- Title
- Prior sensitivity analysis for a hierarchical model
- Creator
- Junaidi; Stojanovski, E.; Nur, D.
- Relation
- 4th Applied Statistics Education and Research Collaboration (ASEARC) Conference. Proceedings of the 4th Applied Statistics Education and Research Collaboration (ASEARC) Conference (Parramatta, NSW 17-18 February, 2011) p. 64-67
- Relation
- http://eis.uow.edu.au/asearc/4thAnnResCon/index.html
- Publisher
- University of Wollongong
- Resource Type
- conference paper
- Date
- 2011
- Description
- Meta-analysis can be presented in the Frequentist or Bayesian framework. Based on the model of DuMouchel, a simulation study is conducted which fixes the overall mean and variance-covariance matrix to generate estimates of the true mean effect. These estimates will be compared to the true effect to assess bias. A sensitivity analysis, to measure the robustness of results to the selection of prior distributions, is conducted by employing Uniform and Pareto distributions for the variance components, the t-distribution for the overall mean component and a combination of priors for both variance and mean components respectively. Results were more sensitive when the prior was changed only on the overall mean component.
- Subject
- sensitivity analysis; hierarchical Bayesian model; meta-analysis
- Identifier
- http://hdl.handle.net/1959.13/1051724
- Identifier
- uon:15309
- Identifier
- ISBN:9781741281958
- Language
- eng
- Full Text
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