Multimethod latent class analysis

Nussbeck FW, Eid M (2015)
Frontiers in Psychology 6: 1332.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
Correct and, hence, valid classifications of individuals are of high importance in the social sciences as these classifications are the basis for diagnoses and/or the assignment to a treatment. The via regia to inspect the validity of psychological ratings is the multitrait-multimethod (MTMM) approach. First, a latent variable model for the analysis of rater agreement (latent rater agreement model) will be presented that allows for the analysis of convergent validity between different measurement approaches (e.g., raters). Models of rater agreement are transferred to the level of latent variables. Second, the latent rater agreement model will be extended to a more informative MTMM latent class model. This model allows for estimating (i) the convergence of ratings, (ii) method biases in terms of differential latent distributions of raters and differential associations of categorizations within raters (specific rater bias), and (iii) the distinguishability of categories indicating if categories are satisfyingly distinct from each other. Finally, an empirical application is presented to exemplify the interpretation of the MTMM latent class model.
Stichworte
log-linear modeling; rater bias; MTMM-analysis; rater agreement; latent-class analysis
Erscheinungsjahr
2015
Zeitschriftentitel
Frontiers in Psychology
Band
6
Art.-Nr.
1332
ISSN
1664-1078
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Deutsche Forschungsgemeinschaft und die Universität Bielefeld gefördert.
Page URI
https://pub.uni-bielefeld.de/record/2777484

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Nussbeck FW, Eid M. Multimethod latent class analysis. Frontiers in Psychology. 2015;6: 1332.
Nussbeck, F. W., & Eid, M. (2015). Multimethod latent class analysis. Frontiers in Psychology, 6, 1332. doi:10.3389/fpsyg.2015.01332
Nussbeck, Fridtjof W., and Eid, Michael. 2015. “Multimethod latent class analysis”. Frontiers in Psychology 6: 1332.
Nussbeck, F. W., and Eid, M. (2015). Multimethod latent class analysis. Frontiers in Psychology 6:1332.
Nussbeck, F.W., & Eid, M., 2015. Multimethod latent class analysis. Frontiers in Psychology, 6: 1332.
F.W. Nussbeck and M. Eid, “Multimethod latent class analysis”, Frontiers in Psychology, vol. 6, 2015, : 1332.
Nussbeck, F.W., Eid, M.: Multimethod latent class analysis. Frontiers in Psychology. 6, : 1332 (2015).
Nussbeck, Fridtjof W., and Eid, Michael. “Multimethod latent class analysis”. Frontiers in Psychology 6 (2015): 1332.
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32 References

Daten bereitgestellt von Europe PubMed Central.

Modelling patterns of agreement and disagreement.
Agresti A., Stat Methods Med Res 1(2), 1992
PMID: 1341658

Agresti A.., 2013

AUTHOR UNKNOWN, 2013
Clinical psychology: construct validation with multiple sources of information and multiple settings
Burns G., Haynes S.., 2006
Convergent and discriminant validation by the multitrait-multimethod matrix.
CAMPBELL DT, FISKE DW., Psychol Bull 56(2), 1959
PMID: 13634291
Structural equation models for multitrait-multimethod data
Eid M., Lischetzke T., Nussbeck F.., 2006
A Bayesian analysis of some nonparametric problems
Ferguson T.., 1973
Latent class analysis in medical research.
Formann AK, Kohlmann T., Stat Methods Med Res 5(2), 1996
PMID: 8817797
On the accuracy of personality judgment: a realistic approach.
Funder DC., Psychol Rev 102(4), 1995
PMID: 7480467
Testing log-linear models with inequality constraints: a comparison of asymptotic, bootstrap, and posterior predictive p-values
Galindo-Garre F., Vermunt J.., 2005
Avoiding boundary estimates in latent class analysis by Bayesian posterior mode estimation
Galindo-Garre F., Vermunt J.., 2006
The analysis of systems of qualitative variables when some of the variables are unobservable: a modified latent structure approach
Goodman L.., 1974
Exploratory latent structure-analysis using both identifiable and unidentifiable models
Goodman L.., 1974

Habermann S.., 1979

Hagenaars J.., 1990

Hagenaars J.., 1993

Heinen A.., 1993
WinBUGS - a Bayesian modelling framework: concepts, structure, and extensibility
Lunn D., Thomas A., Best N., Spiegelhalter D.., 2000
Modeling interinformant agreement in the absence of a "gold standard".
Baillargeon RH, Boulerice B, Tremblay RE, Zoccolillo M, Vitaro F, Kohen DE., J Child Psychol Psychiatry 42(4), 2001
PMID: 11383962
Assessing multimethod association with categorical variables
Nussbeck F.., 2006

Nussbeck F.., 2009
Estimating with a latent class model the reliability of nominal judgments upon which two raters agree
Schuster C., Smith D.., 2006

van F., Langeheine R., de W.., 1996
Causal log-linear modelling with latent variables and missing data
Vermunt J.., 1996

Vermunt J.., 1997

Vermunt J.., 1997
Multilevel latent class models
Vermunt J.., 2003
Latent class and finite mixture models for multilevel data sets.
Vermunt JK., Stat Methods Med Res 17(1), 2007
PMID: 17855746

Vermunt J., Magidson J.., 2005

Wickens T.., 2002
Another look at interrater agreement.
Zwick R., Psychol Bull 103(3), 1988
PMID: 3380931
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