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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24009

Title: A Mixed Model to Disentangle Variance and Serial Autocorrelation in Affective Instability Using Ecological Momentary Assessment Data
Authors: Vansteelandt, Kristof
Verbeke, Geert
Issue Date: 2016
Abstract: Affective instability, the tendency to experience emotions that fluctuate frequently and intensively over time, is a core feature of several mental disorders including borderline personality disorder. Currently, affect is often measured with Ecological Momentary Assessment protocols, which yield the possibility to quantify the instability of affect over time. A number of linear mixed models are proposed to examine (diagnostic) group differences in affective instability. The models contribute to the existing literature by estimating simultaneously both the variance and serial dependency component of affective instability when observations are unequally spaced in time with the serial autocorrelation (or emotional inertia) declining as a function of the time interval between observations. In addition, the models can eliminate systematic trends, take between subject differences into account and test for (diagnostic) group differences in serial autocorrelation, short-term as well as long-term affective variability. The usefulness of the models is illustrated in a study on diagnostic group differences in affective instability in the domain of eating disorders. Limitations of the model are that they pertain to group (and not individual) differences and do not focus explicitly on circadian rhythms or cycles in affect.
URI: http://hdl.handle.net/1942/24009
DOI: 10.1080/00273171.2016.1159177
ISI #: 000382588600002
ISSN: 0027-3171
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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