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 Science Limited
2004
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/5556/1/DDT_beyond_classical_MA.pdf http://irep.iium.edu.my/5556/ http://www.sciencedirect.com/science/article/pii/S135964460403274X |
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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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