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Graphical sensitivity analysis with different methods of imputation for a trial with probable non-ignorable missing data

Record type: Conference or Workshop Item (Other)

Graphical sensitivity analyses have recently been recommended for clinical trials with non-ignorable missing binary outcome. We demonstrate an adaptation of this methodology for a continuous outcome of a trial of three cognitive-behavioural therapies for mild depression in primary care, in which one arm had unexpectedly high levels of missing data. Fixed value and multiple imputation from a normal distribution (assuming either varying mean and fixed SD, or fixed mean and varying SD) were used to obtain contour plots of the contrast estimates with their P values superimposed; their confidence interval; and the root mean square error. Imputation was based on both the outcome value alone, or on change from baseline. The plots showed fixed value imputation to be more sensitive than imputing from a normal distribution, but the normally distributed imputations were subject to sampling noise. The contours of the sensitivity plots were close to linear in appearance with the slope approximately equal to the ratio of the proportions of subjects with missing data in each trial arm.

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Citation

Weatherall, Mark, Pickering, R.M. and Harris, S. (2005) Graphical sensitivity analysis with different methods of imputation for a trial with probable non-ignorable missing data At Wellington Statistics Group (WSG). 13 Apr 2005.

More information

Published date: 2005
Venue - Dates: Wellington Statistics Group (WSG), 2005-04-13 - 2005-04-13
Keywords: imputation, missing data, analysis, methods, trial

Identifiers

Local EPrints ID: 62198
URI: http://eprints.soton.ac.uk/id/eprint/62198
PURE UUID: c329a216-52ce-4002-8fcc-a06bbc2202ff

Catalogue record

Date deposited: 17 Apr 2009
Last modified: 17 Jul 2017 14:21

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Contributors

Author: Mark Weatherall
Author: R.M. Pickering
Author: S. Harris

University divisions


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