Shaw-Shepherd Research Collaborative
Lotspeich S, Shepherd BE, Amorim G, Shaw PA, Tao R. Efficient odds ratio estimation under two-phase sampling using error-prone data from a multi-national HIV research cohort. Biometrics 2021 July; Epub ahead of print.
Boe LA, Tinker LF, Shaw PA: An Approximate Quasi-Likelihood Approach for Error-Prone Failure Time Outcomes and Exposures. Statistics in Medicine (in press). Pre-Print
Giganti MJ, Shepherd BE. Multiple imputation variance estimation in studies with missing or misclassified inclusion criteria. American Journal of Epidemiology 2020; 189: 1628-1632.
Chen T, Lumley T. Optimal multiwave sampling for regression modeling in two-phase designs. Statistics in Medicine 2020 12 30; 39 (30) 4912-4921. PDF
Amorim G, Tau R, Lotspeich SC, Shaw PA, Lumley T, Shepherd BE. Two-Phase Sampling Designs for Data Validation in Settings with Covariate Measurement Error and Continuous Outcome. Journal of the Royal Statistical Society, Series A (in press)
Oh E, Shepherd BE, Lumley T, Shaw PA: Improved Generalized Raking Estimators to Address Dependent Covariate and Failure-Time Outcome Error. Biometrical Journal. 2021 Jun; 63(5):1006-27. PDF
Baldoni P, Sotres-Alvarez D, Lumley TS, Shaw PA. On the use of Regression Calibration in a Complex Sampling Design with Application to the Hispanic Community Health Study/Study of Latinos. American Journal of Epidemiology, 2021 July; 190(7): 1366–1376. PDF
Oh EJ, Shepherd BE, Lumley T, Shaw PA. Raking and regression calibration: Methods to address bias from correlated covariate and time-to-event error. Statistics in Medicine. 2021;40(3):631–649. [PDF]
Tau R, Lotspeich SC, Shaw PA, Shepherd BE. Efficient semiparametric inference for two-phase studies with outcome and covariate measurement errors. Statistics in Medicine, 2021; 40(3):725–738.
Han K, Lumley T, Shepherd BE, Shaw PA: Two-phase analysis and study design for survival models with error-prone exposures. Statistical Methods in Medical Research, 2020 Dec 16. [PDF]
Shepherd BE, Shaw PA. Errors in multiple variables in HIV cohort and electronic health record data: statistical challenges and opportunities. Statistical Communications in Infectious Disease, 2020; 12 (s1), [PDF]
Shaw PA, He J, and Shepherd B. Regression calibration to correct correlated errors in outcome and exposure. Statistics in Medicine, 2021; 40(2): 271-286. [PDF]
Illenberger N, Small DS, and Shaw PA. Understanding regression to the mean in the context of synthetic controls and other matched difference in difference methods. Epidemiology 2020; 31(6):815-22. [PDF]
Giganti MJ, Shaw PA, Chen G, Bebawy SS, Turner MM, Sterling TR, Shepherd BE: Accounting for dependent errors in predictors and time-to-event outcomes using validation samples and multiple imputation Annals of Applied Statistics 2020;14(2):1045-61.
Keogh RH, Shaw PA, Gustafson P, Carroll RJ, Deffner V, Dodd KW, Küchenhoff H, Tooze JA, Wallace MP, Kipnis V, Freedman LS. STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part I – basic theory, validation studies and simple methods of adjustment. Statistics in Medicine 2020 Jul 20;39(16):2197-2231. [PDF]
Shaw PA, Gustafson P, Carroll RJ, Deffner V, Dodd KW, Keogh RH, Kipnis V, Tooze JA, Wallace MP, Küchenhoff H, Freedman LS. STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part II –more complex methods of adjustment and advanced topics. Statistics in Medicine 2020 Jul 20;39(16):2232-2263. [PDF]
Shepherd B, Shaw PA and Dodd L. Using audit Information to adjust parameter estimates for data errors in clinical trials. Clinical Trials, 2012 Dec; 9(6): 721-729.
Yang JB, Shepherd BE, Lumley T, Shaw PA. Optimum Allocation for Adaptive Multi-Wave Sampling in R: The R Package optimall. Preprint arXiv:2106.09494. 2021 Jun 17. PDF
Han K, Shaw PA, Lumley T. Combining multiple imputation with raking of weights in the setting of nearly-true models. Preprint arXiv:1910.01162 [stat.ME]. PDF