A Generalized Publication Bias Model

Statistics – Methodology

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

18 pages, 3 figures

Scientific paper

Scargle (2000) has discussed Rosenthal and Rubin's (1978) "fail-safe number" (FSN) method for estimating the number of unpublished studies in meta-analysis. He concluded that this FSN cannot possibly be correct because a central assumption the authors used conflicts with the very definition of publication bias. While this point has been made by others before (Elsahoff, 1978; Darlington, 1980; Thomas, 1985, Iyengar & Greenhouse, 1988), Scargle showed, by way of a simple 2-parameter model, how far off Rosenthal & Rubin' s estimate can be in practice. However, his results relied on the assumption that the decision variable is normally distributed with zero mean. In this case the ratio of unpublished to published papers is large only in a tiny region of the parameter plane. Building on these results, we now show that (1) Replacing densities with probability masses greatly simplifies Scargle's derivations and permits an explicit statement of the relation between the probability alpha of Type I errors and the step-size beta; (2) This result does not require any distribution assumptions; (3) The distinction between 1-sided and 2-sided rejection regions becomes immaterial; (4) This distribution-free approach leads to an immediate generalization to partitions involving more than two intervals, and thus covers more general selection functions.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A Generalized Publication Bias Model does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Generalized Publication Bias Model, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Generalized Publication Bias Model will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-202491

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.