A Multimethod Latent State-Trait Model for Structurally Different and Interchangeable Methods

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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A Multimethod Latent State-Trait Model for Structurally Different and Interchangeable Methods. / Koch, Tobias; Schultze, Martin; Holtmann, Jana et al.

in: Psychometrika, Jahrgang 82, Nr. 1, 01.03.2017, S. 17-47.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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Koch T, Schultze M, Holtmann J, Geiser C, Eid M. A Multimethod Latent State-Trait Model for Structurally Different and Interchangeable Methods. Psychometrika. 2017 Mär 1;82(1):17-47. doi: 10.1007/s11336-016-9541-x

Bibtex

@article{6ae07a7108134becbb81ca18f6b8c97d,
title = "A Multimethod Latent State-Trait Model for Structurally Different and Interchangeable Methods",
abstract = "A new multiple indicator multilevel latent state-trait (LST) model for the analysis of multitrait–multimethod–multioccasion (MTMM-MO) data is proposed. The LST-COM model combines current CFA-MTMM modeling approaches of interchangeable and structurally different methods and LST modeling approaches. The model enables researchers to specify construct and method factors on the level of time-stable (trait) as well as time-variable (occasion-specific) latent variables and analyze the convergent and discriminant validity among different rater groups across time. The statistical performance of the model is scrutinized by a simulation study and guidelines for empirical applications are provided.",
keywords = "Economics, empirical/statistics, CFA-MTMM, interchangeable methods, latent state-trait (LST) theory, multilevel structural equation modeling, structurally different methods",
author = "Tobias Koch and Martin Schultze and Jana Holtmann and Christian Geiser and Michael Eid",
year = "2017",
month = mar,
day = "1",
doi = "10.1007/s11336-016-9541-x",
language = "English",
volume = "82",
pages = "17--47",
journal = "Psychometrika",
issn = "0033-3123",
publisher = "Springer New York LLC",
number = "1",

}

RIS

TY - JOUR

T1 - A Multimethod Latent State-Trait Model for Structurally Different and Interchangeable Methods

AU - Koch, Tobias

AU - Schultze, Martin

AU - Holtmann, Jana

AU - Geiser, Christian

AU - Eid, Michael

PY - 2017/3/1

Y1 - 2017/3/1

N2 - A new multiple indicator multilevel latent state-trait (LST) model for the analysis of multitrait–multimethod–multioccasion (MTMM-MO) data is proposed. The LST-COM model combines current CFA-MTMM modeling approaches of interchangeable and structurally different methods and LST modeling approaches. The model enables researchers to specify construct and method factors on the level of time-stable (trait) as well as time-variable (occasion-specific) latent variables and analyze the convergent and discriminant validity among different rater groups across time. The statistical performance of the model is scrutinized by a simulation study and guidelines for empirical applications are provided.

AB - A new multiple indicator multilevel latent state-trait (LST) model for the analysis of multitrait–multimethod–multioccasion (MTMM-MO) data is proposed. The LST-COM model combines current CFA-MTMM modeling approaches of interchangeable and structurally different methods and LST modeling approaches. The model enables researchers to specify construct and method factors on the level of time-stable (trait) as well as time-variable (occasion-specific) latent variables and analyze the convergent and discriminant validity among different rater groups across time. The statistical performance of the model is scrutinized by a simulation study and guidelines for empirical applications are provided.

KW - Economics, empirical/statistics

KW - CFA-MTMM

KW - interchangeable methods

KW - latent state-trait (LST) theory

KW - multilevel structural equation modeling

KW - structurally different methods

U2 - 10.1007/s11336-016-9541-x

DO - 10.1007/s11336-016-9541-x

M3 - Journal articles

C2 - 27905055

VL - 82

SP - 17

EP - 47

JO - Psychometrika

JF - Psychometrika

SN - 0033-3123

IS - 1

ER -

DOI