Estimating the bias in meta analysis estimates for continuous data with non-random missing study variance

Nik Idris, Nik Ruzni (2011) Estimating the bias in meta analysis estimates for continuous data with non-random missing study variance. Matematika, 27 (2). pp. 121-128. ISSN 0127-8274

PDF (Estimating the Bias In Meta Analysis Estimates For Continuous Data With Non-Random Missing Study Variance ) - Published Version Restricted to Registered users only Download (102kB) | Request a copy

Abstract

This paper examines, analytically, the biases introduced in the meta analysis estimates when the study-level variances are missing with non-random missing mechanism (MNAR). Two common approaches in handling this problem is considered, namely, the missing variances are imputed, and the studies with missing study variances are omitted from the analysis. The results suggest the variance will be underestimated if the magnitude of the study-variances that are missing are mostly larger implying false impression of precision. On the other hand, if the missing variances are mostly smaller, the variance of the e®ect size will be overestimated.

Item Type:	Article (Journal)
Additional Information:	4059/7219
Uncontrolled Keywords:	meta analysis; variance estimates; not missing at random; imputation
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:	03 Feb 2012 07:46
Last Modified:	03 Feb 2012 07:46
URI:	http://irep.iium.edu.my/id/eprint/7219

Actions (login required)

View Item