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http://hdl.handle.net/1942/32304
Title: | Meta-Research on Statistical Methods of Combining Diagnostic Studies | Authors: | Tadger Viloria, Philippe Ferdinand | Advisors: | LESAFFRE, Emmanuel VERDE, Pablo |
Issue Date: | 2020 | Publisher: | tUL | Abstract: | The current study has the following aims: systematically investigating the extent to which results of recently published meta-analyses of diagnostic test accuracy could be biased when the authors have applied classical hierarchical models that implicitly assumed normality. Another aim is to compare results with a ready to use Bayesian hierarchical model. Finally, the study aims to assess the impact of its internal validity when classical hierarchical models are used for meta-analyses and results are compared with an Bayesian hierarchical approach. In classical hierarchical models, studies with a high risk for normality assumption may have: non-convergence issues, profile likelihood irregularities, and non-positive-definite random-effect covariance matrix. In Bayesian hierarchical models, the same studies don’t present any difficulties in the fitting or estimation process | Notes: | Master of Statistics-Biostatistics | Document URI: | http://hdl.handle.net/1942/32304 | Category: | T2 | Type: | Theses and Dissertations |
Appears in Collections: | Master theses |
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d0daeefe-66ec-4eb4-ab2a-d545693c123b.pdf | 4.58 MB | Adobe PDF | View/Open |
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