Causal modelling in randomised trials: applications and extensions of finite mixture models

Thursday, 26 November 2015
9.30am - 10.30am
Ella Latham Theatre, Royal Children's Hospital
Ground floor, 50 Flemington Rd
Parkville 3052

Understanding treatment effect heterogeneity is an important aspect of randomised trials, and process variables describing the intervention content are crucial components of this. Frequently these variables can only be measured in intervention groups.

Principal stratification, whereby control group participants are assigned to the latent class they would have been in had they been randomised to intervention, has been proposed for analysing this problem and is often estimated using finite mixture models. This estimates an estimand known as the principal stratum direct effect. The standard principal stratification approach generally makes use of a single observation of the process and outcome variables, which more realistically have repeated measures collected.

This principal stratification approach to evaluation will be illustrated using randomised trials comparing psychotherapy with treatment as usual in patients with recent onset of psychosis where the process measure is the therapeutic alliance or therapeutic empathy between the therapist and patient.  We extend this to account for repeated measures of the process variables and outcomes using general growth mixture models. We will discuss the estimation of these models, comparing the traditional one-step approach with a recently proposed three-step procedure. 

Dr Richard Emsley

Dr Richard Emsley

Centre for Biostatistics
The University of Manchester

Richard is a Senior Lecturer in Biostatistics in the Centre for Biostatistics. He is also Visiting Lecturer in the Department of Biostatistics at the Institute of Psychiatry, Psychology and Neuroscience at King's College London. His research aims to answer three key questions: Are treatments effective? How do they work? Which groups are they most effective for? This involves the development of statistical methods for causal inference, efficacy and mechanisms evaluation and stratified medicine. He is the initiator and Chair of the steering group for the UK Causal Inference Meeting (UK-CIM).  He is involved in stratified medicine research programmes in schizophrenia, psoriasis, arthritis and cancer.


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