Abstract
The authors elaborate the complications and the opportunities inherent in the statistical analysis of small-group data. They begin by discussing nonindependence of group members' scores and then consider standard methods for the analysis of small-group data and determine that these methods do not take into account this nonindependence. A new method is proposed that uses multilevel modeling and allows for negative nonindependence and mutual influence. Finally, the complications of interactions, different group sizes, and differential effects are considered. The authors strongly urge that the analysis model of data from small-group studies should mirror the psychological processes that generate those data.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
