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Abdus S Wahed, PhD

Professor, Biostatistics

Director of PhD Graduate Program, Biostatistics

Editor, Journal of Statistical Research

Contact

7136 Parran Hall, 130 DeSoto Street, Pittsburgh, PA 15261
R-znvy: jnurq@cvgg.rqh
Primary Phone: 967-179-8508
Web site:


Personal Statement

My current major research interest is in personalized medicine – development of statistical methods for testing dynamic treatment regimes (adaptive treatment strategies) through sequentially randomized designs, for screening viable treatment regimes from observational data, and for identifying important variables for forming dynamic treatment regimes. Other methodological research interest includes multivariate ordinal longitudinal data analysis, survival analysis in the presence of misclassified events, and analysis of variance for censored survival data, length biased data, and joint modeling of longitudinal and time-to-event data measured with error. My collaborative research interest includes development of multi-stage depression treatment regimes, sequential treatment decisions in depression treatment, development of risk scores for complications in bariatric surgery, analysis of outcomes in hepatitis B and C clinical trials and cohort studies, and weight loss in young adults.


Education

Ph.D., Statistics (2003), North Carolina State University, Raleigh, NC
M.A., Mathematical Statistics (2000), Ball State University, Muncie, IN
M.Sc., Statistics (1994), University of Dhaka, Bangladesh
B.Sc., Statistics (1992, Minor: Economics and Mathematics), University of Dhaka, Bangladesh


Teaching

Linear Models

Estimation Theory

Likelihood Theory


Selected Publications

1.     Sampene, E. and Wahed, AS. (2016). A Relatively Simple
Efficient Estimator for Relative Risk in Case-Cohort Studies. Journal of
Statistical Research 2016, Vol. 48-50, No. 2, pp. 37-54

2.     Yavuz, I, Cheng, Y, and Wahed, AS (2016).
Estimating the Cumulative Incidence Function of Dynamic Treatment Regimes.
Accepted, Journal of Royal Statistical Society, Series A.

3.     Xu, Y, Müller, P, Wahed, AS, and Thall, PF.
(2016). Bayesian Nonparametric Estimation for Dynamic Treatment Regimes with
Sequential Transition Times; Journal of the American Statistical Association
111 (515), 921-950.

4.     Marron, MM, and Wahed, AS (2016).
Teaching Missing Data Methodology to Undergraduates Using a Group-Based Project
Within a Six-Week Summer Program. Journal of Statistics Education 24 (1), 8-15.

5.     Jaman, A, Latif, AHMM, Bari, W, and Wahed, AS (2016).
A determinant-based criterion for working correlation structure selection in
generalized estimating equations. Statistics in Medicine. Volume 35, Issue 11,
20 May 2016, Pages 1819–1833.

6.     Ogbagaber, SB, Karp, J, and Wahed, AS 

(2016). Design of sequentially randomized trials for testing adaptive treatment
strategies. Early view, Statistics in Medicine. Volume 35, Issue 6, pp 840–858.

7.     Dong, X, Kong, L, and Wahed, AS (2016). Accelerated
failure time model for case-cohort design with longitudinal covariates subject
to measurement error and detection limits. Statistics in Medicine Volume 35,
Issue 8 pp 1327–1339.

8.     Tang, X, and Wahed, AS (2015). Pattern-mixture-type Estimation and Testing

of Neuroblastoma Treatment Regimes. Journal of Statistical Theory and Practice
Vol 9, Issue 2, pp 266-287.

9.     Huang, X, Ning, J, Wahed, AS (2014).

Optimization of individualized dynamic treatment regimes for recurrent
diseases. Statistics in medicine 33.14 (2014): 2363-2378.

10.  Kidwell, K, Ko, JH, and Wahed, AS (2014).
Inference for Median Residual Life under Sequentially Randomized Trials. Statistics
in medicine 33.9 (2014): 1503-1513.

11.  Adeniji, A, Belle, SH, and Wahed, AS
(2014). Incorporating Diagnostic Accuracy into the Estimation of Discrete
Survival Function. Journal of Applied Statistics. Volume 41, Issue 1, 2014, PP 60-72

For a complete list of publications, browse the faculty CV,  OrcID Profile, or visit google scholar page

Abdus S Wahed
© 2017 by University of Pittsburgh Graduate School of Public Health

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