ISCB Course w/ Dimitris Rizopoulos

Czech National Group of the International Society for Clinical Biostatistics, in cooperation with the Institute of Computer Science AS CR in Prague, and, Faculty of Mathematics & Physics of the Charles University in Prague

are delighted to invite you to attend

 a One-day ISCB course on

„Building, Interpreting, and Validating Joint Models for Longitudinal and Time-to-Event Data: An Interactive Short Course“

presented by

Dimitris Rizopoulos

Erasmus University Medical Center, Rotterdam, The Netherlands

Prof. Dimitris Rizopoulos. Ph.D.

Dimitris Rizopoulos is a professor and head of the Department of Biostatistics at the Erasmus Medical Center Rotterdam. His research focuses on joint models for longitudinal and time-to-event data with applications in biomarker identification, precision medicine, precision screening, and active surveillance. He has extensive experience teaching courses on mixed models, survival analysis, and joint models at multiple international conferences and universities around the world. He is the author of a monograph on joint models published by Chapman & Hall/CRC, and is the leading developer in the JMbayes2, GLMMadaptive, and JM R packages.

WHERE

Institute of Computer Science AS CR, Pod Vodarenskou vezi 2, 182 00 Prague, https://maps.app.goo.gl/X656Q26qQULc9iYy6.

Course material (slides) will be made available to registered course participants approx. 1 week ahead of the course schedule. 

WHEN                                               

23 October 2026 (Friday), 9:00 AM through 4:30 PM Central European Time (CET), i.e. still a summer time. The time shift to standard (winter) time will be applied on 25th OCT 2026, i.e. two days after the course commencement.

REGISTRATION DEADLINE       

2 October 2026 (Friday)

Important!!: 

• Before you make a payment, please, e-mail an inquiry to the Course Secretary Ms. Lenka Semeráková for confirmation (semerakova@cs.cas.cz)

• The number of course participants is limited to 30. Should the course reach its capacity, a notification will be placed here

• The payment has to be received by this date

COURSE ABSTRACT

Joint models for longitudinal and time-to-event data have attracted significant attention in recent years. These models are used in follow-up studies to account for endogenous time-varying covariates or to correct for informative dropout. Several variants of these models have been proposed in the literature, and their implementation is now available in widely used statistical software. This course aims to provide a hands-on step-by-step guide on how to build and utilize these models in practice. The course is split into two parts. The first part introduces the statistical background underlying joint models. In the second part, an example dataset will be introduced along with specific motivating research questions. The instructor and the participants will build joint models in an interactive live analysis session to answer these questions. Emphasis will be given to appropriately assessing model fit and correctly interpreting the results.

This course is aimed at applied researchers and graduate students working in applied environments where hierarchical modeling and survival analysis are key issues; this would include biostatisticians working in the pharmaceutical industry, regulatory agencies, or academic centers.

Course background

• This course assumes knowledge of basic statistical concepts, such as standard statistical inference using maximum likelihood and regression models 

• Also, a basic knowledge of R would be beneficial but is not required

• Participants are required to bring their laptop with the battery fully charged. Before the course, instructions will be sent for installing the required software

Target audience

• Professional statisticians working in applied environments where hierarchical modelling and survival analysis are key issues; this would include biostatisticians working in the pharmaceutical industry, regulatory agencies, or academic centers

Learning objectives

After the course, the participants are expected to be able to identify the settings in which joint modeling approach is required. The course will explain which joint models can be used depending on the actual research questions to be answered and which model-building strategies are currently available. Further, participants should be able to construct and fit an appropriate joint model, correctly interpret the obtained results, and extract additional useful information (e.g., plots) that can help communicate the results better.

 The course will be explanatory rather than mathematically rigorous. Therefore emphasis is given in sufficient detail for participants to obtain a clear view of the different joint modeling approaches and how they should be used in practice. To this end, we first motivate joint modeling using real datasets and then illustrate in detail the virtues and drawbacks of each of the presented joint modeling approaches. For completeness and throughout the course, references are provided to material with more technical information.

COURSE SCHEDULE

• REGISTRATION

  • 8:30 - 9:00 Registration of the participants

• LUNCH

  • 12:30 - 13:00 Lunch break

• COFFEE BREAKS

  • 10 minutes between the successive sessions

COURSE OUTLINE

• • Session 1: Motivation and Theoretical Background

o   Settings in which joint models are used

o   Basic joint model

o   Coefficients interpretation 

o   Assessing model fit

• Session 2: Extensions

o   Functional forms

o   Dynamic Predictions

• Session 3: Interactive Practical – Build a Basic Joint Model

o   Introduce an example dataset and the motivating research questions

o   Build the mixed and Cox proportional hazards model

o   Fit the joint model and interpret the coefficients

o   Assess model fit using posterior predictive checks

•  Session 4: Interactive Practical – Extend the Joint Model

o   Fit the model with other functional forms and interpret coefficients

o   Calculate predictions for example individuals

o   Validate the derived predictions

REGISTRATION RATES

Early Bird (until 31 July 2021)

ISCB student member* 2 000 CZK (80 EUR)

ISCB regular member* 2 500 CZK (100 EUR)

Non-ISCB member – academia 5 000 CZK (200 EUR)

Non-ISCB member – business 13 250 CZK (530 EUR)

Regular (1 Aug – 29 October 2021)

ISCB student member* 3 000 CZK (120 EUR)

ISCB regular member* 3 750 CZK (150 EUR)

Non-ISCB member – academia 6 250 CZK (250 EUR)

Non-ISCB member – business 16 250 CZK (650 EUR)

(*) Note: ISCB membership is required for 2025 and 2026. For doctoral students, the ISCB membership for 2026 will be sufficient.

Payments by bank transfer ONLY

(All international payments have to be made in EUR)

ACCOUNT INFORMATION

For all domestic (CZK) and international transfers (EUR):

Bank's name and address   Fio banka, a.s., V Celnici 1028/10, Praha 1, Czech Republic

Account owner                      Mezinárodní společnost pro klinickou biostatistiku v České republice, z.s.

Account number                   2100009829 / 2010  

IBAN                                        CZ3820100000002100009829

BIC code/SWIFT                     FIOBCZPPXXX

• For institutions making payments on behalf of their employees: The payment identification number (variabilní symbol) is 20211112

• Please, remember to state the name of an employee on whose behalf the payment is made in the comment for the payment recipient (poznámka pro příjemce).

CANCELLATION INFORMATION

Cancellation fees apply as explained below:

• before 2 October 2026: 20 EUR

• 3 through 15 October 2026: 60 EUR

• after 15 October 2026: full paid amount

COURSE VENUE

Institute of Computer Science, Czech Academy of Sciences, Pod Vodarenskou vezi 2, 182 07 Prague, Czech Republic 

COURSE SECRETARY

Ms. Lenka Semeráková, Institute of Computer Science, Czech Academy of Sciences, tel. +420 266 053 640, e-mail: semerakova@cs.cas.cz