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Applied multivariate research design and interpretation

Lawrence S Meyers Glenn Gamst; A. J Guarino

Thousand Oaks Sage Publications 2006

Localização: FSP - Faculdade de Saúde Pública    (519.535 38 )(Acessar)

  • Título:
    Applied multivariate research design and interpretation
  • Autor: Lawrence S Meyers
  • Glenn Gamst; A. J Guarino
  • Assuntos: Multivariate analysis; Social sciences -- Statistical methods; Analyse multivariée; Sciences sociales -- Méthodes statistiques; ESTATÍSTICA; ANÁLISE MULTIVARIADA; ANÁLISE ESTATÍSTICA DE DADOS; MODELAGEM DE EQUAÇÕES ESTRUTURAIS
  • Notas: Includes bibliographical references (p. 677-694) and indexes
  • Descrição: Preface -- Part 1. Foundations. 1. An introduction to multivariate design -- 2. Some fundamental research design concepts -- 3A. Data screening -- 3B. Data screening using SPSS -- Part 2. The independent variable variate. 4A. Bivariate correlation and simple linear regression -- 4B. Bivariate correlation and simple linear regression using SPSS -- 5A. Multiple regression -- 5B. Multiple regression using SPSS -- 6A. Logistic regression -- 6B. Logistic regression using SPSS -- 7A. Discriminant function analysis -- 7B. Two-group Discriminant function analysis using SPSS -- Part 3. The dependent variable variate. 8A. Univariate comparisons of means -- 8B. Univariate comparisons of means using SPSS -- 9A. MANOVA : comparing two groups -- 9B. Two-group MANOVA using SPSS -- 10A. MANOVA : comparing three or more groups -- 10B. MANOVA : comparing three or more groups using SPSS -- 11A. MANOVA : two-way factorial -- 11B. MANOVA : two-way factorial using SPSS -- Part 4. The emergent variate. 12A. Principal components and factor analysis -- 12B. Principal components and factor analysis using SPSS -- 13A. Confirmatory factor analysis -- 13B. Confirmatory factor analysis using AMOS -- Part V. Model fitting. 14A. Causal modeling : path analysis and structural equation modeling -- 14B. Path analysis using SPSS and AMOS -- 15A. Applying a model to different groups -- 15B. Assessing model invariance between groups using AMOS -- Appendix -- References -- Name index -- Subject index -- About the authors
    Multivariate designs were once the province of the very few exalted researchers who understood the underlying advanced mathematics. Today, through the sophistication of statistical software packages such as SPSS, virtually all graduate students across the social and behavioral sciences are exposed to the complex multivariate statistical techniques without having to learn the mathematical computations needed to acquire the data output. These students - in psychology, education, political science, etc. - will never be statisticians and appropriately so, their preparation and coursework reflects less of an emphasis on the mathematical complexities of multivariate statistics and more on the analysis and the interpretation of the methods themselves and the actual data output. This book provides full coverage of the wide range of multivariate topics in a conceptual rather than mathematical approach. The authors gear the text toward the needs, level of sophistication, and interest in multivariate methodology of students in these applied programs who need to focus on design and interpretation rather than the intricacies of specific computations: Coverage of the most widely used multivariate designs: multiple regression, exploratory factor analysis, MANOVA, and structural equation modeling; Integrated SPSS examples for hands-on learning from one large study (for consistency of application throughout the text); Examples of written results to enable students to learn how the results of these procedures are communicated; Practical application of the techniques using contemporary studies that will resonate with students
  • Editor: Thousand Oaks Sage Publications
  • Data de criação/publicação: 2006
  • Formato: xxxv, 722 p il 24 cm.
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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