DOI: 10.1101/500660Dec 29, 2018Paper

Analysis of >30,000 abstracts suggests higher false discovery rates for oncology journals, especially those with low impact factors

BioRxiv : the Preprint Server for Biology
Lauren May Hall, Audrey E Hendricks

Abstract

Background: Recently, there has been increasing concern about the replicability, or lack thereof, of published research. An especially high rate of false discoveries has been reported in some areas motivating the creation of resource-intensive collaborations to estimate the replication rate of published research by repeating a large number of studies. The substantial amount of resources required by these replication projects limits the number of studies that can be repeated and consequently the generalizability of the findings. Methods and findings: In 2013, Jager and Leek developed a method to estimate the empirical false discovery rate from journal abstracts and applied their method to five high profile journals. Here, we use the relative efficiency of Jager and Leek's method to gather p-values from over 30,000 abstracts and to subsequently estimate the false discovery rate for 94 journals over a five-year time span. We model the empirical false discovery rate by journal subject area (cancer or general medicine), impact factor, and Open Access status. We find that the empirical false discovery rate is higher for cancer vs. general medicine journals (p = 5.14E-6). Within cancer journals, we find that this relationship is furth...Continue Reading

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