Methodological papers in PDF form for the period 2010-2019 in reverse chronological order.


  • 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
  • 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
  • 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(40:648-665. pdf file


  • Capuano AW, Wilson R, Leurgans S, Dawson JD, Bennett DA, & Hedeker D (2018).  Sigmoidal mixed models for longitudinal data. Statistical Methods in Medical Research, 27(3):863-875.  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
  • Lin X, Mermelstein RJ, & Hedeker D (2018).  A three level Bayesian mixed effects location scale model with an application to Ecological Momentary Assessment (EMA) data.  Statistics in Medicine, 37:2108–2119.  pdf file  supplemental materials
  • 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


  • Li H & Hedeker D (2017). Statistical methods for continuous outcomes in partially clustered designs. Communications in Statistics Theory and Methods, 46(8):3915-3933.  pdf file
  • Siddique J, Hedeker D, & Gibbons RD (2017).  Analysis of Repeated Measures and Longitudinal Data in Health Services Research.  In: Sobolev B, Gatsonis C, (Eds.), Methods in Health Services Research, pp. 1-27. Boston, MA: Springer.  pdf file


  • Demirtas H & Hedeker D (2016). Computing the point-biserial correlation under any underlying continuous distribution. Communications in Statistics — Simulation and Computation, 45(8):2744-2751.  pdf file
  • Gao W, Hedeker D, Mermelstein RJ, & Xie H (2016).  A scalable approach to measuring the impact of nonignorable nonresponse with an application to EMA data. Statistics in Medicine, 35(30):5579-5602.  pdf file
  • Hedeker D, Mermelstein RJ, Demirtas H, & Berbaum ML (2016).  A mixed-effects location-scale model for ordinal questionnaire data. Health Services and Outcomes Research Methodology, 16(3):117-131.  pdf file


  • Cafri G, Hedeker D, & Aarons GA (2015).  An introduction and integration of cross-classified, multiple membership, and dynamic group random-effects models. Psychological Methods, 20(4), 407-421.  pdf file  supplemental materials
  • Hedeker D (2015). Methods for multilevel ordinal data in prevention research. Prevention Science, 16:997-1006.  pdf file
  • Kapur K, Li X, Blood EA, & Hedeker D (2015).  Bayesian mixed-effects location and scale models for multivariate longitudinal outcomes: An application to ecological momentary assessment data. Statistics in Medicine, 34:2312-2324.  pdf file
  • McGinley JS, Curran PJ, & Hedeker D (2015).  A novel modeling framework for ordinal data defined by collapsed counts.  Statistics in Medicine, 34(4), 630-651.  pdf file  supplemental materials


  • Pugach O, Hedeker D, & Mermelstein RJ (2014).  A bivariate mixed-effects location-scale model with application to ecological momentary assessment (EMA) data.  Health Services and Outcomes Research Methodolology, 14(4):194-212.  pdf file
  • Pugach O, Hedeker D, Richmond MJ, Sokolovsky A, & Mermelstein, RJ (2014).  Modeling mood variation and covariation among adolescent smokers: Application of a bivariate location-scale mixed-effects model. Nicotine and Tobacco Research, 16, Supplement 2, S151-S158.  pdf file
  • Siddique J, Harel O, Crespi CM & Hedeker D (2014).  Binary variable multiple-model multiple imputation to address missing data mechanism uncertainty: Application to a smoking cessation trial. Statistics in Medicine, 33(17), 3013-3028.  pdf file
  • Wang K-C, Hedeker D, Chang H-L, & Lin Y-C (2014).  Multilevel logistic regression modeling with correlated random effects: Application to the choice of mode for the leisure traveler.  Journal of the Chinese Institute of Transportation, 26(4), 497-528.  pdf file


  • Leon AC, Demirtas H, Li C, & Hedeker D (2013).  Subject-level matching for imbalance in cluster randomized trials with a small number of clusters.  Pharmaceutical Statistics, 12(5):268-274. pdf file
  • Liu L, Hedeker D, & Mermelstein RJ (2013).  Modeling nicotine dependence: An application of a longitudinal IRT model for the analysis of adolescent Nicotine Dependence Syndrome Scale. Nicotine & Tobacco Research, 15(2):326-333.  pdf file
  • Hedeker D & Nordgren R (2013).  MIXREGLS: A program for mixed-effects location scale analysis.  Journal of Statistical Software, 52(12):1-38. pdf file
  • Rose JS, Dierker LC, Hedeker D, & Mermelstein RJ (2013).  An integrative data analysis approach to investigating measurement equivalence of DSM nicotine dependence symptoms.  Drug and Alcohol Dependence, 129:25–32.  pdf file


  • Demirtas H, Hedeker D, & Mermelstein RJ (2012).  Simulation of massive public health data by power polynomials. Statistics in Medicine, 31:3337-3346. pdf file
  • Hedeker D & Mermelstein RJ (2012).  Mood changes associated with smoking in adolescents: An application of a mixed-effects location scale model for longitudinal Ecological Momentary Assessment (EMA) data. In G. R. Hancock & J. Harring (Eds.), Advances in Longitudinal Methods in the Social and Behavioral Sciences (pp. 59-79). Information Age Publishing, Charlotte, NC.  pdf file
  • Hedeker D, Mermelstein RJ, & Demirtas H. (2012).  Modeling between- and within-subject variance in Ecological Momentary Assessment (EMA) data using mixed-effects location scale models. Statistics in Medicine, 31:3328-3336.  pdf file
  • Leon AC, Demirtas H, Li C, & Hedeker D (2012).  Two propensity score-based strategies for a three decade observational study: Investigating psychotropic medications and suicide risk.  Statistics in Medicine, 31:3255-3260.  pdf file
  • Leon AC, Hedeker D, Li C, & Demirtas H (2012).  Performance of a propensity score adjustment in longitudinal studies with covariate-dependent representation.  Statistics in Medicine, 31:2262-2274.  pdf file
  • Li X & Hedeker, D. (2012). A three-level mixed-effects location scale model with an application to ecological momentary assessment (EMA) data. Statistics in Medicine, 31:3192-3210.  pdf file   supplemental materials
  • Selya AS, Rose JS, Dierker LC, Hedeker D, & Mermelstein RJ (2012). A practical guide to calculating Cohen’s f2, a measure of local effect size, from PROC MIXED.  Frontiers in Psychology, 3:111.  pdf file


  • Demirtas H & Hedeker D (2011). A practical way for computing approximate lower and upper correlation bounds. The American Statistician, 65:104-109.  pdf file
  • Demirtas H & Hedeker D (2011).  Generating multivariate continuous data via the notion of nearest neighbors.  Journal of Applied Statistics, 38:47-55.  pdf file
  • Hedeker D & Mermelstein RJ (2011).  Multilevel analysis of ordinal outcomes related to survival data.  In J. J. Hox & J. K. Roberts (Eds.), The Handbook of Advanced Multilevel Analysis (pp. 115-136). Taylor and Francis, New York.  pdf file
  • Leon AC & Hedeker D (2011).  Propensity score stratification for observational comparison of repeated binary outcomes.  Statistics and Its Interface, 4:489-498.  pdf file


  • Gibbons RD, Hedeker D, & du Toit SHC (2010).  Advances in analysis of longitudinal data. Annual Review of Clinical Psychology, 6:79-107.  pdf file
  • Liu LC, Hedeker D, Segawa E, & Flay BR (2010).  Evaluation of longitudinal intervention effects: An example of latent growth mixture models for ordinal drug-use outcomes. Journal of Drug Issues, 40:27-44.  pdf file
  • Schneider KL, Hedeker D, Bailey KC, Cook JW, & Spring B (2010).  A comment on analyzing addictive behaviors over time. Nicotine & Tobacco Research, 12:445-448.  pdf file