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Dimitris Rizopoulos

 

  Associate Professor in Biostatistics (Vidi laureate 2014-2019)

 

Research Interests:

  • Survival Analysis
  • Longitudinal Data Analysis
  • Joint Modeling of Longitudinal & Time-to-Event Data
  • Statistical Analysis with Missing Data
  • Latent Variable Modeling
  • Statistical Computing

I am primarily interested in the statistical analysis of repeated measurements of biomarkers with time-to-event data. Examples include among others: CD4 cell counts for HIV infected patients, PSA levels for prostate cancer patients, and serum bilirubin levels for liver cirrhosis patients. My focus is in studying the association between such markers and the risk for an event, and developing dynamic prediction tools.


 

Books


 

Methodological Publications:

  • Rizopoulos, D., Hatfield, L., Carlin, B. and Takkenberg, J. (2014). Combining dynamic predictions from joint models  for longitudinal and time-to-event data using Bayesian model averaging. Journal of the American Statistical Association, to appear.
  • Rizopoulos, D. and Lesaffre, E. (2014). Joint modeling techniques. Statistical Methods in Medical Research 23, 3-10.
  • Molenberghs, G., Kenward, M. Aerts, M., Verbeke, G., Tsiatis, AA., Davidian, M. and Rizopoulos, D. (2014). On random sample size, ignorability, ancillarity, completeness, separability and degeneracy: Sequential trials, random sample sizes, and missing data. Statistical Methods in Medical Research 23, 11-41.
  • Rizopoulos, D. (2014). Comments on 'Joint modeling of survival and longitudinal non-survival data: Current methods and issues. Report of the DIA Bayesian joint modeling working group'. Statistics in Medicine, to appear.
  • Rizopoulos, D. and Takkenberg, J. (2014). Tools & Techniques: Dealing with time-varying covariates in survival analysis - Joint models versus Cox models. EuroIntervention, to appear.
  • Andrinopoulou, E.R., Rizopoulos, D., Takkenberg, J. and Lesaffre, E. (2014). Joint modeling of two longitudinal outcomes and competing risk data. Statistics in Medicine, to appear.
  • Murawska, M. and Rizopoulos, D. (2014). Simple analysis of non-Markov models: A case study on heart transplant data. Statistical Modelling, to appear.
  • Vasdekis, V., Rizopoulos, D. and Moustaki, I. (2014). Weighted pairwise likelihood estimation for a general class of random effects models. Biostatistics, to appear.
  • Viviani, S. Rizopoulos, D. and Alfo, M. (2014). Local sensitivity of shared parameter models to non-ignorability of dropout. Statistical Modelling, to appear.
  • Viviani, S., Alfo, M. and Rizopoulos, D. (2014). Generalized linear mixed joint model for longitudinal and survival outcomes. Statistics and Computing 24, 417-427.
  • Njeru Njagi, E, Molenberghs, G., Rizopoulos, D., Verbeke, G., Kenward, M. Dendale, P. and Willekens, K. (2014). A flexible joint modelling framework for longitudinal and time-to-event data with overdispersion. Statistical Methods in Medical Research, to appear.
  • Njeru Njagi, E, Molenberghs, G., Kenward, M., Verbeke, G. and Rizopoulos, D. (2014). A characterization of missingness at random in a generalized shared-parameter joint modelling framework for longitudinal and time-to-event data, and sensitivity analysis. Biometrical Journal, to appear.
  • Njeru Njagi, E, Rizopoulos, D., Molenberghs, G., Dendale, P. and Willekens, K. (2013). A joint survival-longitudinal modelling approach for the dynamic prediction of rehospitalization in telemonitored chronic heart failure patients. Statistical Modelling 13, 179-198.
  • Rizopoulos, D. (2012). Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule. Computational Statistics & Data Analysis 56, 491-501.
  • Murawska, M., Rizopoulos, D. and Lesaffre, E. (2012). A two-stage joint model for nonlinear longitudinal response and a time-to-event with application in transplantation studies. Journal of Probability and Statistics 2012, article ID 194194, 18 pages.
  • Andrinopoulou, E.R., Rizopoulos, D., Jin, R., Bogers, A., Lesaffre, E. and Takkenberg, J. (2012).  An introduction to mixed models and joint modeling: Analysis of valve function over time. Annals of Thoracic Surgery 93, 1765-1772.
  • Rizopoulos, D. (2011). Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data. Biometrics 67, 819-829.
  • Rizopoulos, D. and Ghosh, P. (2011). A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes a time-to-event. Statistics in Medicine 30, 1366-1380.
  • Rizopoulos, D., Verbeke, G. and Molenberghs, G. (2010). Multiple-imputation-based residuals and diagnostic plots for joint models of longitudinal and survival outcomes. Biometrics 66, 20-29.
  • Rizopoulos, D. (2010). JM: An R package for the joint modelling of longitudinal and time-to-event data. Journal of Statistical Software 35(9), 1-33.
  • Tsonaka, R., Rizopoulos, D., Verbeke, G. and Lesaffre, E. (2010). Nonignorable models for intermittently missing categorical longitudinal responses. Biometrics 66, 834-844.
  • Rizopoulos, D., Verbeke, G. and Lesaffre, E. (2009). Fully exponential Laplace approximations for the joint modelling of survival and longitudinal data. Journal of the Royal Statistical Society, Series B 71, 637-654.
  • Rizopoulos, D., Verbeke, G. and Molenberghs, G. (2008). Shared parameter models under random effects misspecification. Biometrika 95, 63-74.
  • Rizopoulos, D., Verbeke, G., Lesaffre, E. and Vanrenterghem, Y. (2008). A two-part joint model for the analysis of survival and longitudinal binary data with excess zeros. Biometrics 64, 611-619.
  • Rizopoulos, D. and Moustaki, I. (2008). Generalized latent variable models with nonlinear effects. British Journal of Mathematical and Statistical Psychology 61, 415-438.
  • Lesaffre, E., Rizopoulos, D. and Tsonaka, R. (2007). The logistic transform for bounded outcome scores. Biostatistics 8, 72-85.
  • Rizopoulos, D. (2006). ltm: An R package for latent variable modelling and item response theory analyses. Journal of Statistical Software 17(5), 1-25.
  • Tsonaka, R., Rizopoulos, D. and Lesaffre, E. (2006). Power and sample size calculations for discrete bounded outcome scores. Statistics in Medicine 25, 4241-4252.

 

Software (R Packages):

  • JMbayes: Joint models for longitudinal and time-to-event (survival) data using MCMC.

Download from CRAN / Paper

  • JM: Joint models for longitudinal and time-to-event (survival) data.

Download from CRAN / Detailed Information / Paper

  • ltm: Latent variable models for item response theory analyses

Dowload from CRAN / Detailed Information / Paper


 

Recent Invited Conference Lectures:

http://eur.academia.edu/DimitrisRizopoulos/Talks

Curriculum Vitae:

http://eur.academia.edu/DimitrisRizopoulos/CurriculumVitae