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| Main Authors: | , , |
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| Format: | Recurso educativo Open Access |
| Language: | en |
| Published: |
2017
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| Online Access: | https://eric.ed.gov/?id=EJ1256813 |
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| _version_ | 1867181869895778304 |
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| author | Fanshawe, Thomas R. Shaw, Luke F. Spence, Graeme T. |
| author_facet | Fanshawe, Thomas R. Shaw, Luke F. Spence, Graeme T. Fanshawe, Thomas R. Shaw, Luke F. Spence, Graeme T. |
| collection | Education Resources Information Center |
| contents | A Large-Scale Assessment of Temporal Trends in Meta-Analyses Using Systematic Review Reports from the Cochrane Library Fanshawe, Thomas R. Shaw, Luke F. Spence, Graeme T. Meta Analysis Intervention Databases Medical Research Trend Analysis Least Squares Statistics Predictor Variables Research Reports Outcomes of Treatment Models Introduction: Previous studies suggest that many systematic reviews contain meta-analyses that display temporal trends, such as the first study's result being more extreme than later studies' or a drift in the pooled estimate. We assessed the extent and characteristics of temporal trends using all Cochrane intervention reports published 2008-2012. Methods: We selected the largest meta-analysis within each report and analysed trends using methods including a Z -test (first versus subsequent estimates); generalised least squares; and cumulative sum charts. Predictors considered include meta-analysis size and review group. Results: Of 1288 meta-analyses containing at least 4 studies, the point estimate from the first study was more extreme and in the same direction as the pooled estimate in 738 (57%), with a statistically significant difference (first versus subsequent) in 165 (13%). Generalised least squares indicated trends in 717 (56%); 18% of fixed effects analyses had at least one violation of cumulative sum limits. For some methods, meta-analysis size was associated with temporal patterns and use of a random effects model, but there was no consistent association with review group. Conclusions: All results suggest that more meta-analyses demonstrate temporal patterns than would be expected by chance. Hence, assuming the standard meta-analysis model without temporal trend is sometimes inappropriate. Factors associated with trends are likely to be context specific. |
| format | Recurso educativo Open Access |
| id | eric_EJ1256813 |
| institution | ERIC Institute of Education Sciences |
| language | en |
| publishDate | 2017 |
| record_format | eric |
| spellingShingle | A Large-Scale Assessment of Temporal Trends in Meta-Analyses Using Systematic Review Reports from the Cochrane Library Fanshawe, Thomas R. Shaw, Luke F. Spence, Graeme T. Meta Analysis Intervention Databases Medical Research Trend Analysis Least Squares Statistics Predictor Variables Research Reports Outcomes of Treatment Models A Large-Scale Assessment of Temporal Trends in Meta-Analyses Using Systematic Review Reports from the Cochrane Library Fanshawe, Thomas R. Shaw, Luke F. Spence, Graeme T. Meta Analysis Intervention Databases Medical Research Trend Analysis Least Squares Statistics Predictor Variables Research Reports Outcomes of Treatment Models Introduction: Previous studies suggest that many systematic reviews contain meta-analyses that display temporal trends, such as the first study's result being more extreme than later studies' or a drift in the pooled estimate. We assessed the extent and characteristics of temporal trends using all Cochrane intervention reports published 2008-2012. Methods: We selected the largest meta-analysis within each report and analysed trends using methods including a Z -test (first versus subsequent estimates); generalised least squares; and cumulative sum charts. Predictors considered include meta-analysis size and review group. Results: Of 1288 meta-analyses containing at least 4 studies, the point estimate from the first study was more extreme and in the same direction as the pooled estimate in 738 (57%), with a statistically significant difference (first versus subsequent) in 165 (13%). Generalised least squares indicated trends in 717 (56%); 18% of fixed effects analyses had at least one violation of cumulative sum limits. For some methods, meta-analysis size was associated with temporal patterns and use of a random effects model, but there was no consistent association with review group. Conclusions: All results suggest that more meta-analyses demonstrate temporal patterns than would be expected by chance. Hence, assuming the standard meta-analysis model without temporal trend is sometimes inappropriate. Factors associated with trends are likely to be context specific. |
| title | A Large-Scale Assessment of Temporal Trends in Meta-Analyses Using Systematic Review Reports from the Cochrane Library |
| topic | Meta Analysis Intervention Databases Medical Research Trend Analysis Least Squares Statistics Predictor Variables Research Reports Outcomes of Treatment Models |
| url | https://eric.ed.gov/?id=EJ1256813 |