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My focus is in studying the association between such markers and the risk for an event, and developing dynamic prediction tools. Positions and employment: - Associate Professor, March - present, Dept. Books: Rizopoulos, D. Journal of Statistical Software, to appear.
Rizopoulos, D. Personalized screening intervals for biomarkers using joint models for longitudinal and survival data. Biostatistics 17, Andrinopoulou, E. Bayesian shrinkage approach for a joint model of longitudinal and survival outcomes assuming different association structures.
Statistics in Medicine, to appear. Erler, N. Dealing with missing covariates in epidemiologic studies: A comparison between multiple imputation and a full Bayesian approach.
Combined dynamic predictions using joint models of two longitudinal outcomes and competing risk data. Statistical Methods in Medical Research, to appear. Nasserinejad, K. Prediction of hemoglobin in blood donors using latent class mixed-effects transition models. Statistics in Medicine 35, Garcia-Hernandez, A. 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 34, Murawska, M. Simple analysis of non-Markov models: A case study on heart transplant data. Statistical Modelling 15, Combining dynamic predictions from joint models for longitudinal and time-to-event data using Bayesian model averaging.
Journal of the American Statistical Association , Joint modeling techniques. Statistical Methods in Medical Research 23, Molenberghs, G.
Aerts, M. On random sample size, ignorability, ancillarity, completeness, separability and degeneracy: Sequential trials, random sample sizes, and missing data. EuroIntervention 10, Joint modeling of two longitudinal outcomes and competing risk data. Statistics in Medicine 33, Vasdekis, V. Weighted pairwise likelihood estimation for a general class of random effects models.
Biostatistics 15, Viviani, S. Local sensitivity of shared parameter models to non-ignorability of dropout. Statistical Modelling 14, Generalized linear mixed joint model for longitudinal and survival outcomes. Statistics and Computing 24, Njeru Njagi, E, Molenberghs, G. Dendale, P.
A flexible joint modelling framework for longitudinal and time-to-event data with overdispersion. 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 56, Njeru Njagi, E, Rizopoulos, D. A joint survival-longitudinal modelling approach for the dynamic prediction of rehospitalization in telemonitored chronic heart failure patients.
Statistical Modelling 13, Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule. A two-stage joint model for nonlinear longitudinal response and a time-to-event with application in transplantation studies. Journal of Probability and Statistics , article ID , 18 pages. An introduction to mixed models and joint modeling: Analysis of valve function over time. Annals of Thoracic Surgery 93, Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data.
Biometrics 67, A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes a time-to-event. Statistics in Medicine 30, Multiple-imputation-based residuals and diagnostic plots for joint models of longitudinal and survival outcomes. Biometrics 66, JM: An R package for the joint modelling of longitudinal and time-to-event data. Journal of Statistical Software 35 9 , Tsonaka, R.
Nonignorable models for intermittently missing categorical longitudinal responses. Fully exponential Laplace approximations for the joint modelling of survival and longitudinal data. Shared parameter models under random effects misspecification.
Biometrika 95, A two-part joint model for the analysis of survival and longitudinal binary data with excess zeros. Biometrics 64, Generalized latent variable models with nonlinear effects.
British Journal of Mathematical and Statistical Psychology 61, Lesaffre, E. The logistic transform for bounded outcome scores. Biostatistics 8, Journal of Statistical Software 17 5 , Power and sample size calculations for discrete bounded outcome scores.
Prof.dr. D. (Dimitris) Rizopoulos
I am a professor of biostatistics at the Erasmus Medical Center Rotterdam. My research focuses on joint models for longitudinal and time-to-event data with applications in biomarker identification, precision medicine, screening and active surveilance. I currently serve as a co-Editor for Biostatistics [ twitter handle ]. Novel methods for optimally planning when to collect longitudinal measurements or event information.
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