Health Services and Outcomes Research Methodology

, Volume 16, Issue 3, pp 75–91

An interview with Don Hedeker

Article

Abstract

Don Hedeker was born in the late 1950s in Chicago, Illinois. He attended public schools in Chicago and did his undergraduate work at the University of Chicago, earning a degree in Economics in 1980. In 1981, he began graduate work in the Department of Behavioral Sciences, Committee on Research Methodology and Quantitative Psychology at the University of Chicago. He completed his dissertation in 1989 under the direction of Darrell Bock. In 1993, Don accepted a faculty position at the University of Illinois at Chicago (UIC) where he was promoted to tenured Associate Professor in 1996 and to Full Professor in 2001. He spent 20 years on the faculty at UIC, leaving in 2014 in order to return to the University of Chicago as a Professor of Biostatistics in the Department of Public Health Sciences. Don’s main expertise is in the development and dissemination of advanced statistical methods for clustered and longitudinal data. In addition to many methodological papers in these areas, Don has developed several freeware computer programs for statistical analysis of such data. To date, he has published over 180 papers and 1 book. Don is also an accomplished musician, and has played in bands since high school. This interview was conducted in honor of Don being awarded the 2015 Long-term Excellence Award from the Health Policy Statistics Section of the American Statistical Association. The interview took place in Don’s office at the University of Chicago on December 23, 2015.

Keywords

University of Chicago Mixed-effects models Darrell Bock Robert Gibbons The Polkaholics 

References

  1. Bock, R.D.: The discrete Bayesian. In: Wainer, H., Messick, S. (eds.) Principals of Psychometrics. Erlbaum, Hillsdale (1983)Google Scholar
  2. Bock, R.D. (ed.): Multilevel Analysis of Educational Data. Academic Press, New York (1989)Google Scholar
  3. Chi, E.M., Reinsel, G.C.: Models for longitudinal data with random effects and AR (1) errors. J. Am. Stat. Soc. 84, 452–459 (1989)CrossRefGoogle Scholar
  4. Gibbons, R.D., Bock, R.D.: Trend in correlated proportions. Psychometrika 52(1), 113–124 (1987)CrossRefGoogle Scholar
  5. Gruder, C.L., Mermelstein, R.J., Kirkendol, S., Hedeker, D., Wong, S.C., Schreckengost, J., Warnecke, R.B., Burzette, R., Miller, T.Q.: Effects of social support and relapse prevention training as adjuncts to a televised smoking cessation intervention. J. Consult. Clin. Psychol. 61, 113–120 (1993)CrossRefPubMedGoogle Scholar
  6. Hedeker, D.: Random Regression Models with Autocorrelated Errors. Ph.D. thesis, University of Chicago, Department of Psychology (1989)Google Scholar
  7. Hedeker, D., Gibbons, R.D.: MIXOR: a computer program for mixed-effects ordinal probit and logistic regression analysis. Comput. Methods Programs Biomed. 49, 157–176 (1996a)CrossRefPubMedGoogle Scholar
  8. Hedeker, D., Gibbons, R.D.: MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors. Comput. Methods Programs Biomed. 49, 229–252 (1996b)CrossRefPubMedGoogle Scholar
  9. Hedeker, D., Mermelstein, R.J.: A multilevel thresholds of change model for analysis of stages of change data. Multivar. Behav. Res. 33, 427–455 (1998)CrossRefGoogle Scholar
  10. Hedeker, D., Gibbons, R.D.: Longitudinal Data Analysis. Wiley, New York (2006)Google Scholar
  11. Hedeker, D., Nordgren, R.: MIXREGLS: a program for mixed-effects location scale analysis. J. Stat. Softw. 52(12), 1–38 (2013)CrossRefPubMedPubMedCentralGoogle Scholar
  12. Hedeker, D., Gibbons, R.D., Flay, B.R.: Random-effects regression models for clustered data: with an example from smoking prevention research. J. Consult. Clin. Psychol. 62, 757–765 (1994)CrossRefPubMedGoogle Scholar
  13. Hedeker, D., Flay, B.R., Petraitis, J.: Estimating individual differences of behavioral intentions: an application of random-effects modeling to the theory of reasoned action. J. Consult. Clin. Psychol. 64, 109–120 (1996)CrossRefPubMedGoogle Scholar
  14. Hedeker, D., Mermelstein, R.J., Weeks, K.A.: The thresholds of change model: an approach to analyzing stages of change data. Ann. Behav. Med. 21, 61–70 (1999)CrossRefPubMedGoogle Scholar
  15. Hedeker, D., Mermelstein, R., Flay, B.R.: Application of item response theory models for intensive longitudinal data. In: Walls, T., Schafer, J. (eds.) Models for Intensive Longitudinal Data. Oxford University Press, Oxford (2006a)Google Scholar
  16. Hedeker, D., Berbaum, M., Mermelstein, R.J.: Location-scale models for multilevel ordinal data: between- and within-subjects variance modeling. J. Probab. Stat. Sci. 4, 1–20 (2006b)Google Scholar
  17. Hedeker, D., Mermelstein, R.J., Demirtas, H.: Analysis of binary outcomes with missing data: missing = smoking, last observation carried forward, and a little multiple imputation. Addiction 102, 1564–1573 (2007)CrossRefPubMedGoogle Scholar
  18. Hedeker, D., Mermelstein, R.J., Demirtas, H.: An application of a mixed-effects location scale model for analysis of ecological momentary assessment (EMA) data. Biometrics 64(2), 627–634 (2008)CrossRefPubMedGoogle Scholar
  19. Hedeker, D., Demirtas, H., Mermelstein, R.J.: A mixed ordinal location scale model for analysis of ecological momentary assessment (EMA) data. Stat. Interface 2(4), 391 (2009a)CrossRefPubMedPubMedCentralGoogle Scholar
  20. Hedeker, D., Mermelstein, R.J., Berbaum, M.L., Campbell, R.T.: Modeling mood variation associated with smoking: an application of a heterogeneous mixed-effects model for analysis of ecological momentary assessment (EMA) data. Addiction 104(2), 297–307 (2009b)CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Preventive MedicineNorthwestern UniversityChicagoUSA

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