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      Evidências Adicionais de Validade da Escala de Satisfação no Trabalho Translated title: Additional Validity Evidence for the Job Satisfaction Scale Translated title: Evidencias Adicionales de Validez de la Escala de Satisfacción Laboral

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          Abstract

          Este estudo objetivou identificar as propriedades da escala de satisfação no trabalho mais utilizada em amostras brasileiras em termos de sua estrutura, invariância da medida e validade convergente. Participaram da pesquisa 733 trabalhadores (46% mulheres) do setor industrial e terciário de dois estados brasileiros. Além do modelo original de cinco fatores correlacionados, foram comparados três modelos estruturais alternativos (cinco fatores não correlacionados, hierárquico e bifatorial). Os resultados apontam que a estrutura bifatorial com cinco variáveis latentes de primeiro nível mais uma variável geral também de primeiro nível é um modelo estrutural robusto para avaliar a satisfação de trabalhadores brasileiros e foi invariante para todos os grupos testados, tendo a possibilidade de aplicação em amostras com diversidade em termos de tempo de trabalho, grau de escolaridade e sexo. A medida também apresentou correlação positiva de moderada a elevada com outras duas variáveis do comportamento organizacional, confirmando a validade convergente.

          Translated abstract

          This study aimed to identify the properties of the job satisfaction scale most used in Brazilian samples in terms of its structure, convergent validity and measure invariance. The study involved 733 workers (46% women) from the industrial and tertiary sectors of two Brazilian states. In addition to the original model of five correlated factors, three alternative structural models were compared (five uncorrelated factors, hierarchical and bifactorial). The results show that the bifactorial structure, with five latent variables of the first level plus a general variable also of the first level, is a robust structural model to evaluate the satisfaction of Brazilian workers and was invariant for all groups tested, with the possibility of application in samples with different work times, levels of education and gender. The measure also showed a positive moderate to high correlation with the other two variables of organizational behavior confirming the convergent validity.

          Translated abstract

          Este estudio tuvo como objetivo identificar las propiedades de la escala de satisfacción laboral más utilizada en muestras brasileñas en términos de su estructura, validez convergente e invarianza de medida. Participaron de la encuesta 733 trabajadores (46% mujeres) de los sectores industrial y terciario de dos provincias brasileñas. Además del modelo original de cinco factores correlacionados, se compararon tres modelos estructurales alternativos (cinco factores no correlacionados, jerárquico y el de dos factores). Los resultados demuestran que, la estructura de dos factores con cinco variables latentes del primer nivel más una variable general, también del primer nivel, es un modelo estructural robusto para evaluar la satisfacción laboral de los trabajadores brasileños y fue invariante para todos los grupos evaluados, con la posibilidad de aplicación en muestras con diferentes tiempos de trabajo, escolaridad y género. La medida también presentó correlación positiva, de moderada a elevada, con otras dos variables del comportamiento organizacional, lo que confirma la validez convergente.

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          lavaan: AnRPackage for Structural Equation Modeling

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            Structural Equation Modeling with AMOS : Basic Concepts, Applications, and Programming

            <p>This bestselling text provides a practical guide to the basic concepts of structural equation modeling (SEM) and the AMOS program (Versions 17 & 18). The author reviews SEM applications based on actual data taken from her research. Noted for its non-mathematical language, this book is written for the novice SEM user. With each chapter, the author "walks" the reader through all steps involved in testing the SEM model including: </p><ul><p><li>an explanation of the issues addressed </li><p></p><p><li>an illustration of the hypothesized and posthoc models tested </li><p></p><p><li>AMOS input and output with accompanying interpretation and explanation</li><p></p><p><li>The function of the AMOS toolbar icons and their related pull-down menus</li><p></p><p><li>The data and published reference upon which the model was based.</li><p></p></ul><p></p><p>With over 50% new material, highlights of the new edition include:</p><ul><p><li>All new screen shots featuring Version 17 of the AMOS program </li><p></p><p><li>All data files now available at www.psypress.com/sem-with-amos </li><p></p><p><li>Application of a multitrait-mulitimethod model, latent growth curve model, and second-order model based on categorical data</li><p></p><p><li>All applications based on the most commonly used graphical interface</li><p></p><p><li>The automated multi-group approach to testing for equivalence</li><p></p></ul><p></p><p>The book opens with an introduction to the fundamental concepts of SEM and the basics of the AMOS program. The next 3 sections present applications that focus on single-group, multiple-group, and multitrait-mutimethod and latent growth curve models. The book concludes with a discussion about non-normal and missing (incomplete) data and two applications capable of addressing these issues. </p><p></p><p>Intended for researchers, practitioners, and students who use SEM and AMOS in their work, this book is an ideal resource for graduate level courses on SEM taught in departments of psychology, education, business, and other social and health sciences and/or as a supplement in courses on applied statistics, multivariate statistics, statistics II, intermediate or advanced statistics, and/or research design. Appropriate for those with limited or no previous exposure to SEM, a prerequisite of basic statistics through regression analysis is recommended. </p>
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              Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic.

              A scaled difference test statistic [Formula: see text] that can be computed from standard software of structural equation models (SEM) by hand calculations was proposed in Satorra and Bentler (2001). The statistic [Formula: see text] is asymptotically equivalent to the scaled difference test statistic T̄(d) introduced in Satorra (2000), which requires more involved computations beyond standard output of SEM software. The test statistic [Formula: see text] has been widely used in practice, but in some applications it is negative due to negativity of its associated scaling correction. Using the implicit function theorem, this note develops an improved scaling correction leading to a new scaled difference statistic T̄(d) that avoids negative chi-square values.
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                Author and article information

                Journal
                avp
                Avaliação Psicológica
                Aval. psicol.
                Universidade São Francisco; Pós-Graduação Stricto Sensu em Psicologia (Campinas, SP, Brazil )
                1677-0471
                2175-3431
                March 2021
                : 20
                : 1
                : 61-70
                Affiliations
                [02] Virgínia orgnameUniversity of Virginia Estados Unidos
                [01] Niterói RJ orgnameUniversidade Salgado de Oliveira Brasil
                Article
                S1677-04712021000100008 S1677-0471(21)02000100008
                10.15689/ap.2021.2001.17426.07
                4f09be28-2af3-48ad-a008-c1d194dad60e

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : December 2018
                : September 2020
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 55, Pages: 10
                Product

                SciELO Periódicos Eletrônicos em Psicologia

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                validez estadística,modelo de dos factores,satisfacción laboral,modelo bifatorial,validade estatística,satisfação no trabalho,bifactor model,statistical validity,job satisfaction

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