Sally W. Thurston, PhD

Associate Professor of Biostatistics
Associate Professor of Oncology
Ph.D. (1997) Harvard University


Contact Information:

University of Rochester
Dept of Biostatistics and Computational Biology
265 Crittenden Boulevard, CU 420630
Rochester, New York 14642-0630
Office: Saunders Research Building 4145
Phone: (585) 275-2406
Fax: (585) 273-1031
Sally Thurston, PhD

Research Interests

Much of my statistical research is motivated by problems arising in environmental and occupational health. Research interests include modeling multiple outcomes, correction for measurement error bias, exposure assessment, modeling multiple correlated exposures, non-parametric smoothing, Bayesian inference, informative prior specification, and using biomarkers to improve cancer risk estimates.

I am currently the director of the Design, Biostatistics, and Clinical Research Ethics key function of Rochester's Clinical and Translational Sciences Institute ( I am a member of Rochester's Environmental Health Sciences Center ( I collaborate closely with several faculty in Environmental Medicine, including as a lead statistician for the Seychelles Child Development Study, and with several faculty in Public Health Sciences.

I received an A.B. in Biology from Oberlin College, an M.S. in Natural Resources from Cornell University, and a Ph.D. in Statistics from Harvard University. Prior to coming to Rochester in 2002, I was a postdoctoral fellow and then a research associate in Biostatistics at Harvard School of Public Health. I am a member of the American Statistical Association and the International Biometric Society, and an elected member of the International Statistical Institute.

Selected Publications

Statistical Methods

  • Evans K, Love TMT, Thurston SW. Outlier identification in model-based cluster analysis. Journal of Classification, to appear.
  • Xiao L, Thurston SW, Ruppert D, Love TMT, Davidson PW (2014). Bayesian models for multiple outcomes in domains with application to the Seychelles Child Development Study. Journal of the American Statistical Association, 109:1-10.
  • Woodard DB, Love TM, Thurston SW, Ruppert D, Sathyanarayana S, Swan SH (2013). Latent factor regression models for grouped outcomes.  Biometrics 69:785-794.
  • Thurston SW, Ruppert D, and Davidson PW (2009). Bayesian Models for Multiple Outcomes Nested in Domains. Biometrics 65(4):1078-1086. PMCID:  PMC3031784.
  • Liang H, Thurston SW, Ruppert D, Apanasovich T, and Hauser R (2008). Additive Partial Linear Models with Measurement Error. Biometrika 95(3):667-678.
  • Thurston SW, Williams P, Hauser R, Hu H, Hernandez-Avila M, and Spiegelman D (2005). A comparison of regression calibration approaches for designs with internal validation data. Journal of Statistical Planning and Inference 131(1):175-190.
  • Thurston SW, Spiegelman D, and Ruppert D (2003). Equivalence of Regression Calibration Methods for External Validation Data. Journal of Statistical Planning and Inference 113(2):527-539.

Environmental Health

  • van Wijngaarden E, Thurston SW, Myers GJ, Strain JJ, Weiss B, Zarcone T, Watson GE, Zareba G, McSorley EM, Mulhern MS, Yeates AJ, Henderson J, Gedeon J, Shamlaye CF, Davidson PW (2013). Prenatal methyl mercury exposure in relation to neurodevelopment and behavior at 19 years of age in the Seychelles Child Development Study. Neurotoxicology and Teratology, 39:19-25.
  • Barrett ES, Tran T, Thurston S, Furberg A-S, Ellison P, Thune I (2013). Marriage and motherhood are associated with lower testosterone concentrations in women. Hormones and Behavior 63:72-79.
  • Sagiv SK, Thurston SW, Bellinger DC, Amarasiriwardena C, Korrick SA (2012). Prenatal exposure to mercury and fish consumption during pregnancy and attention-deficit/hyperactivity disorder-related behavior in children. Archives of Pediatrics & Adolescent Medicine 166:1123-1131.
  • Strain JJ, Davidson PW, Thurston SW, Harrington D, Mulhern M, McAfee Al, van Wijngaarden E, Shamlaye CF, Henderson J, Watson G, Zareba G, Cory-Slechta  DA, Lynch M, Wallace JMW, McSorley EM, Bonham MP, Stokes-Riner A, Sloane-Reeves J,  Janciuras J, Wong R, Clarkson TW, Myers GJ (2012). Maternal polyunsaturated fatty acid status but not prenatal methylmercury exposure is associated with children's language functions at age five years in the Seychelles.  Journal of Nutrition 142:1943-1949.
  • Sagiv SK, Thurston SW, Bellinger DC, Altshul LM, and Korrick SA (2012). Neuropsychological measures of attention and impulse control among 8-year-old children exposed prenatally to organochlorines. Environmental Health Perspectives 120:904-909.
  • Davidson PW, Cory-Slechta DA, Thurston SW, Huang LS, Shamlaye CF, Gunzler D, Watson G, van Wijngaarden E, Zareba G, Klein JD, Clarkson TW, Strain JJ, and Myers GJ (2011). Fish consumption and prenatal methylmercury exposure: cognitive and behavioural outcomes in the main cohort at 17 years from the Seychelles Child Development Study. NeuroToxicology 32(6):711-717.
  • Watson GE, Lynch M, Myers GJ, Shamlaye CF, Thurston SW, Zareba G, Clarkson TW, and Davidson PW (2011). Prenatal exposure to dental amalgam: evidence from the Seychelles Child Development Main Cohort. Journal of the American Dental Association 142(11):1283-1294.
  • Stokes-Riner A, Thurston SW, Myers GJ, Duffy EM, Wallace J, Bonham M, Robson P, Shamlaye CF, Strain JJ, Watson G, and Davidson PW (2011). A longitudinal analysis of prenatal exposure to methylmercury and fatty acids in the Seychelles. Neurotoxicology and Teratology 33(2):325-328.
  • Thurston SW, Bovet P, Myers GJ, Davidson PW, Georger LA, Shamlaye C, and Clarkson TW (2007). Does prenatal methylmercury exposure from fish consumption affect blood pressure in childhood? NeuroToxicology 28(5):924-930.  PMCID:  PMC2104472, NIHMSID:  NIHMS33069


  • Thurston SW (2013). Biomarkers, in Encyclopedia of Environmetrics, 2nd ed., El-Shaarawi AH and Piegorsch WW (editors), John Wiley and Sons Ltd: Chichester, UK. DOI: 10.1002/9780470057339.vab019.pub2. Published online 1/15/2013.
  • Park SY, Love TM, Nelson J, Thurston SW, Perelson A, and Lee HY (2011). Designing a Genome-Based HIV-1 Incidence Assay with High Sensitivity and Specificity AIDS 25(16):F13-F19.
  • Friesen MC, Costello S, Thurston SW, and Eisen EA (2011). Distinguishing the common components of oil- and water-based metalworking fluids for assessment of cancer incidence risk in autoworkers. American Journal of Industrial Medicine 54(6):450-460.
  • Thurston SW, Liu G, Miller DP and Christiani DC (2005). Modeling lung cancer risk in case-control studies using a new dose metric of smoking [with Commentary]. Cancer Epidemiology, Biomarkers & Prevention 14(10):2296-2302.