Biostatistical Models for Joint Longitudinal and Survival Data in Medical Research.

Date and time: 
Thu, 2018-05-17 09:29

Dr. Edmund Njeru Njagi will be running a five day course in"Biostatistical Models for Joint Longitudinal and Survival Data in Medical Research".

  • Dr. Edmund Njeru Njagi teaches Medical Statistics and conducts research in biostatistics and cancer epidemiology at the London School of Hygiene & Tropical Medicine. His interests include joint modelling of multivariate longitudinal and time to event data, and missing data.
  • read more about him from the link below
  • https://www.lshtm.ac.uk/aboutus/people/njagi.edmund-njeru

Contents 

This five-day course introduces longitudinal and joint modelling techniques for medical research. We will begin with methods for exploring longitudinal data, followed by the theory and application of linear mixed models. Next, we will look at joint models for multivariate longitudinal data, discussing in detail the shared and correlated random effects joint models. Moving on to joint models for longitudinal and survival data, we will first study their formulation and estimation. Next, we will consider different parameterizations of these models, before concluding with techniques for dynamically predicting survival status using longitudinal and survival data.

OBJECTIVES

  • Longitudinal and survival data are common in medical research. Examples include longitudinal CD4 counts and survival time in HIV research, and longitudinal prostate specific antigen measurements and time to recurrence in cancer research. This workshop aims to introduce longitudinal and joint modelling techniques used to answer the various medical research questions relevant in these settings. Starting with motivating medical research data and analysis objectives, formulation of these models will be explained. This will be coupled with practical illustrations on conducting these analyses using R software, interpretation of results, and drawing relevant conclusions.

Workshop Components

  • The workshop consists of five days, covering a wide range of practical topics:
  • Statistical software: getting familiar with R statistical software for longitudinal and joint modelling.
  • Modelling data: how to formulate and apply longitudinal and joint models for the problem at hand.

Required knowledge
Basic knowledge of linear regression, survival analysis, and R software is advisable. The requisite elements of these three components will however be briefly reviewed during the course.

Softwares
Statistical models introduced in this workshop will be illustrated in R statistical software.
R is available as Free Software and runs under Windows and Macintosh. It can be downloaded at https://cran.rproject.org/. It is recommended that participants install the software beforehand.

Venue
Faculty of Science Boardroom, Chiromo Campus,University of Nairobi
Date and Time
6 – 10 August 2018 from 08.30 – 17.00 everyday

Registration FEE

The registration fee is Two Thousand Kenyan Shillings (KShs. 2,000)

PAYMENT DETAILS.

Payments can be made via Mpesa.

MPESA to number: +254725878750, the receiver’s name is Dr. Rachel Sarguta. Registration will be finalized once fee is received.
 

Registration Contacts:
School of Mathematics, University of Nairobi
Tel: +254-725-878750, + 254-704-315332, and +254-780-834766
Email: maths@uonbi.ac.ke, rsarguta@uonbi.ac.ke, and onyango@uonbi.ac.ke

click the button below to register

 

Note

Limited financial support is available for Master’s and PhD- students from partner universities except JKUAT and University of Nairobi, to participate in this workshop. Approximately two applicants for these scholarships from partner universities shall be supported.
For more information contact:
1. Dr. Nelson Owuor
Tel: +254704315332
Email: onyango@uonbi.ac.ke
2. Dr. Rachel Sarguta
Tel: 254725878750
Email: rsarguta@uonbi.ac.ke
3. Prof. Dr. Roel Braekers
Email: roel.braekers@uhasselt.be
Registration Deadline is strictly: July 31, 2018
Number of participants: The number of participants is limited to 50.

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This course was Sponsored by Sponsored by VLIR-UOS  

partners 

Expiry Date: 
Thu, 2018-05-17 09:29

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