A case study on the effect of imputing the missing variability measures in meta analysis

A Meta Analysis is a statistical technique for integrating quantitative results of the same research question from several sources. It is being applied in various disciplines including the medical and social sciences research,. One of the common problems with meta analysis data is when the vari...

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Main Author: Nik Idris, Nik Ruzni
Format: Proceeding Paper
Language:English
Published: 2007
Subjects:
Online Access:http://irep.iium.edu.my/5553/1/ICOBM07.bandung.pdf
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author Nik Idris, Nik Ruzni
author_facet Nik Idris, Nik Ruzni
author_sort Nik Idris, Nik Ruzni
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description A Meta Analysis is a statistical technique for integrating quantitative results of the same research question from several sources. It is being applied in various disciplines including the medical and social sciences research,. One of the common problems with meta analysis data is when the variability measures, specifically, the standard deviations are not reported in the individual studies. Current approaches in handling this problem is either to exclude the studies with the missing standard deviations or to impute the standard deviations. This paper examines and compares meta analysis estimates based on these two approaches using a meta analysis of all studies on the effectiveness of Transurethral Needle Ablation (TUNA) for treatment of Benign Prostatic Hyperplasia (BPH) patients. The results show that the estimates of treatment effects are more precise with inclusion of more studies using the imputed standard deviations. Additionally, the estimates are robust against different values of the correlation coefficients.
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spelling oai:generic.eprints.org:55532012-08-16T07:38:32Z http://irep.iium.edu.my/5553/ A case study on the effect of imputing the missing variability measures in meta analysis Nik Idris, Nik Ruzni HA Statistics A Meta Analysis is a statistical technique for integrating quantitative results of the same research question from several sources. It is being applied in various disciplines including the medical and social sciences research,. One of the common problems with meta analysis data is when the variability measures, specifically, the standard deviations are not reported in the individual studies. Current approaches in handling this problem is either to exclude the studies with the missing standard deviations or to impute the standard deviations. This paper examines and compares meta analysis estimates based on these two approaches using a meta analysis of all studies on the effectiveness of Transurethral Needle Ablation (TUNA) for treatment of Benign Prostatic Hyperplasia (BPH) patients. The results show that the estimates of treatment effects are more precise with inclusion of more studies using the imputed standard deviations. Additionally, the estimates are robust against different values of the correlation coefficients. 2007-08-27 Proceeding Paper NonPeerReviewed application/pdf en http://irep.iium.edu.my/5553/1/ICOBM07.bandung.pdf Nik Idris, Nik Ruzni (2007) A case study on the effect of imputing the missing variability measures in meta analysis. In: International Conference on BioMathematics, 27-29 August 2007, Bandung, Indonesia. http://icomb07.math.itb.ac.id
spellingShingle HA Statistics
Nik Idris, Nik Ruzni
A case study on the effect of imputing the missing variability measures in meta analysis
title A case study on the effect of imputing the missing variability measures in meta analysis
title_full A case study on the effect of imputing the missing variability measures in meta analysis
title_fullStr A case study on the effect of imputing the missing variability measures in meta analysis
title_full_unstemmed A case study on the effect of imputing the missing variability measures in meta analysis
title_short A case study on the effect of imputing the missing variability measures in meta analysis
title_sort case study on the effect of imputing the missing variability measures in meta analysis
topic HA Statistics
url http://irep.iium.edu.my/5553/1/ICOBM07.bandung.pdf
work_keys_str_mv AT nikidrisnikruzni acasestudyontheeffectofimputingthemissingvariabilitymeasuresinmetaanalysis
AT nikidrisnikruzni casestudyontheeffectofimputingthemissingvariabilitymeasuresinmetaanalysis