TY - JOUR
T1 - Circular Modelling of Circumplex Measurements for Interpersonal Behavior
AU - Cremers, Jolien
AU - Pennings, Helena J.M.
AU - Mainhard, Tim
AU - Klugkist, Irene
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a Vidi grant awarded to Irene Klugkist from the Dutch Organization for Scientific Research (NWO 452-12-010).
Publisher Copyright:
© The Author(s) 2019.
PY - 2021/3/1
Y1 - 2021/3/1
N2 - This article describes a new way to analyze data from the interpersonal circumplex (IPC) for interpersonal behavior. Instead of analyzing Agency and Communion separately or analyzing the IPC’s octants, we propose using a circular regression model that allows us to investigate effects on a blend of Agency and Communion. The proposed circular model is called a projected normal (PN) model. We illustrate the use of a PN mixed-effects model on three repeated measures data sets with circumplex measurements from interpersonal and educational psychology. This model allows us to detect different types of patterns in the data and provides a more valid analysis of circumplex data. In addition to being able to investigate the effect on the location (mean) of scores on the IPC, we can also investigate effects on the spread (variance) of scores on the IPC. We also introduce new tools that help interpret the fixed and random effects of PN models.
AB - This article describes a new way to analyze data from the interpersonal circumplex (IPC) for interpersonal behavior. Instead of analyzing Agency and Communion separately or analyzing the IPC’s octants, we propose using a circular regression model that allows us to investigate effects on a blend of Agency and Communion. The proposed circular model is called a projected normal (PN) model. We illustrate the use of a PN mixed-effects model on three repeated measures data sets with circumplex measurements from interpersonal and educational psychology. This model allows us to detect different types of patterns in the data and provides a more valid analysis of circumplex data. In addition to being able to investigate the effect on the location (mean) of scores on the IPC, we can also investigate effects on the spread (variance) of scores on the IPC. We also introduce new tools that help interpret the fixed and random effects of PN models.
KW - circular mixed-effects model
KW - embedding approach
KW - interpersonal circle
KW - interpersonal circumplex
KW - interpersonal theory
UR - http://www.scopus.com/inward/record.url?scp=85068589092&partnerID=8YFLogxK
U2 - 10.1177/1073191119858407
DO - 10.1177/1073191119858407
M3 - Article
C2 - 31257905
AN - SCOPUS:85068589092
SN - 1073-1911
VL - 28
SP - 585
EP - 600
JO - Assessment
JF - Assessment
IS - 2
ER -