Papers
- Wang, Colantuoni, Leroux, Scharfstein (2019): idem: An R Package for Inferences in Clinical Trials with Death and Missingness. Journal of Statistical Software. To Appear.
- Scharfstein and McDermott (2019): Global Sensitivity Analysis of Clinical Trials with Missing Patient Reported Outcomes. Statistical Methods in Medical Research, 28: 1439-1456.
- Colantuoni, Scharfstein, Wang, Hashem, Leroux, Needham, Girard (2018): Statistical Methods to Compare Functional Outcomes in RCTs with High Mortality. British Medical Journal, 360:j5748.
- Scharfstein, McDermott, Diaz, Carone, Lunardon and Turkoz (2018): Global Sensitivity Analysis for Repeated Measures Studies with Informative Dropout: A Semiparametric Approach. Biometrics, 74: 207-219.
- Scharfstein, Zhu and Tsiatis (2016): Survival Analysis Book Chapter
- Wang, Scharfstein, Colantuoni, Girard and Yan (2017): Inference in Randomized Trials with Death and Missingness. Biometrics, 73: 431-440.
- Scharfstein, Rotnitzky, Abraham, McDermott, Chaisson and Geiter (2015): On the Analysis of Tuberculosis Studies with Intermittent Missing Sputum Data. Annals of Applied Statistics, 9: 2215-2236.
- Kharazzi, Wang and Scharfstein (2014): Prospective EHR-Based Clinical Trials: The Challenge of Missing Data. Journal of General Internal Medicine, 29: 976-978.
- Scharfstein, McDermott, Olson and Weigand (2014): Global Sensitivity Analysis for Repeated Measures Studies with Informative Dropout: A Fully Parametric Approach. Statistics in Biopharmaceutical Research, 6: 338-348.
- Li, Hutfless, Scharfstein, Daniels, Hogan, Little, Roy, Law and Dickersin (2014): Standards should be applied in the prevention and handling of missing data for patient-centered outcomes research: a systematic review and expert consensus. Journal of Clinical Epidemiology 67(1):15-32. PubMed PMID: 24262770.