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ALLSTAT  February 2007

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Subject:

RSS joint Med Sec. & GAS half day meeting on Statistics in mental health research: 21st March

From:

Gordon Taylor <[log in to unmask]>

Reply-To:

Gordon Taylor <[log in to unmask]>

Date:

Fri, 9 Feb 2007 10:12:47 +0000

Content-Type:

text/plain

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Statistics in Mental Health Research

For all section and study group meetings held at the RSS pre-registration is recommended.  You can register by email:
[log in to unmask] or by phone (020) 7638 8998.

 Time 2.00-6.00

 Venue (Errol Street unless otherwise specified)

 Meeting organized by           GAS and Medical Section           

Meeting organiser: Sabine Landau and Ian White

Contact details: [log in to unmask] <mailto:[log in to unmask]> 
and [log in to unmask] <mailto:[log in to unmask]>

2:00-2:30pm Graham Dunn (Biostatistics Group, University of Manchester)

 Modelling treatment-effect heterogeneity in RCTs of psychological 
treatments

I describe instrumental variable (IV) methods for the estimation of the 
'dose'-response effects of psychological interventions in RCTs in which 
there is variability in the number of sessions of therapy attended, the 
effect of which is modified by the strength of the therapeutic alliance 
between patients and their therapists.  The IV methods allow for (a) 
hidden confounding, (b) measurement errors and (c) that alliance is only 
measured in those receiving treatment.

Three two-stage estimation procedures are illustrated, and their 
equivalence demonstrated, through Monte Carlo simulation and analysis of 
the results of an actual trial (SoCRATES).  

 

2:30-3:00pm Morven Leese (Health Service and Population Research 
Department, Institute of Psychiatry, KCL, London)

 Aggregate scores as psychiatric outcomes

In the QUATRO trial of therapy to improve adherence to antipsychotic 
medication, fifteen outcomes, covering adherence, symptoms and quality 
of life, were collected. This large number of multiple measures is 
typical of psychiatric research. However, despite the appeal of a wide 
perspective on treatment outcome, a smaller set of primary outcomes is 
generally required for clinical trials. One solution, the combination of 
measures into aggregate scores, is discussed in this talk. The focus is 
on assessing the reliability of the resulting scores rather than on the 
specific rationale for combination. Various ways of combining the eight 
subscales of the SF-36 (one of the quality-of-life measures used in the 
QUATRO trial) are compared in an illustrative example.

 
3:00-3:30pm Tim Croudace (Department of Psychiatry, University of Cambridge)

 "Latent Goldberg" - psychometric statistics

and the General Health Questionnaire

Epidemiological studies often use psychometric instrumentation from 
Goldberg's GHQ family to assess psychiatric morbidity. New psychometric 
models at the interface between latent variable models, mixture models 
and multilevel models enable applied researchers to model GHQ 
questionnaire responses at the item level in many subtly different ways 
that go beyond the somewhat blunt approach of the traditional linear 
factor model. Examples of alternative latent structure models for GHQ 
data will be introduced. Insights as to how these models may be extended 
will also be discussed.


4:00-4:30pm Mick Brammer (Department of Biostatistics and Computing, 
Institute of Psychiatry, KCL, London)

Some issues arising in the statistical analysis of functional fMRI data

Functional magnetic resonance imaging (fMRI) is a very widely used 
method for imaging human brain function in vivo. This increasing level 
of use means that statisticians working in the field of medicine may 
encounter such data and be asked to offer advice on analysis. The aim 
here is to explain the basic features of fMRI data sets and to introduce 
some of the approaches to analysis and inference based both on 
adaptations of standard inferential procedures and on data-driven 
permutation-based approaches.

 

4:30-5:00pm Chris Roberts (Biostatistics Group, University of Manchester)

 The design and analysis of clinical trials of non-pharmacological 
therapies.

The issue of clustering effects due to treatments in individually 
randomised trials, whilst long-recognised is generally ignored in both 
design and analysis. Such effects may be hypothesised in trials of 
psychological treatment involving talking therapies and where treatment 
is delivered to patients together as a group rather, for example group 
therapies for psychological problems. As with group-randomised trials, 
between cluster variation can lead to lack of independence between 
patients' outcomes. The implications of this for design, including 
sample size estimation, and statistical analysis will be discussed.

 

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