Royal Statistical Society
Highlands Local Group

Local organising Committee


Dr Claus Mayer (Chair)
Biomathematics & Statistics Scotland
Aberdeen AB25 2ZD
Dr David McLernon (Hon Secretary)
Polwarth Building,
Aberdeen AB25 2ZD 
Phone: +44 (0) 1224 438652 Phone: +44 (0) 1224 437152  

We are delighted to announce that Matteo Quartagno, Research Fellow at the London School of Hygiene and Tropical Medicine, will be delivering a talk for the RSS Highlands Local Group on 22nd October. The details are below and the abstract will be announced in due course.

Date: Monday 22nd Oct 2018

Speaker: Matteo Quartagno, Research Fellow, Dept of Medical Statistics, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine

Time: 3pm for 3.30pm start

Venue: Room 115, Health Sciences Building, Foresterhill, UoA, Aberdeen

Title: Handling Missing Multilevel Data with Joint Modelling Multiple Imputation

Abstract: Abstract: Multiple Imputation (MI) is a flexible tool to handle missing data that has been increasingly used in recent years. It broadly consists in filling in the missing values multiple times, creating several completed datasets; these are then analysed with standard techniques obtaining different parameter estimates, that are finally combined with Rubinís rules. One of the conditions for the validity of MI is that the two models used for (i) imputing and (ii) analysing the data need to be compatible. For this reason, when the partially observed data have a multilevel structure, both models need to reflect this. In this talk I am going to present an imputation technique, known as Joint Modelling imputation, based on running an MCMC sampler after defining a joint imputation model for the partially observed variables. This imputation strategy is particularly appealing for imputing data compatibly with a multilevel analysis model and is implemented in the R package jomo. I will explain under which circumstances simple JM imputation works properly, and I will explore possible solutions to situations where it doesnít. Finally I will conclude by outlining plans for future research in this area.

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