The Power, Accuracy, and Precision of the Relational Event Model. (October 2021)

• Record Type: Journal Article
• Authors: Schecter, Aaron; Quintane, Eric
• Is Part Of: Organizational research methods. Volume 24:Number 4(2021)
• Page Start: 802
• Page End: 829
• Publication Date: 2021-10
• Subjects: construct validation -- reliability -- validity -- criterion -- predictive validity -- nonlinear modeling -- quantitative research -- longitudinal analysis; Organization -- Research -- Methodology -- Periodicals; Organizational sociology -- Research -- Methodology -- Periodicals; Management -- Research -- Methodology -- Periodicals; 302.350721
• DOI: 10.1177/1094428120963830
• Languages: English
• ISSNs: 1094-4281

Abstract

The relational event model (REM) solves a problem for organizational researchers who have access to sequences of time-stamped interactions. It enables them to estimate statistical models without collapsing the data into cross-sectional panels, which removes timing and sequence information. However, there is little guidance in the extant literature regarding issues that may affect REM's power, precision, and accuracy: How many events or actors are needed? How large should the risk set be? How should statistics be scaled? To gain insights into these issues, we conduct a series of experiments using simulated sequences of relational events under different conditions and using different sampling and scaling strategies. We also provide an empirical example using email communications in a real-life context. Our results indicate that, in most cases, the power and precision levels of REMs are good, making it a strong explanatory model. However, REM suffers from issues of accuracy that can be severe in certain cases, making it a poor predictive model. We provide a set of practical recommendations to guide researchers' use of REMs in organizational research.