Fragkos, Konstantinos C. and Tsagris, Michail and Frangos, Christos C. (2014): Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal’s Fail-Safe Number. Published in: International Scholarly Research Notices , Vol. 2014, (December 2014): pp. 1-17.
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Abstract
The purpose of the present paper is to assess the efficacy of confidence intervals for Rosenthal’s fail-safe number. Although Rosenthal’s estimator is highly used by researchers, its statistical properties are largely unexplored. First of all, we developed statistical theory which allowed us to produce confidence intervals for Rosenthal’s fail-safe number.This was produced by discerning whether the number of studies analysed in a meta-analysis is fixed or random. Each case produces different variance estimators. For a given number of studies and a given distribution, we provided five variance estimators. Confidence intervals are examined with a normal approximation and a nonparametric bootstrap. The accuracy of the different confidence interval estimates was then tested by methods of simulation under different distributional assumptions. The half normal distribution variance estimator has the best probability coverage. Finally, we provide a table of lower confidence intervals for Rosenthal’s estimator.
Item Type: | MPRA Paper |
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Original Title: | Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal’s Fail-Safe Number |
English Title: | Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal’s Fail-Safe Number |
Language: | English |
Keywords: | Meta-analysis, Rosenthal's fail safe number, file-drawer problem, bootstrap |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C18 - Methodological Issues: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C19 - Other |
Item ID: | 66451 |
Depositing User: | Mr Michail Tsagris |
Date Deposited: | 05 Sep 2015 19:17 |
Last Modified: | 28 Sep 2019 17:06 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/66451 |