An empirical assessment of meta-analysis estimates from multi-level studies
A conventional meta-analysis may be performed using studies which are available at individual patient level (IPD) or aggregate level (AD). Presently however, meta-analysis that combine the two levels of studies is increasingly common. The implications of utilising different levels of data on the ove...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/45232/1/IREP.pdf http://irep.iium.edu.my/45232/3/conference_program-_kuala_lumpur_oct-ver06.pdf http://irep.iium.edu.my/45232/ http://npcst2015.weebly.com/ |
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| Summary: | A conventional meta-analysis may be performed using studies which are available at individual patient level (IPD) or aggregate level (AD). Presently however, meta-analysis that combine the two levels of studies is increasingly common. The implications of utilising different levels of data on the overall estimates have not been fully explored. Objective: This study examined the efficacy of the estimates of overall treatment effect from AD, IPD and the mixed AD: IPD studies, and investigated how they differ from the true treatment effect. Additionally, this study investigated the influence of the ratio of AD: IPD on the precision of the overall treatment effects estimates. The bias, root mean-square-error (RMSE) and coverage probability were used to assess the efficiency of the overall estimates. Results: The results showed that the IPD meta-analysis produced better estimates in terms of RMSE compared to AD meta-analysis and the mixed AD:IPD meta-analysis. For the cases where both the AD and IPD studies were available, our findings showed that the combined AD : IPD data produced better estimates, in terms of precision, than utilising the AD alone. Conclusion: It is therefore recommended that available IPD should always be included in a conventional meta-analysis using summary level data as significant |
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