Longitudinal Methods.

Khoo, Siek-Toon; West, Stephen G.; Wu, Wei; Kwok, Oi‐Man

doi:10.1037/11383-021

Cited by 60 publications

(42 citation statements)

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“…An increasing body of research is devoted to longitudinal data analysis examining the change and stability of a given attribute across time (see Singer and Willett, 2003; Khoo et al, 2006). The prominence of longitudinal studies may be explained by the fact that longitudinal measurement designs bear many advantages.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2014

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2014

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“…Given that the transition from adolescence into early adulthood is a period of considerable developmental change, research in this area would benefit from the development of a comprehensive measure of CU traits that has been validated for use across this time period. This would allow for the examination of the stability of these features over time without the introduction of unwanted variance in test scores due to measurement differences (Khoo et al 2006). However, nearly all youth measures of this construct have yet to be validated for use within young adult populations (for exception see Campbell et al 2009).…”

Section: Introductionmentioning

confidence: 99%

A Validation of the Inventory of Callous-Unemotional Traits in a Community Sample of Young Adult Males

Byrd

Kahn

Pardini

2012

J Psychopathol Behav Assess

107

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Callous-unemotional (CU) traits have been shown to delineate a subgroup of individuals at high risk for exhibiting severe and persistent criminal behavior. The Inventory of Callous-Unemotional Traits (ICU; Frick 2004) was recently developed as a comprehensive rating scale designed to measure multiple facets of CU traits. However, validation of this measure has been limited to youth in adolescence and emerging adulthood (age range=12–20), leaving questions about the utility of this measure in early adulthood unanswered. The current study evaluated the factor structure of the ICU within a racially diverse and well characterized community sample of adult males (n=425) using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). While results found the best fitting model to be the three-bifactor structure that has been previously reported in adolescent samples, the fit indices were only marginally acceptable and suggest the need for scale refinement. Total and subscales scores demonstrated significant and distinct associations with relevant external criteria (e.g., delinquency, psychopathy, psychopathology, psychosocial functioning). Implications and directions for future research are discussed.

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“…Thus, ordered-categorical CFA will often be the approach of choice when measured indicators are ordered-categorical. Methods of establishing longitudinal measurement invariance for ordered-categorical indicators within the CFA framework build on the foundations of tests of multiple-group measurement invariance for continuous indicators (Meredith, 1993; Widaman & Reise, 1997), tests of longitudinal measurement invariance for continuous indicators (Meredith & Horn, 2001; Khoo et al, 2006), and CFA models for ordered-categorical indicators (Muthén, 1984; Wirth & Edwards, 2007). …”

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confidence: 99%

Testing measurement invariance in longitudinal data with ordered-categorical measures.

Liu¹,

Millsap²,

West³

et al. 2017

Psychological Methods

Self Cite

269

361

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A goal of developmental research is to examine individual changes in constructs over time. The accuracy of the models answering such research questions hinges on the assumption of longitudinal measurement invariance: The repeatedly measured variables need to represent the same construct in the same metric over time. Measurement invariance can be studied through factor models examining the relations between the observed indicators and the latent constructs. In longitudinal research ordered-categorical indicators such as self- or observer-report Likert scales are commonly used, and these measures often do not approximate continuous normal distributions. The present didactic paper extends previous work on measurement invariance to the longitudinal case for ordered-categorical indicators. We address a number of problems that commonly arise in testing measurement invariance with longitudinal data including model identification and interpretation, sparse data, missing data, and estimation issues. We also develop a procedure and associated R program for gauging the practical significance of the violations of invariance. We illustrate these issues with an empirical example using a subscale from the Mexican American Cultural Values scale. Finally, we provide comparisons of the current capabilities of three major latent variable programs (lavaan, Mplus, OpenMx) and computer scripts for addressing longitudinal measurement invariance.

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Longitudinal Methods.

Cited by 60 publications

References 0 publications

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

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

A Validation of the Inventory of Callous-Unemotional Traits in a Community Sample of Young Adult Males

Testing measurement invariance in longitudinal data with ordered-categorical measures.

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