The Forward Search Algorithm for Detecting Aberrant Response Patterns in Factor Analysis for Binary Data

dc.contributor.authorMavridis, D.en
dc.contributor.authorMoustaki, I.en
dc.date.accessioned2015-11-24T17:44:55Z
dc.date.available2015-11-24T17:44:55Z
dc.identifier.issn1061-8600-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/14962
dc.rightsDefault Licence-
dc.subjectlatent variable modelsen
dc.subjectmaskingen
dc.subjectoutliersen
dc.subjectrobustnessen
dc.subjectswampingen
dc.subjectmultiple outliersen
dc.subjectmodelsen
dc.subjectfiten
dc.titleThe Forward Search Algorithm for Detecting Aberrant Response Patterns in Factor Analysis for Binary Dataen
heal.abstractIn this article we implement a for-ward search algorithm for identifying atypical subjects/observations in factor analysis models for binary data. Forward plots of goodness-of-fit statistics, residuals, and parameter estimates help us identify aberrant observations and detect deviations from the hypothesized model, Methods to initialize, progress, and monitor the search are explored. Simulation envelopes are constructed to investigate whether changes in the statistics being monitored are solely due to random variation. One real and two simulated datasets are used to illustrate the performance of the suggested algorithm. The two simulated datasets explore the effectiveness of the method in the presence of a single outlier and a cluster of outliers. Matlab computer code for implementing, the proposed methods is available online.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.primaryDOI 10.1198/jcgs.2009.08060-
heal.identifier.secondary<Go to ISI>://000273082500013-
heal.identifier.secondaryhttp://amstat.tandfonline.com/doi/abs/10.1198/jcgs.2009.08060-
heal.journalNameJournal of Computational and Graphical Statisticsen
heal.journalTypepeer-reviewed-
heal.languageen-
heal.publicationDate2009-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Αγωγής. Παιδαγωγικό Τμήμα Δημοτικής Εκπαίδευσηςel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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