Circular Modelling of Circumplex Measurements for Interpersonal Behavior

Area of Science:

• Psychology
• Behavioral Science
• Statistical Modeling

Background:

• The interpersonal circumplex (IPC) is a common model for understanding interpersonal behavior.
• Traditional analysis of IPC data often involves separate examination of Agency and Communion or octant-based approaches, which may limit insights.
• A need exists for more integrated and nuanced methods to analyze circumplex data.

Purpose of the Study:

• To introduce a new circular regression model, the projected normal (PN) model, for analyzing interpersonal circumplex data.
• To provide a method for investigating effects on combined aspects of Agency and Communion.
• To enhance the validity and depth of analysis for circumplex measurements.

Main Methods:

• Development and application of a projected normal (PN) mixed-effects model.
• Utilizing the PN model on three repeated measures datasets with circumplex measurements.
• Introducing new tools for interpreting fixed and random effects within the PN model.

Main Results:

• The PN model allows for the investigation of effects on a blend of Agency and Communion, moving beyond separate analyses.
• The model can detect diverse patterns within interpersonal behavior data.
• Analysis of both the location (mean) and spread (variance) of scores on the IPC is possible.

Conclusions:

• The projected normal (PN) model offers a more valid and comprehensive approach to analyzing interpersonal circumplex data.
• This method provides deeper insights into interpersonal behavior by examining combined Agency and Communion.
• The developed tools facilitate a better understanding of complex effects in psychological data.