Psi Training Course s1
presented by
Geert Verbeke and Geert Molenberghs
(Interuniversity Institute for Biostatistics and Statistics Bioinformatics,
Katholieke Universiteit Leuven and Universiteit Hasselt)
on 26 & 27 September 2016
Venue:
/ The Royal Statistical Society, 12 Errol Street, London, EC1Y 8LXNearest Tube stations: Barbican, Liverpool Street, Moorgate, Old Street
Course Summary: / The course begins with a brief presentation of linear mixed models for continuous hierarchical data. The course focus is from the modeller’s perspective and on applications. Emphasis will be on model formulation, parameter estimation, and hypothesis testing, as well as on the distinction between the random-effects (hierarchical) model and the implied marginal model. Models for non-Gaussian data will be discussed, with a strong emphasis on generalized estimating equations (GEE) and the generalized linear mixed model (GLMM). A brief review of the classical generalized linear modelling framework will be presented. Similarities and differences with the continuous case will be discussed. The differences between marginal models, such as GEE, and random-effects models, such as the GLMM, will be explained in detail. Focus will be primarily on binary outcomes, however, GEE and GLMM model formulations will also be covered. When analysing hierarchical and longitudinal data, one is often confronted with missing observations, i.e. scheduled measurements have not been made, due to a variety of (known or unknown) reasons. It will be shown that, if no appropriate measures are taken, missing data can seriously jeopardize results, and interpretation difficulties are bound to occur. Methods to properly analyse incomplete data, under flexible assumptions, will be presented.
All topics will be illustrated with worked examples using SAS. While there are no hands-on practical sessions, the course notes include worked examples with annotated programs and output from SAS, discussed in such a way that they are also of use to non-SAS-users.
Learning Outcomes:
/ Participants should be able to perform a basic analysis for a particular longitudinal data set at hand, using linear, generalized linear and non-linear tools for longitudinal data. Based on a selection of exploratory tools, the nature of the data, and the research questions to be answered in the analyses, they should be able to construct an appropriate statistical model, to fit the model within the SAS framework, and to interpret the obtained results. Further, participants should be aware not only of the possibilities and strengths of a particular selected approach, but also of its drawbacks in comparison to other methods.Topics
Covered:
/ Day 1: Linear mixed models, model formulation, parameter interpretation, hierarchical versus marginal model interpretation, estimation and inference, empirical Bayes, model families for discrete outcomes, marginal models and generalized estimating equations (GEE).Day 2: Generalized mixed models, estimation methods (Laplace, MQL, PQL, Quadrature), comparison with GEE, missing data mechanisms, problems with non-random dropout (i.e., bias, loss of efficiency, etc.), modelling frameworks to handle dropout (selection, pattern mixture and shared parameter models), sensitivity analyses.
Knowledge Assumed:
/ Throughout the course, it will be assumed that the participants are familiar with basic statistical modelling, including linear models (regression and analysis of variance), as well as generalized linear models (logistic and Poisson regression). Pre-requisite knowledge should also include general estimation and testing theory (maximum likelihood, likelihood ratio).Course
Format:
/ Registration begins at 09.30 and the course runs from 10.00 until 17.00 on 28 September and from 09.30 to 17.00 on 29 September.Fees
(incl VAT)
/ Registration before 26 August 2016 / Registration on / after 26 August 2016/ Non Member
RSS Fellow
RSS CStat: also MIS, FIS & GradStat / £562.50+vat
£478.12+vat
£450+vat / £625+vat
£531.25+vat
£500+vat
Contact:
/ Tessa Pearson, Royal Statistical Society, 12 Errol Street, London EC1Y 8LX.Tel: +44 (0)20 7614 3947 Email: Fax: +44 (0)20 7614 3905
Non members are welcome to join the Society at the same time as registering for the course and the discount received will cover the cost of their first subscription payment. More information about membership can be found at www.rss.org.uk/join
REGISTRATION FORMLONGITUDINAL AND MISSING DATA – 26 & 27 SEPTEMBER 2016
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CStat, MIS, FIS and GradStat (£450+vat) £540.00 □ / Non member (£625+vat) £750.00 □
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CStat, MIS, FIS and GradStat (£500+vat) £600.00 □
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Please return completed form to: / Tessa Pearson, Royal Statistical Society, 12 Errol Street, London EC1Y 8LX, UK
Tel: +44 (0)20 7614 3947 Email: Fax: +44 (0)20 7614 3905