Does open peer review improve citation count? Evidence from a propensity score matching analysis of PeerJ
| Autor: | Jiechun Liang, Qianjin Zong, Yafen Xie |
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| Rok vydání: | 2020 |
| Předmět: |
Economic research
Matching (statistics) Computer science Average treatment effect 05 social sciences Confounding General Social Sciences Library and Information Sciences 050905 science studies Computer Science Applications Statistics Propensity score matching Altmetrics 0509 other social sciences 050904 information & library sciences Citation |
| Zdroj: | Scientometrics. 125:607-623 |
| ISSN: | 1588-2861 0138-9130 |
| DOI: | 10.1007/s11192-020-03545-y |
| Popis: | This study aims to investigate whether open peer review can improve citation count. Articles published in PeerJ during 2013 and 2015 were chosen as the data set. Two categories of the articles were generated: articles with closed peer review history and articles with open peer review history. A propensity score matching with the radius matching method was performed using 14 confounding variables. The other five common matching methods of propensity score matching, the bias-adjusted matching estimator developed by Abadie and Imbens (Simple and bias-corrected matching estimators for average treatment effects, National Bureau of Economic Research, Cambridge, pp 1–57, 2002), and the data set excluding articles with an extremely high citation count were used to check the robustness of the results. The results of this study showed that articles with open peer review history could be expected to have significantly greater citation counts than articles with closed peer review history. Our results suggest that open peer review can improve citation count, and that the best practice for open peer review might be a compromise open peer review. |
| Databáze: | OpenAIRE |
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