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

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

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 Mengakomodasi Efek Metode dalam Pengujian Validitas Konstruk Melalui Analisis Faktor Konfirmatori

2017 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Wahyu Widhiarso
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Equation Modeling ◽  
Fit Indices ◽  
Method Effect ◽  
Confirmatory Factor ◽  
Method Effects ◽  
Item Writing

Literatures in the field of psychometrics recommend researchers to employvarious of methods on measuring individual attributes. Ideally,each methods are complementary and measuresthe construct designed to be measured. However, some problems arise when among the methods is unique and unrelated to the construct being measured. The uniqueness of method can lead what is called the method effect. In testing construct validity using confirmatory factor analysis, the emergence of this effect tend to reducing the goodness of fit indices of the model. There are many ways to solve these problem, one of themis controling the method effects and accommodate it to the model. This paper introduces how to accommodate method effecton the confirmatory factor analysis using structural equation modeling. In the application section, author identify the emergence of method effects due to the differences item writing direction (favorable-unfavorable). The analysis showed that method effectemerge from different writing direction.

scholarly journals The Effects of Political Cynicism and National Siege Mentality on the Internalization of an Anti-European Sentiment

2016 ◽  
Vol 6 (1) ◽  
pp. 22
Author(s):  
Zlatko Šram
Keyword(s):  
Structural Equation ◽  
Goodness Of Fit ◽  
Structural Model ◽  
Survey Methods ◽  
Adult Population ◽  
Equation Model ◽  
Fit Indices ◽  
Political Cynicism ◽  
Confirmatory Factor ◽  
Unidimensional Construct

<p>This paper aims to provide an insight into the political-psychological understanding of an attitudinal construct labeled anti-European sentiment. A structural equation model for prediction was developed and evaluated by using full information mximum likelihood estimates obtained from LISREL 8.52 computer program. Assumption was that both political cynicism and national siege mentality would have an effect on anti-European sentiment. The data reported here were obtained by standard survey methods on the sample of adult population in Croatia (N=533). Confirmatory factor analysis (CFA) was performed to explore factorial and construct validity of the measures used in this research. CFA yielded unidimensional construct measurements with acceptable fit indices. Structural model indicated that exogenous variables (political cynicism, national siege mentality) have significant effects on the anti-European sentiment used as an endogenous (dependent) variable. Goodness-of-fit indices suggested acceptable fit of the model (RMSEA=0.07, CFI=0.97, NNFI=0.97, SRMR=0.05). Given the amount of variance of anti-European sentiment, it was showen that political cynicism and national siege mentality have strong predictive validity for anti-European sentiment (43 percent of the variance was explained by the structural model). In order to explain the interactions among the variables investigated, the author proposed the distrust-threat model of political hostility.</p>

A Psychometric Study of the Quality Perception Questionnaire

2012 ◽  
Vol 71 (2) ◽  
pp. 101-106 ◽  
Author(s):  
Raffaele Cioffi† ◽  
Anna Coluccia ◽  
Fabio Ferretti ◽  
Francesca Lorini ◽  
Aristide Saggino ◽  
...  
Keyword(s):  
Structural Equation ◽  
Factor Model ◽  
Equation Modeling ◽  
Fit Indices ◽  
Quality Perception ◽  
Italian Survey ◽  
Confirmatory Factor ◽  
Instrument Measuring ◽  
Hospital Structures

The present paper reexamines the psychometric properties of the Quality Perception Questionnaire (QPQ), an Italian survey instrument measuring patients’ perceptions of the quality of a recent hospital admission experience, in a sample of 4400 patients (Mage = 56.42 years; SD = 19.71 years, 48.8% females). The 14-item survey measures four factors: satisfaction with medical doctors, nursing staff, auxiliary staff, and hospital structures. First, we tested two models using a confirmatory factor analysis (structural equation modeling): a four orthogonal factor and a four oblique factor model. The SEM fit indices and the χ² difference suggested the acceptance of the second model. We then did a simulation using a bootstrap with 1000 replications. Results confirmed the four oblique factor solution. Third, we tested whether there were significant differences with respect to age or sex. The multivariate general linear model showed no significant differences in the factors with respect to sex or age.

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.

A Cautionary Note on Incremental Fit Indices Reported by LISREL

Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Null Model ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Fit Indices ◽  
Cautionary Note ◽  
Confirmatory Factor

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.

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.

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