scholarly journals Why We Need to Abandon Fixed Cutoffs for Goodness-of-Fit Indices: A Comprehensive Simulation and Possible Solutions

2021 ◽  
Author(s):  
Katharina Groskurth ◽  
Matthias Bluemke ◽  
Clemens M. Lechner
Keyword(s):  
Goodness Of Fit ◽  
Model Misspecification ◽  
Model Fit ◽  
Fit Indices ◽  
New Approach ◽  
Response Options ◽  
Factor Loadings ◽  
Confirmatory Factor ◽  
Main Effect ◽  
Extraneous Data

To evaluate model fit in confirmatory factor analysis, researchers compare goodness-of-fit indices (GOFs) against fixed cutoff values derived from simulation studies. However, these cutoffs may not be as broadly applicable as researchers typically assume, especially when used in settings not covered in the simulation scenarios from which these cutoffs were derived. Thus, we aim to evaluate (1) the sensitivity of GOFs to model misspecification and (2) their susceptibility to extraneous data and analysis characteristics (i.e., estimator, number of indicators, number of response options, distribution of response options, loading magnitude, sample size, and factor correlation). Our study includes the most comprehensive simulation on that matter to date. This enables us to uncover several previously unknown or at least underappreciated issues with GOFs. All widely used GOFs are far more susceptible to extraneous influences in even more complex ways than generally appreciated, and their sensitivity to misspecifications in factor loadings and factor correlations varies significantly across different scenarios. For instance, one of those strong influences on all GOFs constituted the magnitude of factor loadings (either as a main effect or two-way interaction with other characteristics). The strong susceptibility of GOFs to data and analysis characteristics showed that the practice of judging the fit of models against fixed cutoffs is more problematic than so-far assumed. Hitherto unnoticed effects on GOFs imply that no general cutoff rules can be applied to evaluate model fit. We discuss alternatives for assessing model fit and develop a new approach to tailor cutoffs for GOFs to research settings.

A Bootstrap Procedure for Evaluating Goodness-of-Fit Indices of Structural Equation and Confirmatory Factor Models

1989 ◽  
Vol 26 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Paula Fitzgerald Bone ◽  
Subhash Sharma ◽  
Terence A. Shimp
Keyword(s):  
Structural Equation ◽  
Goodness Of Fit ◽  
Factor Models ◽  
Model Fit ◽  
Fit Indices ◽  
Bootstrap Sampling ◽  
Bootstrap Procedure ◽  
Number Of Factors ◽  
Confirmatory Factor ◽  
Competing Models

The authors propose a bootstrap procedure for evaluating the goodness-of-fit indices for structural equation and confirmatory factor models. Monté Carlo simulations are applied to obtain a bootstrap sampling distribution (BSD) for each fit statistic. Then the BSD is used to evaluate model fit. Because the BSD takes into consideration sample size and model characteristics (e.g., number of factors, number of indicators per factor), its application in the proposed procedure makes it possible to compare the fits of competing models. Two previous studies are reanalyzed in illustrating how to implement the proposed procedure.

scholarly journals Confirmatory analysis of the model to measure employee engagement

2016 ◽  
Vol 14 (2) ◽  
pp. 93-103
Author(s):  
Lailah Imandin ◽  
Christo Bisschoff ◽  
Christoff Botha
Keyword(s):  
Employee Engagement ◽  
Goodness Of Fit ◽  
Model Fit ◽  
Fit Indices ◽  
Managerial Decision ◽  
Satisfactory Model ◽  
Confirmatory Factor ◽  
Confirmatory Analysis ◽  
Engagement Factors ◽  
Fit Index

A model to measure the employee engagement was developed by researching historical employee engagement models. These models, consisting of employee engagement constructs and their measuring criteria, have been empirically validated and factorized into seven employee engagement factors. The seven employee engagement factors (of which factor one consists of two sub-factors) were subjected to confirmatory factor analysis to ensure the inclusion of the factors in the validated model to measure employee engagement. The model was also tested for goodness of fit, and the model shows good fit indices with the Comparative Fit Index (0.799), while the good model fit of the secondary fit indices RMSEA (0.078 within a narrow margin of 0.004) and Hoelter (113 at p <= 0.1; 111 at p <= 0.05) also show satisfactory model fit. Management can use the model as diagnostic tool to measure employee engagement and to apply it in managerial decision-making. On the other hand, academics could apply the model to extend their research in employee engagement

scholarly journals The Pandemic Stressor Scale – Factorial Validity and Reliability of a Measure of Stressors During a Pandemic

2021 ◽  
Author(s):  
Annett Lotzin ◽  
Ronja Ketelsen ◽  
Irina Zrnic ◽  
Brigitte Lueger-Schuster ◽  
Maria Böttche ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Goodness Of Fit ◽  
Factor Model ◽  
General Factor ◽  
Factorial Validity ◽  
Fit Indices ◽  
Validity And Reliability ◽  
Factor Loadings ◽  
Confirmatory Factor ◽  
Stressor Scale

Abstract Background: This study aimed to assess the factorial validity and reliability of the Pandemic Stressor Scale (PaSS), a new measure to assess the severity of distress for different stressors relevant during a pandemic or epidemic. Methods: The PaSS was administered in N = 2760 German participants. Exploratory factor analysis was used to extract factors. The factor structure obtained in the German sample was examined in N = 1021 Austrian participants using confirmatory factor analysis. χ², RMSEA, SRMR, CFI, TLI were assessed as global goodness of fit indices for two models (Model 1: nine-factor model; Model 2: nine-factor model combined with a second-order general factor). We additionally assessed factor loadings, communalities, factor reliability, discriminant validity as local fit indices. Internal consistency, item discrimination, and item difficulty were assessed as additional test quality criteria.Results: The results of the exploratory factor analysis suggested a nine-factor solution with factor loadings accounting for 50.4% of the total variance (Factor 1 ‘Problems with Childcare’, Factor 2 ‘Work-related Problems’, Factor 3 ‘Restricted Face-to-Face Contact’, Factor 4 ‘Burden of Infection ‘, Factor 5 ‘Crisis Management and Communication’, Factor 6 ‘Difficult Housing Condition’, Factor 7 ‘Fear of Infection’, Factor 8 ‘Restricted Access to Resources’, Factor 9 ‘Restricted Activity’). The confirmatory factor analysis showed a sufficient global fit for both tested models (Model 1: χ² (369, N =1021) = 1443.28, p < .001, RMSEA = .053, SRMR = .055, CFI = .919, TLI = .904; Model 2: χ² (396, N = 1021) = 1948.51, p < .001, RMSEA = .062, SRMR = .074, CFI = .883, TLI = .871). The results of the chi-square difference test indicated a significantly better model-fit of Model 1 compared to Model 2 (∆χ² (27, N = 1021) = 505.23, p < .001). Local goodness of fit indices were comparable for both tested models. We found good factor reliabilities for all factors and moderate to large factor loadings of the items as indicators. In Model 2, four first-order factors showed small factor loadings on the second-order general factor. Conclusion: The Pandemic Stressor Scale showed sufficient factorial validity for the nine measured domains of stressors during the current COVID-19 pandemic.

Confirmatory Factor Analysis of the Long and Short Forms of the Worry Domains Questionnaire

2009 ◽  
Vol 25 (4) ◽  
pp. 239-243
Author(s):  
Roberto Nuevo ◽  
Andrés Losada ◽  
María Márquez-González ◽  
Cecilia Peñacoba
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Goodness Of Fit ◽  
Factorial Validity ◽  
Fit Indices ◽  
Short Forms ◽  
Confirmatory Factor ◽  
Positive Correlations ◽  
Future Work

The Worry Domains Questionnaire was proposed as a measure of both pathological and nonpathological worry, and assesses the frequency of worrying about five different domains: relationships, lack of confidence, aimless future, work, and financial. The present study analyzed the factor structure of the long and short forms of the WDQ (WDQ and WDQ-SF, respectively) through confirmatory factor analysis in a sample of 262 students (M age = 21.8; SD = 2.6; 86.3% females). While the goodness-of-fit indices did not provide support for the WDQ, good fit indices were found for the WDQ-SF. Furthermore, no source of misspecification was identified, thus, supporting the factorial validity of the WDQ-SF scale. Significant positive correlations between the WDQ-SF and its subscales with worry (PSWQ), anxiety (STAI-T), and depression (BDI) were found. The internal consistency was good for the total scale and for the subscales. This work provides support for the use of the WDQ-SF, and potential uses for research and clinical purposes are discussed.

Is That Measure Really One-Dimensional?

Methodology ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 188-196 ◽  
Author(s):  
Esther T. Beierl ◽  
Markus Bühner ◽  
Moritz Heene
Keyword(s):  
Model Fit ◽  
Nuisance Parameters ◽  
Factorial Validity ◽  
Fit Indices ◽  
Analysis Model ◽  
Factor Analysis Model ◽  
One Dimensional ◽  
Confirmatory Factor Analysis Model ◽  
Cutoff Values ◽  
Confirmatory Factor

Abstract. Factorial validity is often assessed using confirmatory factor analysis. Model fit is commonly evaluated using the cutoff values for the fit indices proposed by Hu and Bentler (1999) . There is a body of research showing that those cutoff values cannot be generalized. Model fit does not only depend on the severity of misspecification, but also on nuisance parameters, which are independent of the misspecification. Using a simulation study, we demonstrate their influence on measures of model fit. We specified a severe misspecification, omitting a second factor, which signifies factorial invalidity. Measures of model fit showed only small misfit because nuisance parameters, magnitude of factor loadings and a balanced/imbalanced number of indicators per factor, also influenced the degree of misfit. Drawing from our results, we discuss challenges in the assessment of factorial validity.

A Comparison of Reliability Estimation Based on Confirmatory Factor Analysis and Exploratory Structural Equation Models

2021 ◽  
pp. 001316442110089
Author(s):  
Yuanshu Fu ◽  
Zhonglin Wen ◽  
Yang Wang
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Reliability Estimation ◽  
Model Fit ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Reliability Estimates ◽  
Confirmatory Factor ◽  
Composite Reliability

Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is often found to be substantially better than that of ICM-CFA. The present study first illustrated the method used to estimate composite reliability under ESEM and then compared the difference between ESEM and ICM-CFA in terms of composite reliability estimation under various indicators per factor, target factor loadings, cross-loadings, and sample sizes. The results showed no apparent difference in using ESEM or ICM-CFA for estimating composite reliability, and the rotation type did not affect the composite reliability estimates generated by ESEM. An empirical example was given as further proof of the results of the simulation studies. Based on the present study, we suggest that if the model fit of ESEM (regardless of the utilized rotation criteria) is acceptable but that of ICM-CFA is not, the composite reliability estimates based on the above two models should be similar. If the target factor loadings are relatively small, researchers should increase the number of indicators per factor or increase the sample size.

Psychometric Assessment of the Persian Translated Version of the Romantic Perfectionism Scale Among Couples

2021 ◽  
pp. 003329412110360
Author(s):  
Abbas Abdollahi ◽  
Kelly A. Allen
Keyword(s):  
Content Validity ◽  
Goodness Of Fit ◽  
Factor Loading ◽  
Face Validity ◽  
Fit Indices ◽  
Depression Anxiety Stress Scale ◽  
Confirmatory Factor ◽  
Married Men ◽  
Iranian Version ◽  
Acceptable Internal Consistency

Romantic perfectionismi can be disruptive to relationships, yet no validated measure for assessing romantic perfectionism in Iranian couples has been developed. Therefore, the purpose of this study was to translate and validate the Romantic Perfectionism Scale (RPS) among Iranian couples. Participants in the study were 200 married men and 320 married women from Tehran, Iran, who completed the translated RPS, the Almost Perfect Scale-Revised, and the Depression Anxiety Stress Scale-21 online. Item impact scores were used to calculate face validity. Impact score values for all items were greater than 1.5, signaling appropriate face validity.. The Content Validity Index (CVI) and the Content Validity Ratio (CVR) were used to measure content validity. Values of the CVI were above the cut-off score of 0.7, implying satisfactory content validity of the items. The CVR values were greater than the Lawshe table (0.78) cut-off score, demonstrating that all items were essential. Confirmatory Factor Analysis (CFA) using AMOS software was used to evaluate the construct validity. The results of the goodness of fit indices confirmed the RPS with two subscales (i.e., self-oriented romantic perfectionism and other-oriented romantic perfectionism) as per the original scale. All items remained in the scale as all factor loading values were greater than 0.45. The findings showed that the two subscales, and the scale as a whole, had acceptable internal consistency, as the construct reliability values for self-oriented romantic perfectionism (0.81), other-oriented romantic perfectionism (0.72), and the whole scale (0.74) were greater than 0.7. The results support the psychometric properties of the Iranian version of the RPS, which could be used by future researchers and clinicians to assess romantic perfectionism in Iranian couples.

Development of a Uniquely South African Leadership Questionnaire

2002 ◽  
Vol 32 (2) ◽  
pp. 9-25 ◽  
Author(s):  
Hermann H. Spangenberg ◽  
Callie C. Theron
Keyword(s):  
South African ◽  
Goodness Of Fit ◽  
Principal Component ◽  
Charismatic Leadership ◽  
Fit Indices ◽  
Confirmatory Factor Analyses ◽  
Leadership Model ◽  
Emerging Leadership ◽  
Confirmatory Factor ◽  
Unit Performance

This paper describes the development of a leadership questionnaire the aim of which is to assess the behaviours required to lead change and transformation, while at the same time managing organisational unit performance effectively. A Delphi technique was used to facilitate the identification and testing of emerging leadership dimensions and items, starting with a three-stage model of charismatic leadership, The resultant leadership model comprises four stages, measured as 21 dimensions. The research questionnaire consists of 235 items. The questionnaire was field tested by means of 360° assessment conducted amongst 189 unit managers from a diverse group of organisations. Seven hundred and fifty completed questionnaires were obtained. Unrestricted principal component analyses were performed on each of the sub-scales (dimensions) to examine the unidimensionality assumption. This procedure resulted in the formation of three additional sub-scales. Item analyses on each of the sub-scales produced highly satisfactory Cronbach Alpha values. Further confirmatory factor analyses using LISREL were conducted on each of the 24 sub-scales. A series of goodness-of-fit indices generally showed satisfactory results. Overall, results indicate that a 96-item questionnaire format consisting of 24 dimensions with four items each (selected on the basis of factor loadings) could be used with confidence. Recommendations are made for further research.

scholarly journals The Stress and Anxiety to Viral Epidemics-6 items (SAVE-6): A new instrument for assessing anxiety response to viral epidemics in the general population during the COVID-19 pandemic

2021 ◽  
Author(s):  
Seockhoon Chung ◽  
Myung Hee Ahn ◽  
Sangha Lee ◽  
Solbi Kang ◽  
Sooyeon Suh ◽  
...  
Keyword(s):  
General Population ◽  
Goodness Of Fit ◽  
Online Survey ◽  
Fit Indices ◽  
Depression And Anxiety ◽  
Mild Degree ◽  
New Instrument ◽  
Confirmatory Factor ◽  
Good Internal Consistency ◽  
Anxiety Response

During the COVID-19 pandemic, people have reported experiencing anxiety in response to the viral epidemic. This study aimed to explore the validity and usefulness of the Stress and Anxiety to the Viral Epidemic-6 items (SAVE-6) scale for measuring the anxiety response to the viral epidemic of the general population. A total of 1,009 respondents participated in an online survey, and 501 (49.7%) participants were rated as having at least a mild degree of anxiety response to the viral epidemic (SAVE-6 score ≥ 15), whereas 90 (8.9%) and 91 (9.0%) were rated as having depression and anxiety, respectively. The SAVE-6 scales showed good internal consistency (Cronbach’s α = .82). Confirmatory factor analysis supported a one-factor structure for the measure. Goodness-of-fit indices (χ2/df ratio = 19.1, CFI = .92; TLI = .86; SRMR = 0.05; RMSEA = .13) were adequate. The SAVE-6 was found to be a reliable, valid, and useful brief measure that can be applied to the general population. The SAVE-6 may be useful for easily assessing the anxiety symptoms during the pandemic in the general population.

scholarly journals A study on development of Perceived Quality-Image Scale in Sports Organizations

2018 ◽  
Vol 15 (4) ◽  
pp. 2407
Author(s):  
Yeşim Bayrakdaroglu ◽  
Dursun Katkat
Keyword(s):  
Reliability Analysis ◽  
Model Fit ◽  
Measurement Tool ◽  
Fit Indices ◽  
Confirmatory Factor Analyses ◽  
Sports Organizations ◽  
Confirmatory Factor ◽  
Quality Image ◽  
Model Fit Indices ◽  
Marketing Activities

The purpose of this study is to research how marketing activities of international sports organizations are performed and to develop a scale determining the effects of image management on public. The audiences of interuniversity World Winter Olympic sheld in Erzurum in 2011 participated in the research. Explanatory and Confirmatory Factor Analysis, reliability analysis were performed over the data obtained. All model fit indices of 25-item and four-factor structure of quality-image scale perceived in sports organizations applied were found to be at good level. In line with the findings obtained from the explanatory and confirmatory factor analyses and reliability analysis, it can be uttered that the scale is a valid and reliable measurement tool that can be used in field researches.

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