Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14740

Title: Modeling actor and partner effects in dyadic data when outcomes are categorical
Authors: Loeys, Tom
Molenberghs, Geert
Issue Date: 2013
Citation: Psychological methods, 18 (2), p. 220-236
Abstract: When 2 people interact in a relationship, the outcome of each person can be affected by both his or her own inputs and his or her partner's inputs. For Gaussian dyadic outcomes, linear mixed models taking into account the correlation within dyads are frequently used to estimate actor's and partner's effects based on the actor–partner interdependence model. In this article, we explore the potential of generalized linear mixed models (GLMMs) for the analysis of non- Gaussian dyadic outcomes. Several approximation techniques that are available in standard software packages for these GLMMs are investigated. Despite the different modeling options related to these different techniques, none of these have an overall satisfactory performance in estimating actor and partner effects and the within-dyad correlation, especially when the latter is negative and/or the number of dyads is small. An approach based on generalized estimating equations for the analysis of non-Gaussian dyadic data turns out to be an interesting alternative.
Notes: Reprint Address: Loeys, T (reprint author) - Univ Ghent, Dept Data Anal, Henri Dunantlaan 1, B-9000 Ghent, Belgium. E-mail Addresses:tom.loeys@ugent.be
URI: http://hdl.handle.net/1942/14740
DOI: 10.1037/a0030640
ISI #: 000320404300006
ISSN: 1082-989X
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
Published version1.86 MBAdobe PDF
Peer-reviewed author version1.27 MBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.