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dc.contributor.advisorDeboeck, Pacal
dc.contributor.authorGarnier-Villarreal, Mauricio
dc.date.accessioned2014-02-05T16:34:40Z
dc.date.available2014-02-05T16:34:40Z
dc.date.issued2013-12-31
dc.date.submitted2013
dc.identifier.otherhttp://dissertations.umi.com/ku:13166
dc.identifier.urihttp://hdl.handle.net/1808/12978
dc.description.abstractWe examine longitudinal extensions of the two-method measurement design, which uses planned missingness to optimize cost-efficiency and validity of hard-to-measure constructs. These designs use a combination of two measures: a "gold standard" that is highly valid but expensive to administer, and an inexpensive (e.g., survey-based) measure that contains systematic measurement bias (e.g., response bias). Using simulated data on 4 measurement occasions, we compared the cost-efficiency and validity of longitudinal designs where the gold standard is measured at one or more measurement occasions. We manipulated the nature of the response bias over time (constant, increasing, fluctuating), the factorial structure of the response bias over time, and the constraints placed on the latent variable model. Our results showed that parameter bias is lowest when the gold standard is measured on at least two occasions. When a multifactorial structure was used to model response bias over time, estimation difficulties were common. Almost all parameters in all conditions displayed high relative efficiency, suggesting that the 2-method design is an effective way to reduce costs and improve power and accuracy in longitudinal research.
dc.format.extent49 pages
dc.language.isoen
dc.publisherUniversity of Kansas
dc.rightsThis item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
dc.subjectQuantitative psychology
dc.subjectPsychometrics
dc.subjectIntentionally missing data
dc.subjectMissing data
dc.subjectPlanned missingness
dc.subjectSimsem
dc.subjectStructural equation modeling
dc.subjectTwo-method measurement
dc.titleTWO-METHOD PLANNED MISSING DESIGNS FOR LONGITUDINAL RESEARCH
dc.typeThesis
dc.contributor.cmtememberLittle, Todd D.
dc.contributor.cmtememberJohnson, David
dc.thesis.degreeDisciplinePsychology
dc.thesis.degreeLevelM.A.
kusw.oastatusna
dc.identifier.orcidhttps://orcid.org/0000-0002-2951-6647
kusw.oapolicyThis item does not meet KU Open Access policy criteria.
kusw.bibid8086518
dc.rights.accessrightsopenAccess


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