A longitudinal multilevel CFA-MTMM model for interchangeable and structurally different methods

Frontiers in Psychology

Tobias Koch¹ 

关键词: multilevel structural equation modeling;    longitudinal modeling;    MTMM modeling;    multirater data;    rater bias;    method effects;    simulation study;   

DOI  :  10.3389/fpsyg.2014.00311

学科分类：心理学（综合）

来源: Frontiers

【 摘 要 】

One of the key interests in the social sciences is the investigation of change and stability of a given attribute. Although numerous models have been proposed in the past for analyzing longitudinal data including multilevel and/or latent variable modeling approaches, only few modeling approaches have been developed for studying the construct validity in longitudinal multitrait-multimethod (MTMM) measurement designs. The aim of the present study was to extend the spectrum of current longitudinal modeling approaches for MTMM analysis. Specifically, a new longitudinal multilevel CFA-MTMM model for measurement designs with structurally different and interchangeable methods (called Latent-State-Combination-Of-Methods model, LS-COM) is presented. Interchangeable methods are methods that are randomly sampled from a set of equivalent methods (e.g., multiple student ratings for teaching quality), whereas structurally different methods are methods that cannot be easily replaced by one another (e.g., teacher, self-ratings, principle ratings). Results of a simulation study indicate that the parameters and standard errors in the LS-COM model are well recovered even in conditions with only five observations per estimated model parameter. The advantages and limitations of the LS-COM model relative to other longitudinal MTMM modeling approaches are discussed.

【 授权许可】

CC BY