Seminars


For further information on any CSM events please e-mail: csm@lshtm.ac.uk.


Centre for Statistical Methodology Seminar
Health Economics Theme
Friday 29 June 2018, 12:45-2:00pm
LG9, Keppel Street
Experiences of structured elicitation cost-effectiveness analyses
Marta Soares (University of York)

Abstract: Empirical evidence supporting the cost-effectiveness estimates of particular health care technologies may be limited, or it may even be missing entirely. In these situations, additional information, often in the form of expert judgments, is needed to reach a decision. There are formal methods to quantify experts’ beliefs, termed as structured expert elicitation (SEE), but only limited research is available in support of methodological choices. Perhaps as a consequence, the use of SEE in the context of cost-effectiveness modelling is limited. This talk will be based on a recently published paper (https://www.sciencedirect.com/science/article/pii/S1098301518302274) that reviews applications of SEE in cost-effectiveness modelling with the aim of summarizing the basis for methodological choices made in each application and recording the difficulties and challenges reported by the authors in the design, conduct, and analyses. This talk will also summarise plans for the additional work to be conducted within an MRC funded project on elicitation for health care decision making.

Centre for Statistical Methodology Seminar
Monday 2 July 2018, 12:45-2:00pm
LG7, Keppel Street
Bayesian treatment comparison using parametric mixture priors computed from elicited histograms
Moreno Ursino (Cordeliers Research Centre, Paris)

Abstract: A pervasive problem in randomized clinical trials in children or rare diseases is that the sample size often is too small to obtain a confirmatory conclusion using conventional statistical methods. We propose a Bayesian methodology for constructing a parametric prior on two treatment effect parameters, based on information elicited from expert physicians. The motivating application is a 70-patient randomized trial to compare two treatments for idiopathic nephrotic syndrome in children. Before the trial, 17 experts provided their opinions about the treatment effect for each arm constructing manually histograms using the “bins-and-chips” graphical method. For each physician and treatment, a marginal prior, characterized by location and precision, was fit to each elicited histogram. Bivariate expert-specific priors were constructed using two correlated latent expert effects, using either of two proposed methods. An overall prior was constructed as a mixture of the individual physicians’ priors, with three possible weighting schemes. A framework was provided for performing a sensitivity analysis of posterior inferences to prior bias and precision. A simulation study evaluating several versions of the methodology for binary outcomes was presented.  The methodology provides a practical way to incorporate expert opinion, with the prior-to-posterior sensitivity analysis allowing non-statisticians to draw their own conclusions in an informed way.

Centre for Statistical Methodology Seminar
Missing Data & Measurement Error Theme
Friday 6 July 2018, 12:45-2:00pm
LG8, Keppel Street
Generating multiple imputation from multiple models to reflect missing data mechanism uncertainty: Application to a longitudinal clinical trial
Prof Ofer Harel (University of Connecticut)

Abstract: We present a framework for generating multiple imputations for continuous variables when the missing data are assumed to be nonignorably missing. Imputations are generated from more than one imputation model in order to incorporate uncertainty regarding the missing data mechanism. Parameter estimates based on the dierent imputation models are combined using rules for nested multiple imputation. Through the use of simulation, we investigate the impact of missing data mechanism uncertainty on post-imputation inferences and show that incorporating this uncertainty can increase the coverage of parameter estimates. We apply our method to a longitudinal clinical trial of low-income women with depression where nonignorably missing data were a concern. We show that dierent assumptions regarding the missing data mechanism can have a substantial impact on inferences. Our method provides a simple approach for formalizing subjective notions regarding nonresponse so that they can be easily stated, communicated, and compared. This is a joint work with Juned Siddique and Catherine Crespi.

Centre for Statistical Methodology Seminar
Friday 28 September 2018, 12:45-2:00pm
LG9, Keppel Street
Title TBC
Lucia Petito (Harvard School of Public Health)

Centre for Statistical Methodology Seminar
Friday 26 October 2018, 12:45-2:00pm
LG9, Keppel Street
Title TBC
Alexina Mason (LSHTM)

Centre for Statistical Methodology Seminar
Clinical Trials Theme

Friday 2 November 2018, 12:45-2:00pm
LG9, Keppel Street
Title TBC
Sofia Villar (MRC Biostatistics Unit, Cambridge)

Centre for Statistical Methodology Seminar
Clinical Trials Theme

Friday 23 November 2018, 12:45-2:00pm
LG9, Keppel Street
Title TBC
Prof Lucinda Billingham (University of Birmingham)