Construct Validity of the Risk, Pain, and Injury Questionnaire

2005 ◽  
Vol 22 (4) ◽  
pp. 433-446 ◽  
Author(s):  
Stephan R. Walk ◽  
Lenny D. Wiersma
Keyword(s):  
Structural Equation Modeling ◽  
Construct Validity ◽  
West Coast ◽  
Content Validity ◽  
Structural Equation ◽  
Factor Model ◽  
Model Fit ◽  
Face Validity ◽  
Equation Modeling ◽  
Limited Support

Nixon’s (1994a; 1994b; 1996a; 1996b) research using a Risk, Pain, and Injury Questionnaire (RPIQ) is perhaps the most systematic in the risk, pain, and injury literature. The RPIQ is intended to measure the acceptance of dominant discourses on risk, pain, and injury among athletes and others. This article presents a face validity critique of the RPIQ and results of a subsequent content validity analysis based on a study of 171 athletes from a West Coast university. Structural equation modeling used to test Nixon’s original 3-factor model (M1) revealed poor model fit. Two alternate models (M2 and M3) tested reformulated subscale constructs and items. Whereas M2 demonstrated poor construct validity, limited support was found for items in M3. Further replications of this research are recommended.

A New Dimension of Organizational Justice: Procedural Voice

2009 ◽  
Vol 105 (2) ◽  
pp. 411-426 ◽  
Author(s):  
Denise Jepsen ◽  
John Rodwell
Keyword(s):  
Structural Equation Modeling ◽  
Organizational Justice ◽  
Latent Variable ◽  
Structural Equation ◽  
Factor Model ◽  
Model Fit ◽  
Equation Modeling ◽  
Wide Range

Dimensionality of the Colquitt justice measures was investigated across a wide range of service occupations. Structural equation modeling of data from 410 survey respondents found support for the 4-factor model of justice (procedural, distributive, interpersonal, and informational), although significant improvement of model fit was obtained by including a new latent variable, “procedural voice,” which taps employees' desire to express their views and feelings and influence results. The model was confirmed in a second sample ( N = 505) in the same organization six months later.

On the Structure of Affect

2021 ◽  
Vol 229 (1) ◽  
pp. 24-37 ◽  
Author(s):  
Nadine Wedderhoff ◽  
Timo Gnambs ◽  
Oliver Wedderhoff ◽  
Tanja Burgard ◽  
Michael Bošnjak
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Factor Model ◽  
Self Report ◽  
Equation Modeling ◽  
Positive And Negative Affect ◽  
Correlation Matrices ◽  
The World ◽  
Best Fit ◽  
Cross National

Abstract. The Positive and Negative Affect Schedule (PANAS; Watson et al., 1988 ) is a popular self-report questionnaire that is administered all over the world. Though originally developed to measure two independent factors, different models have been proposed in the literature. Comparisons among alternative models as well as analyses concerning their robustness in cross-national research have left an inconclusive picture. Therefore, the present study evaluates the dimensionality of the PANAS and differences between English and translated versions of the PANAS using a meta-analytic structural equation modeling approach. Correlation matrices from 57 independent samples ( N = 54,043) were pooled across subsamples. For both English and non-English samples, a correlated two-factor model including correlated uniquenesses provided the best fit. However, measurement invariance analyses indicated differences in factor loadings between subsamples. Thus, cross-national application of the PANAS might only be justified if measurement equivalence was explicitly tested for the countries at hand.

scholarly journals Analisis Faktor-Faktor Yang Mempengaruhi Kesiapan Kerja Pada Siswa SMK Negeri 1 Sinjai

2018 ◽  
Vol 6 (2) ◽  
pp. 105-115
Author(s):  
Muhammad Ihsan
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Model Fit ◽  
Equation Modeling

Tujuan penelitian ini adalah: 1) Untuk mengetahui bagaimana hasil dari faktor-faktor yang mempengaruhi kesiapan kerja siswa SMK Negeri 1 Sinjai, 2) Untuk mengetahui hasil presentasi  dari analisis faktor-faktor yang mempengaruhi kesiapan kerja pada siswa SMK Negeri 1 Sinjai, 3) Untuk mengetahui faktor-faktor apa sajakah yang mempengaruhi penerimaan kesiapan kerja siswa SMK Negeri 1 Sinjai. Penelitian ini menggunakan metode deskriptif eksploratif. Populasi dalam penelitian ini adalah seluruh siswa kelas 3 SMK Negeri 1 Sinjai sejumlah 341 siswa dan sampel sebanyak 200 siswa. Analisis data dilakukan dengan pendekatan Structural Equation Modeling (SEM), yaitu SEM berbasis covariance. Berdasarkan hasil dari analisis data yang dilakukan, diperoleh kesimpulan bahwa: 1) Pengujian variabel-variabel pada model I-E-O, yang berpengaruh pada kesiapan kerja siswa SMK Negeri 1 Sinjai, dengan menggunakan pendekatan SEM, disimpulkan model fit dengan data yang ada. 2) Faktor kemampuan memiliki nilai koefisien sebesar 5,537437. Faktor kemampuan merupakan faktor terkuat yang mempengaruhi kesiapan kerja pada siswa SMK Negeri 1 Sinjai. Faktor ini terdiri atas prestasi belajar, tingkat intelegensi, pengalaman praktek, kedisiplinan, ekspektansi masuk dunia kerja, bakat. 3) Faktor-faktor yang mempengaruhi kesiapan kerja siswa SMK Negeri 1 Sinjai, dipengaruhi oleh faktor kemampuan, faktor akademis, faktor prilaku dan potensi diri, faktor bawaan/warisan.

Evaluating the Construct Validity of Ryff’s Scales of Psychological Well-Being Using Exploratory Structural Equation Modeling

2016 ◽  
Vol 35 (6) ◽  
pp. 633-638 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Tze-Li Hsu ◽  
KoFan Lee ◽  
Lori Wolff
Keyword(s):  
Structural Equation Modeling ◽  
Construct Validity ◽  
Structural Equation ◽  
Discriminant Validity ◽  
Well Being ◽  
The United States ◽  
Equation Modeling ◽  
Exploratory Structural Equation Modeling ◽  
Psychological Well Being ◽  
Measurement Models

The purpose of this study was to evaluate the construct validity of Ryff’s Scales of Psychological Well-Being (SPWB) using exploratory structural equation modeling (ESEM). The data were drawn from the national survey of Midlife in the United States conducted during 1994 and 1995. Measurement models assuming different number of factors (1-6 factors) and considering the effect of negatively wording items were specified and compared to determine optimal number of underlying factors. The discriminant validity was assessed following Farrell’s suggestions. The results showed the discriminant validity was questionable due to five indicators with considerable cross-loadings.

Structural Equation Modeling with Factors and Composites

2017 ◽  
Vol 13 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Factor Model ◽  
Common Factor ◽  
Equation Modeling ◽  
A Algorithm ◽  
Multivariate Statistical ◽  
Full Information Maximum Likelihood ◽  
Common Factor Model ◽  
Path Coefficients

Recent methodological developments building on partial least squares (PLS) techniques and related ideas have significantly contributed to bridging the gap between factor-based and composite-based structural equation modeling (SEM) methods. PLS-SEM is extensively used in the field of e-collaboration, as well as in many other fields where multivariate statistical analyses are employed. The author compares results obtained with four methods: covariance-based SEM with full information maximum likelihood (FIML), factor-based SEM with common factor model assumptions (FSEM1), factor-based SEM building on the PLS Regression algorithm (FSEM2), and PLS-SEM employing the Mode A algorithm (PLSA). The comparison suggests that FSEM1 yields path coefficients and loadings that are very similar to FIML's; and that FSEM2 yields path coefficients that are very similar to FIML's and loadings that are very similar to PLSA's.

scholarly journals Cutoff criteria for overall model fit indexes in generalized structured component analysis

2020 ◽  
Vol 8 (4) ◽  
pp. 189-202
Author(s):  
Gyeongcheol Cho ◽  
Heungsun Hwang ◽  
Marko Sarstedt ◽  
Christian M. Ringle
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Component Analysis ◽  
Model Fit ◽  
Equation Modeling ◽  
Generalized Structured Component Analysis ◽  
Root Mean Square Residual ◽  
Fit Indexes ◽  
Cutoff Criteria

AbstractGeneralized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in factor-based structural equation modeling, nothing is known about their performance in GSCA. Addressing this limitation, we present a simulation study’s results, which confirm that both GFI and SRMR indexes distinguish effectively between correct and misspecified models. Based on our findings, we propose rules-of-thumb cutoff criteria for each index in different sample sizes, which researchers could use to assess model fit in practice.

Adaptation and Validation of the Athletic Identity Questionnaire-Adolescent for Use With Children

2008 ◽  
Vol 5 (4) ◽  
pp. 539-558 ◽  
Author(s):  
Cheryl B. Anderson ◽  
Karen J. Coleman
Keyword(s):  
Physical Activity ◽  
Construct Validity ◽  
Structural Equation ◽  
Factor Model ◽  
Athletic Identity ◽  
Ethnically Diverse ◽  
Self Report ◽  
Equation Modeling ◽  
Confirmatory Factor ◽  
Child Factors

Background:This article describes the adaptation of the Athletic Identity Questionnaire (AIQ) for Adolescents for use with children and evaluates its construct validity. Based on a theoretical model supported in adults and adolescents, the AIQ-Child measures the general attribute of athletic, which encompasses exercise, sport, and physical activity and assesses 4 dimensions: appearance, competence, importance of activity, and encouragement from 3 sources (parents, friends, teachers/other adults).Methods:The hypothesized 4-factor model was tested using structural equation modeling in 2 samples of 9- and 10-year-old children that were ethnically diverse (N = 432) and Hispanic (N = 504).Results:Confirmatory factor analysis using LISREL 8.71 supported the 4-factor structure in a 40- or 38-item version in sample 1 (RMSEA = .039, .041) and sample 2 (RMSEA = .038, .038). As in the adult and adolescent models, there was also support for a higher-order model. The AIQ-Child factors were positively related to physical activity (r = .51 to .68) and fitness (r = .15 to .41) and negatively related to TV/computer use (r = –.28 to –.03) and adiposity (r = –.32 to .04).Conclusions:Findings support the factorial and construct validity of the AIQ-Child and its use as a self-report instrument in younger children.

scholarly journals Validating the University Student Engagement Model through Structural Equation Modeling

2018 ◽  
Vol 5 (4) ◽  
pp. 318 ◽  
Author(s):  
Hafsa Mzee Mwita
Keyword(s):  
Structural Equation Modeling ◽  
Student Engagement ◽  
Structural Equation ◽  
Factor Model ◽  
University Student ◽  
Equation Modeling ◽  
Psychological Constructs ◽  
Confirmatory Factor ◽  
The University ◽  
Behavior And Cognition

<p><em>The main purpose </em><em>of this study is to investigate whether emotional, cognitive and behavioral engagements, represents three conceptually and empirically distinct psychological constructs when studied within the same domain. This paper reports part of the findings from a major study entitled “Predictors of Self-Handicapping Behavior among Muslim Students”. Testing for factorial equivalence of scores from a measuring instrument was carried-out through structural equation modeling by using AMOS version 16.</em><em> </em><em>Results of Confirmatory Factor Analysis of responses from 790 undergraduates prove that the SEM three factor model of University Student Engagement (USE) is empirically fit and reliable, which also supports the argument that emotion, behavior and cognition are the student engagement manifestations of an interrelated constellation of academic student engagement. </em></p>

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