Performance of selected imputation techniques for missing variances in meta-analysis

Nik Idris, Nik Ruzni and Abdullah, Mimi Hafizah and Tolos, Siti Marponga (2013) Performance of selected imputation techniques for missing variances in meta-analysis. Journal of Physics: Conference Series, 435 (1). 012037. ISSN 1742-6588 (P), 1742-6596 (O)

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Abstract

A common method of handling the problem of missing variances in meta-analysis of continuous response is through imputation. However, the performance of imputation techniques may be influenced by the type of model utilised. In this article, we examine through a simulation study the effects of the techniques of imputation of the missing SDs and type of models used on the overall meta-analysis estimates. The results suggest that imputation should be adopted to estimate the overall effect size, irrespective of the model used. However, the accuracy of the estimates of the corresponding standard error (SE) is influenced by the imputation techniques. For estimates based on the fixed effects model, mean imputation provides better estimates than multiple imputation, while those based on the random effects model are the more robust of the imputation techniques used. The results showed that although imputation is good in reducing the bias in point estimates, it is however more likely to produce coverage probability higher than the nominal value

Item Type:	Article (Journal)
Additional Information:	4059/30252
Uncontrolled Keywords:	Computational physics Statistical physics and nonlinear systems
Subjects:	Q Science > QA Mathematics
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Science > Department of Computational and Theoretical Sciences
Depositing User:	Dr Nik Ruzni Nik Idris
Date Deposited:	05 Aug 2013 14:13
Last Modified:	28 Nov 2014 11:45
URI:	http://irep.iium.edu.my/id/eprint/30252

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