Abstract
Meta-analysts rely on the availability of data from previously conducted studies. That is, they rely on primary study authors to register their outcome data, either in a study’s text or on publicly available websites, and report the results of their work, either again in a study’s text or on publicly accessible data repositories. If a primary study author does not register data collection and similarly does not report the data collection results, the meta-analyst is at risk of failing to include the collected data. The purpose of this study is to attempt to locate one type of meta-analytic data: findings from studies that neither registered nor reported the collected outcome data. To do so, we conducted a large-scale search for potential studies and emailed an author query request to more than 600 primary study authors to ask if they had collected eligible outcome data. We received responses from 75 authors (12.3%), three of whom sent eligible findings. The results of our search confirmed our proof of concept (i.e., that authors collect data but fail to register or report it publicly), and the meta-analytic results indicated that excluding the identified studies would change some of our substantive conclusions. Cost analyses indicated, however, a high price to finding the missing studies. We end by reaffirming our calls for greater adoption of primary study pre-registration as well as data archiving in publicly available repositories.
Highlights
The former US Secretary of Defense, Mr Donald Rumsfeld, in 2002, popularized the quotation at the beginning of this article as well as the complimentary knownunknown matrix by using the phrase “unknown-unknowns,” which refers to the phenomenon where one does not know what one does not know
The current research project is driven by a specific dissemination and publication bias question that is difficult to answer: can we locate outcomes that primary study authors never registered or reported publicly?. The purpose of this project is to answer this question, which is further divided into three sections
This work derives from an ongoing meta-analysis, which we registered on the Open Science Framework
Summary
The former US Secretary of Defense, Mr Donald Rumsfeld, in 2002, popularized the quotation at the beginning of this article as well as the complimentary knownunknown matrix by using the phrase “unknown-unknowns,” which refers to the phenomenon where one does not know what one does not know. The quotation garnered Mr Rumsfeld media attention and public scrutiny, yet the “unknown-unknowns” concept was a common approach to understanding organizational or project risk management [10]. The matrix is divided into four quadrants based on the cross-section of two axes representing a continuum from known to unknown (Table 1). The upper left quadrant represents knownknowns, or recognized ideas that provide the primary basis for knowledge and decision-making. The lower left-hand corner represents concepts that we recognize exist, but do not have information to process a decision or evaluate a risk. The upper right-hand column, on the other hand, signifies information we have available but do not understand where it might be useful, or which problem it might solve
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