Dr. Robert Lyles is a Professor in the Department of Biostatistics and Bioinformatics in Emory University’s Rollins School of Public Health. He is currently Director of the Biostatistics and Bioinformatics Core of Emory’s Center for AIDS Research, and is a member of the Biostatistics, Epidemiology and Research Design Core Program of the Georgia Clinical and Translational Science Alliance (CTSA). Dr. Lyles is a Fellow of the American Statistical Association with ongoing interests in statistical methods applicable to epidemiological studies, including missing and mismeasured data problems encountered with surveillance data obtained in mortality and morbidity studies and with laboratory assay data used in HIV and environmental research.
Contact Information
Rollins School of Public Health , 1518 Clifton Road NE
Atlanta , GA 30322
Phone: (404) 727-1310
Fax: (404) 727-1370
Email: rlyles@sph.emory.edu
Areas of Interest
- Biomarkers
- Biostatistics
- Longitudinal Analysis
- Missing and Mismeasured Data
- Statistical Modeling
Education
- PhD 1996, University of North Carolina
- MS 1991, University of North Carolina
- BS 1988, Vanderbilt University
Courses Taught
- BIOS 736: Stats Analy W/Missing&Mismeasu
- BIOS 509: Applied Linear Models
- BIOS 795R: Pre-Candidacy Research
- BIOS 799R: Dissertation
Affiliations & Activities
American Statistical Association
International Biometric Society (ENAR)
Publications
- Lyles, R.H., Mitchell, E.M., Weinberg, C.R., Umbach, D.M., Schisterman, E.F., 2016, An Efficient Design Strategy for Logistic Regression Using Outcome- and Covariate-dependent Pooling of Biospecimens Prior to Assay, Biometrics, 72, 965-975
- Tang, L., Lyles, R.H., King, C.C., Hogan, J.W., Lo, Y., 2015, Regression Analysis for Differentially Misclassified Correlated Binary Outcomes , Journal of the Royal Statistical Society, Series C, 64, 433-449
- Mitchell, E.M., Lyles, R.H., Manatunga, A.K., Perkins, N.J., Schisterman, E.F., 2014, Regression for Skewed Biomarker Outcomes Subject to Pooling, Biometrics, 70, 202-211
- Lyles, R.H., Guo, Y., Greenland S. , 2012, Reducing Bias and Mean Squared Error Associated with Regression-Based Odds Ratio Estimators, Journal of Statistical Planning and Inference, 142, 3235-3241
- Lyles, R.H., Tang, L., Superak, H.M., King, C.C., Celentano, D., Lo, Y., Sobel, J., 2011, Validation Data-Based Adjustments for Outcome Misclassification in Logistic Regression: An Illustration, Epidemiology, 22, 589-597
- Lyles, R.H., Lin, J., 2010, Sensitivity Analysis for Misclassification in Logistic Regression via Likelihood Methods and Predictive Value Weighting, Statistics in Medicine, 29, 2297-2309
- Wannemuehler, K.A., Lyles, R.H., Waller, L.A., Hoekstra, R.M., Klein, M, Tolbert, P. , 2009, A Conditional Expectation Approach for Associating Ambient Air Pollutant Exposures with Health Outcomes, Environmetrics, 202, 877-894
- Lyles, R.H., Guo, Y., Hill, A.N., 2009, A Fresh Look at the Discriminant Function Approach for Estimating an Adjusted Odds Ratio, The American Statistician, 63, 320-327
- Lyles, R.H., Lin, H.-M., and Williamson, J.M., 2007, A Practical Approach to Computing Power for Generalized Linear Models with Nominal, Count, or Ordinal Outcomes, Statistics in Medicine, 26, 1632-1648
- Lyles, R.H., Manatunga, A.K., Moore, R.H., Bowman, F.D., and Cook, C.B., 2007, Improving Point Predictions of Random Effects for Subjects at High Risk, Statistics in Medicine, 26, 1285-1300
- Lyles, R.H., Williamson, J.M., Lin, H.-M., and Heilig, C.M., 2005, Extending McNemar’s Test: Estimation and Inference When Paired Binary Outcome Data are Misclassified, Biometrics, 61, 287-294
- Lyles, R.H., Tang, L., Lin, J., Zhang, Z., Mukherjee, B. , , Likelihood-based methods for regression analysis with binary exposure status assessed by pooling, Statistics in Medicine, in press,