Rollins School of Public Health | Faculty Profile

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Emory Rollins School of Public Health
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John  Williamson

Adjunct Associate Professor

Adjunct or Visiting, Biostatistics and Bioinformatics

I work in the Division of Parasitic Diseases and Malaria at the Centers for Disease Control and Prevention. My research interests include relative survival analysis,  longitudinal data analysis, and agreement analysis. My statistical methods work is often motivated from my infectious disease collaboration at the CDC. 

Contact Information

,

Phone: 470-725-6068

Email: jow5@cdc.gov

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Areas of Interest

  • Biostatistics
  • Infectious Disease

Education

  • BS 1986, Rensselaer Polytechnic Institute
  • MS 1989, University of North Carolina at Chapel Hill
  • ScD 1993, Harvard University School of Public Health

Publications

  • , , Firth adjustment for Weibull current-status survival analysis., Communications in Statistics - Theory and Methods, 49, 4587-4602
  • , , Power and sample size calculations for interval-censored survival analysis., Statistics in Medicine, 38, 1390-1400
  • , , A simple approach for sample size calculation for comparing two concordance correlation coefficients estimated on the same subjects., Journal of Biopharmaceutical Statistics , 25, 1145-1160
  • , , Estimating agreement coefficients from sample survey data., Survey Methodology , 38, 63-72
  • , , A Practical approach to computing power for generalized linear models with nominal, count, or ordinal responses., Statistics in Medicine , 26, 1632-1648
  • , , Generalization of the Mantel-Haenszel estimating function for sparse clustered binary data. , Biometrics, 61, 973-981
  • , , A semiparametric method for analyzing matched case-control family studies with a continuous outcome and proband sampling. , Biometrics, 60, 644-650
  • , , Association of co-occurring psychosocial health problems and increased vulnerability to HIV/AIDS among urban men who have sex with men. , American Journal of Public Health , 93, 939-942
  • , , Marginal analyses of clustered data when cluster size is informative. , Biometrics, 59, 36-42
  • , , Analyzing bivariate ordinal data using a global odds ratio. Journal of the American Statistical Association , Theory and Methods , 90, 1432-1437