Missing variability in meta-analysis : is imputing always good?
This paper examines the implications of the present approaches in handling missing variability in meta analysis on the overall standard error (SE) of the estimate. The approaches are (1) exclusion of the studies with missing standard deviations (SDs) and (2) imputation of the missing SDs. The d...
Main Authors: | Nik Idris, Nik Ruzni, Abdullah, Mimi Hafizah |
---|---|
Format: | Proceeding Paper |
Language: | English |
Published: |
2006
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/5555/1/ICSTIE.uitm.pdf |
Similar Items
-
A case study on the effect of imputing the missing variability measures in meta analysis
by: Nik Idris, Nik Ruzni
Published: (2007) -
The effects of imputing the missing standard deviations on the standard error of meta analysis estimates
by: Nik Idris, Nik Ruzni, et al.
Published: (2009) -
An empirical comparison of meta analysis models for continuous data with missing standard deviations
by: Nik Idris, Nik Ruzni, et al.
Published: (2011) -
Estimating the bias in meta analysis estimates for continuous data with non-random missing study variance
by: Nik Idris, Nik Ruzni
Published: (2010) -
Beyond classical meta-analysis: can inadequately reported studies be included?
by: Roberson, Chris, et al.
Published: (2004)