Code Sharing in Psychological Methods and Statistics: An Overview and Associations with Conventional and Alternative Research Metrics
Towards discovering more effective means to promote code sharing as an open science practice, this study explores the current state of code sharing within the field of psychological methods and statistics and examines the association between this practice and conventional and alternative research metrics. Towards this purpose, a total of 815 articles from three major journals within the field of psychological methods and statistics were manually screened and encoded based on code sharing practices and general article characteristics. In addition, data on conventional (citation counts) and alternative research metrics (Altmetric Attention Score) was retrieved through online scientific databases (Web of Science and Altmetric.com). This input was then analysed using descriptive statistics and regression models suitable for count data, and robustness of the findings were assessed using multiverse analysis. The findings of this study suggest that the sharing of scientific computer code is not (yet) extensively practiced within the field of psychological methods and statistics. In the majority of academic articles included in this study, scientific computer code was not shared (66 %). Moreover, if such code was shared, it was frequently found to be improperly annotated (70 %) and/or incomplete (52 %). Nevertheless, the findings of this study also suggest a hopeful prospect, as the sharing of scientific computer code has increased between 2010 and 2017. The study revealed a robust positive connection with alternative research metrics. This study did not find robust positive connection between code sharing and citation counts.