, Kaplan RC, Shaw PA. Nutritional blood concentration biomarkers in the Hispanic Community Health Study/Study of Latinos: Measurement characteristics and power. Am J Epidemiol. 2023 Apr 27;kwad109. doi: 10.1093/aje/kwad109. Online ahead of print. PubMed

Boe LA, Shaw PA, Midthune D, Gustafson P, Kipnis V, Park E, Sotres-Alvarez D, Freedman L, Of The Stratos Initiative OBOTMEAMTGT. Issues in implementing regression calibration analyses. Am J Epidemiol. 2023 Apr 21:kwad098. doi: 10.1093/aje/kwad098. [Epub ahead of print]. PubMed

Teitelman AM, Tieu HV, Chittamuru D, Shaw PA, Nandi V, Davis A, Lipsky RK, Darlington CK, Fiore D, Koblin BA. A randomized controlled pilot study of Just4Us, a counseling and navigation intervention to promote oral HIV prophylaxis uptake among prep-eligible cisgender women. AIDS Behav. 2023 Sep;27(9):2944-2958. doi: 10.1007/s10461-023-04017-z. Epub 2023 Mar 4. PubMed


Healthy findings blog


HIV/AIDS research advances through Pamela Shaw's work

Shaw's project to reduce the impact of errors in data was just honored with an NIH MERIT award.

New funding

Senior male patient with doctor in exam room

Grant of over $55M to boost Alzheimer’s, dementia study

Kaiser Permanente Washington will co-lead an expanded ACT Program to better understand the aging brain.


illustration nurse and patient mammogram

Roundup of 3 recent studies on breast cancer screening

New research spotlights overdiagnosis, MRI before surgery, and a new way of predicting breast cancer risk