Beyond classical meta-analysis: Can inadequately reported studies be included?
Classical meta-analysis requires the same data from each clinical trial, thus data-reporting must be of a high-quality. Imputation methods are used to include studies that provide incomplete information on variability and the fixed and random effects of a drug. Regression models can be used to inclu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2004
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| Online Access: | http://eprints.utm.my/id/eprint/7379/1/Nik_Rumzi_Nik_Idris_2004_Beyond_Classical_Meta-analysis.pdf http://eprints.utm.my/id/eprint/7379/ http://dx.doi.org/10.1016/S1359-6446(04)03274-X |
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| Summary: | Classical meta-analysis requires the same data from each clinical trial, thus data-reporting must be of a high-quality. Imputation methods are used to include studies that provide incomplete information on variability and the fixed and random effects of a drug. Regression models can be used to include studies other than randomized placebo-controlled studies. In the example outlined here, the use of non-randomized single-arm studies and studies against comparator treatments has little influence on the estimation of the treatment effect in comparison with placebo, an effect that is based on the randomized placebo-controlled studies. The inclusion of other studies serves to increase the precision of the effect of the treatment compared with baseline. Although multiple imputation techniques enable a larger number of studies to be included, which will typically increase the precision of the estimated effect, a careful sensitivity analysis is also required. |
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