Goodness of Fit Tools for Dose-Response Meta-Analysis of Binary Outcomes
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| Title: | Goodness of Fit Tools for Dose-Response Meta-Analysis of Binary Outcomes |
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| Language: | English |
| Authors: | Discacciati, Andrea, Crippa, Alessio, Orsini, Nicola |
| Source: | Research Synthesis Methods. Jun 2017 8(2):149-160. |
| Availability: | Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA |
| Peer Reviewed: | Y |
| Page Count: | 12 |
| Publication Date: | 2017 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Goodness of Fit, Research Tools, Meta Analysis, Evaluation Methods |
| DOI: | 10.1002/jrsm.1194 |
| ISSN: | 1759-2879 |
| Abstract: | Goodness of fit evaluation should be a natural step in assessing and reporting dose-response meta-analyses from aggregated data of binary outcomes. However, little attention has been given to this topic in the epidemiological literature, and goodness of fit is rarely, if ever, assessed in practice. We briefly review the two-stage and one-stage methods used to carry out dose-response meta-analyses. We then illustrate and discuss three tools specifically aimed at testing, quantifying, and graphically evaluating the goodness of fit of dose-response meta-analyses. These tools are the deviance, the coefficient of determination, and the decorrelated residuals-versus-exposure plot. Data from two published meta-analyses are used to show how these three tools can improve the practice of quantitative synthesis of aggregated dose-response data. In fact, evaluating the degree of agreement between model predictions and empirical data can help the identification of dose-response patterns, the investigation of sources of heterogeneity, and the assessment of whether the pooled dose-response relation adequately summarizes the published results. |
| Abstractor: | As Provided |
| Entry Date: | 2020 |
| Accession Number: | EJ1256728 |
| Database: | ERIC |
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| Abstract: | Goodness of fit evaluation should be a natural step in assessing and reporting dose-response meta-analyses from aggregated data of binary outcomes. However, little attention has been given to this topic in the epidemiological literature, and goodness of fit is rarely, if ever, assessed in practice. We briefly review the two-stage and one-stage methods used to carry out dose-response meta-analyses. We then illustrate and discuss three tools specifically aimed at testing, quantifying, and graphically evaluating the goodness of fit of dose-response meta-analyses. These tools are the deviance, the coefficient of determination, and the decorrelated residuals-versus-exposure plot. Data from two published meta-analyses are used to show how these three tools can improve the practice of quantitative synthesis of aggregated dose-response data. In fact, evaluating the degree of agreement between model predictions and empirical data can help the identification of dose-response patterns, the investigation of sources of heterogeneity, and the assessment of whether the pooled dose-response relation adequately summarizes the published results. |
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| ISSN: | 1759-2879 |
| DOI: | 10.1002/jrsm.1194 |
