Nandita Mitra, Ph.D.

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Professor of Biostatistics in Biostatistics and Epidemiology at the Hospital of the University of Pennsylvania
Department: Biostatistics and Epidemiology
Graduate Group Affiliations

Contact information
Department of Biostatistics and Epidemiology
University of Pennsylvania Perelman School of Medicine
622 Blockley Hall, 423 Guardian Drive
Philadelphia, Pa 19104
Office: 215-573-4467
Fax: 215-573-4865
Education:
AB (Mathematics)
Brown University, 1992.
MA (Biostatistics)
University of California at Berkeley, 1996.
PhD (Biostatistics)
Columbia University, 2001.
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Selected Publications

Mitra N, Indurkhya A: A propensity score approach to estimating the cost-effectiveness of medical therapies from observational data. Health Economics 14(8): 805-815, August 2005.

Indurkhya A, Mitra N, Schrag D: Using propensity scores to estimate the cost-effectiveness of medical therapies. Statistics in Medicine 25(9): 1561-1576, May 2006.

Handorf EA, Bekelman JE, Heitjan DF, Mitra N: Evaluating costs with unmeasured confounding: A sensitivity analysis for the treatment effect. Annals of Applied Statistics 7(4): 2062-2080, December 2013.

Li Jiaqi, Handorf E, Bekelman J, Mitra N: Propensity score and doubly robust methods for estimating the effect of treatment on censored cost. Statistics in Medicine 35(12): 1985-1999, May 2016.

Li J, Vachani A, Epstein A, Mitra N: A doubly robust approach for cost-effectiveness estimation from observational data. Statistical Methods in Medical Research Jan 2017 Notes: 962280217693262. doi: 10.1177/0962280217693262. [Epub ahead of print]

Spieker A, Roy J, Mitra N: Analyzing medical costs with time-dependent treatment: The nested g-formula. Health Economics 27(7): 1063-1073, Jul 2018.

Handorf EA, Heitjan DF, Bekelman JE, Mitra N: Estimating cost-effectiveness from claims and registry data with measured and unmeasured confounders. Statistical Methods in Medical Research Jan 2018 Notes: DOI: 10.1177/0962280218759137. [Epub ahead of print]

Venkatraman ES, Mitra N, Begg CB: A method for evaluating the impact of individual haplotypes on disease incidence in molecular epidemiology studies. Statistical Applications in Genetics and Molecular Biology 3: article 27, October 2004.

Zhao H, Rebbeck TR, Mitra N: A propensity score approach to correction for bias due to population stratification using genetic and non-genetic factors. Genetic Epidemiology 33(8): 679-690, December 2009.

Mitra N, Heitjan DF: Sensitivity of the hazard ratio to nonignorable treatment assignment in an observational study. Statistics in Medicine 26(6): 1398-1414, March 2007.

French B, Lumley T, Cappola TP, Mitra N: Non-iterative, regression-based estimation of haplotype associations with censored survival outcomes. Statistical Applications in Genetics and Molecular Biology 11(3): 1-22, February 2012.

Zhao H, Rebbeck TR, Mitra N: Analyzing genetic association studies with an extended propensity score approach. Statistical Applications in Genetics and Molecular Biology 11(5): 1544-6115, October 2012.

Zhu Y, Ghosh D, Mitra N, Mukherjee B: A data-adaptive strategy for inverse weighted estimation of causal effects. Health Services and Outcomes Research Methodology 14(3): 69-91, Sep 2014.

Wan F, Small D, Bekelman J, Mitra N: Bias in estimating the causal hazard ratio when using two-stage instrumental variable methods. Statistics in Medicine 34(14): 2235-65, Jun 2015.

Wan F, Mitra N: An evaluation of bias in propensity score-adjusted non-linear regression models. Statistical Methods in Medical Research 3(27), Mar 2018 Notes: 2016 Apr 19. pii: 0962280216643739. [Epub ahead of print]

Kennedy EH, Kangovi S, Mitra N: Estimating scaled treatment effects with multiple outcomes. Statistical Methods in Medical Research Jan 2017 Notes: DOI:10.1177/0962280217747130. [Epub ahead of print]

Wan F, Small D, Mitra N: A general approach to evaluating the bias of 2-stage instrumental variable estimators. Statistics in Medicine 37(12): 1997-2015, May 2018.

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Last updated: 05/30/2019
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