Konstantinos C. Fragkos

arXiv2015

Exploring the Distribution for the Estimator of Rosenthal's 'Fail-Safe' Number of Unpublished Studies in Meta-analysis

The present paper discusses the statistical distribution for the estimator of Rosenthal's 'Fail-Safe' number NR, which is an estimator of unpublished studies in meta-analysis. We calculate the probability distribution function of NR. This is achieved based on the Central Limit Theorem and the proposition that certain components of the estimator NR follow a half normal distribution, derived from the standard normal distribution. Our proposed distributions are supported by simulations and investigation of convergence.

stat.ME↗

arXiv2015

Publication Bias in Meta-Analysis: Confidence Intervals for Rosenthal's Fail-Safe Number

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.

stat.ME↗