This is the website for Don’s statistical methodological work, which contains PDF presentation files, syntax examples, and PDFs of publications in a number of areas:

Don Hedeker’s CV

Recent publications
  • Hedeker, D. & Mermelstein, R.J. (in press). Modeling Variation in Intensive Longitudinal Data.  In A.A. O’Connell, D. B. McCoach, & B. Bell (Eds.), Multilevel Modeling Methods with Introductory and Advanced Applications. Information Age Publishing.  pdf file
  • Lin, X., Mermelstein, R. & Hedeker, D. (2020, epub).  Mixed location scale hidden Markov model for the analysis of intensive longitudinal data.  Health Services and Outcomes Research Methodology.  pdf file
  • Ma, Q. & Hedeker, D.  (2020).  Modeling of between- and within-subject variances using mixed effects location scale (MELS) models.  SAS 2020 Global Forum Proceedings, Paper 4181-2020.  pdf file
  • Yuan, C., Hedeker, D., Mermelstein, R., Xie, H. (2020).  A tractable method to account for high-dimensional nonignorable missing data in intensive longitudinal data.  Statistics in Medicine, 39(20):2589-2605.  pdf file
  • Dzubur, E., Ponnada, A., Nordgren, R., Yang, C.-H., Intille, S., Dunton, G., & Hedeker, D. (2020).  MixWILD: A program for examining the effects of variance and slope of time-varying variables in intensive longitudinal data. Behavior Research Methods, 52:1403–1427.  pdf file
  • Nordgren, R., Hedeker, D., Dunton, G., & Yang, C.-H. (2020).  Extending the mixed-effects model to consider within-subject variance for Ecological Momentary Assessment data.  Statistics in Medicine, 39:577-590. pdf file
  • Hedeker, D. (2019).  Multilevel Modeling of Non-Normal Data. In P. Atkinson, S. Delamont, A. Cernat, J.W. Sakshaug, & R.A. Williams (Eds.), SAGE Research Methods Foundations. doi: 10.4135/9781526421036883650.  pdf file
  • Cursio, J., Mermelstein, R.J., & Hedeker, D. (2019).  Latent trait shared parameter mixed-models for missing ecological momentary assessment data. Statistics in Medicine, 38:660-673. pdf file
  • Wang, J., Wang, P., Hedeker, D., & Chen, L. (2019).  A multivariate mixed-effects selection model framework for batch-processed proteomics data with non-ignorable missingness. Biostatistics, 20(4):648-665. pdf file
  • Courvoisier, D., Walls, T.A., Cheval, B., & Hedeker, D. (2019).  A mixed-effects location scale model for time-to-event data: A smoking behavior application. Addictive Behaviors, 94:42-49. pdf file
  • Hedeker D, du Toit SHC, Demirtas H, & Gibbons RD (2018).  A note on marginalization of regression parameters from mixed models of binary outcomes. Biometrics, 74:354-361.  pdf file
  • Lin X, Mermelstein RJ, & Hedeker D (2018).  A shared parameter location scale mixed efect model for EMA data subject to informative missing.  Health Services and Outcomes Research Methodology, 18:227–243. pdf file
  • Xie, H., Gao, W., Xing, B., Heitjan, D.F., Hedeker, D., & Yuan, C. (2018).  Measuring the impact of nonignorable missingness using the R package isni.  Computer Methods and Programs in Biomedicine, 164:207-220.  pdf file