Validation of the Flourishing Scale (FS), Greek Version and Evaluation of Two Well-Being Models

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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%

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

Kyriazos¹

2018

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“…For applied examples of the implementation of the method see Kyriazos et al (2018aKyriazos et al ( , 2018bKyriazos et al ( , 2018cKyriazos et al ( , 2018d. Psychology er-order structure to use as a benchmark; 2) models with higher-order structure.…”

Section: Higher-order Confirmatory Factor Analysismentioning

confidence: 99%

Early Childhood Acceptance Rejection Questionnaire: Psychometric Properties of the Greek Version

Giotsa¹,

Kyriazos²

2019

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Present study examined the ECPARQ with four different higher order techniques (Bifactor EFA, Bifactor CFA, Bifactor ESEM, Second-order CFA) plus a simple CFA (ICM CFA), evaluating a total of 19 models. All models were tested twice, one for the ECPARQ Mother version and one for the Father version. For each version, alternative models were tested with 2, 3 and 4-factor structures. All models were tested having item 13 both in the intended factor and alternatively in the Warmth factor. This comparison was made to empirically answer in what factor the item 13 belongs. All higher order models had an adequate fit, suggesting thus the theoretical construct of the Warmth dimension of Parenting is supported for the Greek cultural context, although further investigation is necessary. ICM-CFA had equally adequate fit, thus preferable based on parsimony. All models tested having item 13 in the Warmth factor had superior fit in comparison to their counterparts with item 13 in the Indifference/Neglect factor. Internal consistency reliability was adequate.

“…(The above example is an extract adapted from Kyriazos et al, 2018dKyriazos et al, : p. 1796 validating the Flourishing Scale by Diener at al., 2010).…”

Section: Data Screening and Data Managementmentioning

confidence: 99%

“…(2) Cross-Loadings (if m > 1). For applied examples you can refer to Stalikas et al, (2018) and Kyriazos et al (2018aKyriazos et al ( , 2018bKyriazos et al ( , 2018d. On the other hand, when reporting an EFA without fit indices, details on how the number of factors was determined and the relative importance of the factors as a function of variance explained or eigenvalues is also recommended (Howitt & Cramer, 2017).…”

Section: Exploratory Factor Analysis (Efa)mentioning

confidence: 99%

Applied Psychometrics: Writing-Up a Factor Analysis Construct Validation Study with Examples

Kyriazos¹

2018

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Factor analysis is carried out to psychometrically evaluate measurement instruments with multiple items like questionnaires or ability tests. EFA and CFA are widely used in measurement applications for construct validation and scale refinement. One of the more critical aspects of any CFA or EFA is communicating results. This work described reporting essentials of EFA with goodness of fit indices and CFA research when they are used to validate a measurement instrument with continuous variables in a different population from the one originally created. An overview of the minimum information to be reported is included along with short extracts from real published reports. For each reported section basic information to be included is described along with an example-extract adapted from published factor analysis construct validation studies. Additional issues covered include: Cross-validation, Measurement Invariance across Age and Gender, Reliability (α and ω), AVE-Based Validity, Convergent and Discriminant Validity with Correlation Analysis and Normative Data. Properly reported EFA and CFA could contribute to the improvement of the quality of the measurement instruments. A summary of good practices in CFA and SEM reporting based on literature is also included.