Methodological papers in PDF form for the period 2020-present in reverse chronological order.

2025

  • Dousti Mousavi N, Yang J, Mermelstein R, Hedeker D. (2025, epub).  Enhanced modeling approaches for count data analysis with focus on substance use outcomes. J Behav Med.  doi: 10.1007/s10865-025-00610-w. PMID: 41326905.  pdf file
  • Wei, Y., Siddique, J., Spring, B., & Hedeker, D. (2025, epub).  A Bayesian Two-Step Multiple Imputation Approach Based on Mixed Models for Missing EMA Data.  Statistics in Medicine 44, no. 25-27: e70325, https://doi.org/10.1002/sim.70325.  pdf file
  • Ma, Q., Dunton, G.F., & Hedeker, D.  (2025).  Negative binomial mixed effects location-scale models for intensive longitudinal count-type physical activity data provided by wearable devices, Biometrics, Volume 81, Issue 3, https://doi.org/10.1093/biomtc/ujaf099  pdf file   supplemental materials
  • Hedeker, D. Mermelstein, R.J., & Siddique, J. (2025, epub).  A note on ordinal modeling of smoking rate data.  Nicotine & Tobacco Research.  pdf file   appendices

2024

  • Hedeker, D., Brooks, J., Diviak, K., Jao, N., & Mermelstein, R.J. (2024).  Pleasure and satisfaction as predictors of future cigarette and e-cigarette use: A novel two-stage modeling approach. Nicotine & Tobacco Research, 26, 1472–1479.  pdf file
  • Kypriotakis, G., Bernstein, S.L., Bold, K.W., Dziura, J.D., Hedeker, D., Mermelstein, R.J., & Weinberger, A.H.  (2024).  An Introduction and Practical Guide to Strategies for Analyzing Longitudinal Data in Clinical Trials of Smoking Cessation Treatment: Beyond Dichotomous Point-Prevalence Outcomes, Nicotine & Tobacco Research, 26, 796–805.  pdf file
  • Hedeker, D., Pereira, S., Garbeloto, F., Barreira, T. V., Garganta, R., Farias, C., Tani, G., Chaput, J.-P., Stodden, D. F., Maia, J., & Katzmarzyk, P. T. (2024). Statistical analysis of
    the longitudinal fundamental movement skills data in the REACT project using the multilevel ordinal logistic model. American Journal of Human Biology, e24015. https://doi.org/10.1002/ajhb.24015  pdf file
  • Hedeker, D., Siddique, J., Zhang, X., & Spring, B. (2024).  Multivariate and shared parameter mixed-effects models for intensive longitudinal data.  In D.E.K. Martin, A.S.R. Srinivasa Rao, & C.R. Rao (Eds.), Handbook of Statistics Volume 50: Modeling and Analysis of Longitudinal Data, Elsevier.  pdf file

2023

  • Siddique, J., Daniels, M., Inan, G., Battalio, S., Spring, B., & Hedeker, D. (2023).  Joint modeling the frequency and duration of accelerometer-measured physical activity from a lifestyle intervention trial. Statistics in Medicine, 42:, 5100–5112.  pdf file   supporting information
  • Zhang, X. & Hedeker, D. (2023). Detecting influential subjects in intensive longitudinal data using mixed-effects location scale models.  BMC Medical Research Methodology, 23:237. pdf file
  • Yaremych, H.E, Preacher, K.J., & Hedeker, D. (2023). Centering categorical predictors in multilevel models: Best practices and interpretation. Psychological Methods, 28(3):613–630.  pdf file
  • Gill, N. & Hedeker D. (2023).  Fast estimation of mixed-effects location-scale regression models. Statistics in Medicine, 42:1430-1444.  R package   pdf file

2022

  • Brown CH, Hedeker D, Gibbons RD, Duan N, Almirall D, Gallo C, Burnett-Zeigler I, Prado G, Young SD, Valido A, Wyman PA. (2022).  Accounting for Context in Randomized Trials after Assignment. Prevention Science, 23(8):1321-1332. pdf file  supplementary materials
  • Zhang, X. & Hedeker, D. (2022).  Defining R-squared measures for mixed-effects location scale models.  Statistics in Medicine, 41:4467-4483.  pdf file.
  • Ma, Q. Mermelstein, R. & Hedeker, D. (2022).  A shared-parameter location-scale mixed model to link the responsivity in self-initiated event reports and the event-contingent Ecological Momentary Assessments.  Statistics in Medicine, 41:1780-1796.  pdf file
  • Hedeker, D. & Mermelstein, R.J. (2022). 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.  dataset   pdf file

2021

  • Lin, X., Mermelstein, R.J., & Hedeker, D. (2021).  Analysis of multivariate longitudinal substance use outcomes using multivariate mixed cumulative logit model.  BMC Medical Research Methodology, 21:239.  pdf file

2020

  • Ma, Q. Mermelstein, R. & Hedeker, D. (2020).  A three-level mixed model to account for the correlation at both the between-day and the within-day level for ecological momentary assessments.  Health Services and Outcomes Research Methodology, 20:247-264.  pdf file
  • Lin, X., Mermelstein, R. & Hedeker, D. (2020).  Mixed location scale hidden Markov model for the analysis of intensive longitudinal data.  Health Services and Outcomes Research Methodology, 20:222-236.  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