Parsimonious Structural Equation Models for Repeated Measures Data, with Application to the Study of Consumer Preferences
Journal
Psychometrika
ISSN
0033-3123
ISSN-Digital
1860-0980
Type
journal article
Date Issued
2012-04
Author(s)
Abstract
Recent research reflects a growing awareness of the value of using structural equation models to analyze repeated measures data. However, such data, particularly in the presence of covariates, often lead to models that either fit the data poorly, are exceedingly general and hard to interpret, or are specified in a manner that is highly data dependent. This article introduces methods for developing parsimonious models for such data. The underlying technology uses reduced-rank representations of the variances, covariances and means of observed and latent variables. The value of this approach, which may be implemented using standard structural equation modeling software, is illustrated in an application study aimed at understanding heterogeneous consumer preferences. In this application, the parsimonious representations characterize systematic relationships among consumer demographics, attitudes and preferences that would otherwise be undetected. The result is a model that is parsimonious, illuminating, and fits the data well, while keeping data dependence to a minimum.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Springer Verlag
Publisher place
Heidelberg
Volume
77
Number
02
Start page
358
End page
387
Pages
30
Subject(s)
Division(s)
Eprints ID
220719