The Flow Short Scale (FSS) Dimensionality and What MIMIC Shows on Heterogeneity and Invariance

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The "3-faced construct validation method" is a routine for establishing the validity and reliability of an existing scale when adapted in a different cultural context from the context initially developed. This routine can also be used for the initial validation of a newly developed scale. This is essentially a construct validation procedure based on a sample-splitting. The sample is randomly split into three parts, 20% for EFA, 40% for an exploratory CFA and 40% for a cross-validating CFA. The cases per variable threshold is set above 5:1, preferably above 10:1 (minimum conditions) and the first approximately 20% subsample emerges (adequate conditions) to evaluate EFA and Bifactor EFA models. Then the cases per variable threshold is set above 10:1, preferably above 20:1 (minimum conditions) and the 40% subsample emerges (adequate conditions) to examine alternative CFA models (ICM-CFA, Bifactor CFA, ESEM and Bifactor ESEM models). The optimal model(s) is cross-validated by a second CFA in yet another 40% subsample (equal-power CFA sample) as a protection against overfitting (over-optimization) to safeguard model replicability. Measurement invariance follows and is essentially another cross-check of the optimal model over the entire sample because the optimal model is used as the baseline model.

Section: Resultsmentioning

confidence: 99%

Section: T a Kyriazosmentioning

confidence: 99%

Section: T a Kyriazosmentioning

confidence: 99%

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Applied Psychometrics: The 3-Faced Construct Validation Method, a Routine for Evaluating a Factor Structure

Kyriazos¹

2018

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“…For the later, both the Mather and the father version were included to check reflected rejection of adult participants during their childhood, by both parents (see Rohner, 1975Rohner, , 2004. The 3-faced construct validation method (Kyriazos, 2018a) could not be implemented because of the sample size (see also Kyriazos et al, 2018;Kyriazos 2018aKyriazos , 2018b.…”

Section: Discussionmentioning

confidence: 99%

Interpersonal Rejection Anxiety Questionnaire (IRAQ): Psychometric Properties of the Greek Version

Kyriazos¹,

Giotsa²

2019

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The purpose of this work was to evaluate the psychometric properties of the Interpersonal Relationship Anxiety Questionnaire (IRAQ) in Greek adults of the general population. The single factor structure of IRAQ was verified for the Greek context. We used CFA with covariates (MIMIC modeling) for the evaluation of invariance in multiple groups, regressing the latent variables and indicators onto three covariates: 1) age, 2) gender, 3) relationship status. The direct effects of the covariates on interpersonal anxiety were not statistically significant. That is the mean of interpersonal anxiety is not different at different levels of the covariates. Thus, population heterogeneity was absent in IRAQ. The direct effects of the three covariates on all indicators of interpersonal anxiety were not statistically significant. Thus, measurement invariance was supported. Additionally, reliability was adequate. Finally, correlation analysis revealed expected relations with fear of interpersonal relationships and parental rejection. IRAQ is a reliable and valid measure to use in the Greek context.

“…On the other hand, methods 1 Construct Validity can be assessed by other methods along with MTMM. See Kyriazos et al (2018aKyriazos et al ( , 2018bKyriazos et al ( , 2018cKyriazos et al ( , 2018d for applied examples of construct validation studies. Psychology can encompass different occasions, or means of data collection (e.g., self-report, structured interview and observation), or multiple-test forms, e.g.…”

Section: Basic Concepts and Overview Of The "Classic" Mtmmmentioning

confidence: 99%

Applied Psychometrics: The Application of CFA to Multitrait-Multimethod Matrices (CFA-MTMM)

Kyriazos¹

2018

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The application of CFA to Multitrait-Multimethod Matrices (MTMM) is an elaborated method for the evaluation of construct validity in terms of the discriminant and convergent validity as well as method effects. It is implemented to evaluate the acceptability of a questionnaire as a measure of constructs or latent variables, during the structural and external stages of an instrument validation process. CFA can be carried out in MTMM matrices, like in any other covariance matrix, to study the latent variables of traits and methods factors. CFA-MTMM models can distinguish systematic trait or method effects from unsystematic measurement error variance, thus offering the possibility of hypotheses testing on the measurement model, while controlling possible effects. A plethora of CFA-MTMM approaches have been proposed, but the Correlated Methods Models and the Correlated Uniqueness Models are two CFA-MTMM methods most widely used. This work discusses how these two approaches can be parametrized, and how inferences about construct validity and method effects can be drawn on the matrix level and on parameters level. Then, the two methods are briefly compared. Additional CFA MTMM parameterizations are also discussed and their advantages and disadvantages are summarized.