Graphical sensitivity analysis with different methods of imputation for a trial with probable non-ignorable missing data
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), Lambton Quay, New Zealand, 13 Apr 2005. New Zealand, New Zealand Statistical Association (NZSA).
Full text not available from this repository.
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.
|Item Type:||Conference or Workshop Item (Speech)|
|Keywords:||imputation, missing data, analysis, methods, trial|
|Subjects:||R Medicine > R Medicine (General)
H Social Sciences > HA Statistics
|Divisions :||University Structure - Pre August 2011 > School of Medicine > Community Clinical Sciences
|Accepted Date and Publication Date:||
|Date Deposited:||17 Apr 2009|
|Last Modified:||31 Mar 2016 12:45|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)