Explaining General and Specific Factors in Longitudinal, Multimethod, and Bifactor Models: Some Caveats and Recommendations

Tobias Koch; Jana Holtmann; Johannes Bohn; Michael Eid

doi:10.1037/met0000146

Explaining General and Specific Factors in Longitudinal, Multimethod, and Bifactor Models: Some Caveats and Recommendations

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Transfer › begutachtet

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Explaining General and Specific Factors in Longitudinal, Multimethod, and Bifactor Models: Some Caveats and Recommendations. / Koch, Tobias; Holtmann, Jana; Bohn, Johannes et al.
in: Psychological Methods, Jahrgang 23, Nr. 3, 09.2018, S. 505-523.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Transfer › begutachtet

Bibtex

@article{24c67dabfe204a13ab4f2763afc3509d,

title = "Explaining General and Specific Factors in Longitudinal, Multimethod, and Bifactor Models: Some Caveats and Recommendations",

abstract = "An increasing number of psychological studies are devoted to the analysis of g-factor structures. One key purpose of applying g-factor models is to identify predictors or potential causes of the general and specific effects. Typically, researchers relate predictor variables directly to the general and specific factors using a classical mimic approach. However, this procedure bears some methodological challenges, which often lead to model misspecification and biased parameter estimates. We propose 2 possible modeling strategies to circumvent these problems: the multiconstruct bifactor and the residual approach. We illustrate both modeling approaches for the application of g-factor models to longitudinal and multitrait-multimethod data. Practical guidelines are provided for choosing an appropriate method in empirical applications, and the implications of this investigation for multimethod and longitudinal research are discussed.",

keywords = "Psychology, Bifactor models, CTC(M-1) model, G-factor models, Latent state-trait models, MIMIC models",

author = "Tobias Koch and Jana Holtmann and Johannes Bohn and Michael Eid",

year = "2018",

month = sep,

doi = "10.1037/met0000146",

language = "English",

volume = "23",

pages = "505--523",

journal = "Psychological Methods",

issn = "1082-989X",

publisher = "American Psychological Association Inc.",

number = "3",

}

RIS

TY - JOUR

T1 - Explaining General and Specific Factors in Longitudinal, Multimethod, and Bifactor Models

T2 - Some Caveats and Recommendations

AU - Koch, Tobias

AU - Holtmann, Jana

AU - Bohn, Johannes

AU - Eid, Michael

PY - 2018/9

Y1 - 2018/9

N2 - An increasing number of psychological studies are devoted to the analysis of g-factor structures. One key purpose of applying g-factor models is to identify predictors or potential causes of the general and specific effects. Typically, researchers relate predictor variables directly to the general and specific factors using a classical mimic approach. However, this procedure bears some methodological challenges, which often lead to model misspecification and biased parameter estimates. We propose 2 possible modeling strategies to circumvent these problems: the multiconstruct bifactor and the residual approach. We illustrate both modeling approaches for the application of g-factor models to longitudinal and multitrait-multimethod data. Practical guidelines are provided for choosing an appropriate method in empirical applications, and the implications of this investigation for multimethod and longitudinal research are discussed.

AB - An increasing number of psychological studies are devoted to the analysis of g-factor structures. One key purpose of applying g-factor models is to identify predictors or potential causes of the general and specific effects. Typically, researchers relate predictor variables directly to the general and specific factors using a classical mimic approach. However, this procedure bears some methodological challenges, which often lead to model misspecification and biased parameter estimates. We propose 2 possible modeling strategies to circumvent these problems: the multiconstruct bifactor and the residual approach. We illustrate both modeling approaches for the application of g-factor models to longitudinal and multitrait-multimethod data. Practical guidelines are provided for choosing an appropriate method in empirical applications, and the implications of this investigation for multimethod and longitudinal research are discussed.

KW - Psychology

KW - Bifactor models

KW - CTC(M-1) model

KW - G-factor models

KW - Latent state-trait models

KW - MIMIC models

UR - http://www.scopus.com/inward/record.url?scp=85025116674&partnerID=8YFLogxK

U2 - 10.1037/met0000146

DO - 10.1037/met0000146

M3 - Journal articles

C2 - 28737413

VL - 23

SP - 505

EP - 523

JO - Psychological Methods

JF - Psychological Methods

SN - 1082-989X

IS - 3

ER -

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