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dugard p approaching multivariate analysis 2ed 2022

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Textbook in PDF format This fully updated new edition not only provides an introduction to a range of advanced statistical techniques that are used in psychology, but has been expanded to include new chapters describing methods and examples of particular interest to medical researchers. It takes a very practical approach, aimed at enabling readers to begin using the methods to tackle their own problems. This book provides a non-mathematical introduction to multivariate methods, with an emphasis on helping the reader gain an intuitive understanding of what each method is for, what it does and how it does it. The first chapter briefly reviews the main concepts of univariate and bivariate methods and provides an overview of the multivariate methods that will be discussed, bringing out the relationships among them, and summarising how to recognise what types of problem each of them may be appropriate for tackling. In the remaining chapters, introductions to the methods and important conceptual points are followed by the presentation of typical applications from psychology and medicine, using examples with fabricated data. Instructions on how to do the analyses and how to make sense of the results are fully illustrated with dialogue boxes and output tables from SPSS, as well as details of how to interpret and report the output, and extracts of SPSS syntax and code from relevant SAS procedures. This book gets students started, and prepares them to approach more comprehensive treatments with confidence. This makes it an ideal text for psychology students, medical students and students or academics in any discipline that uses multivariate methods. Preface to the Second Edition Preface to the First Edition Multivariate Techniques in Context Using this Book Statistics in Research Terminology and Conventions Testing Hypotheses The Model and Prediction Power The General Linear Model Generalized Linear Models Exploratory Methods Reference Analysis of Variance (ANOVA) Introduction and Terminology Assumptions and Transformations Effect Size and Power A One-Way ANOVA A Factorial Between-Subjects Design A Factorial Within-Subjects Design A Mixed Factorial Design Reporting Results References Multivariate Analysis of Variance (MANOVA) Introduction A Between-Subjects Design with Two DVs A Within-Subjects Design with Two DVs MANOVA and Repeated Measures ANOVA Compared Missing Data Outliers Reporting Results Multiple Regression Introduction and Intuitive Explication Data Requirements A Psychology Example of a Multiple Regression Problem Using a Stepwise Method Categorical Variables Estimating the Success of Predicting New Cases Hierarchical Regression Non-Linear Relationships Reporting Results Reference Analysis of Covariance (ANCOVA) Introduction and Intuitive Explication ANCOVA: A Psychology Example of a Pretest–Posttest Control Group Design ANCOVA with More Than One Treatment Factor Reporting Results Reference Partial Correlation, Mediation and Moderation Introduction Partial Correlation A Psychology Example Suitable for Partial Correlation Analysis Semipartial (or Part) Correlations Reporting Results: Partial Correlation Analysis Mediation Effects Reporting Results: Mediation Analysis Moderating Effects Reporting Results: Moderation Analysis Complex Path Models References Path Analysis Introduction Path Diagrams and Terminology Conducting a Path Analysis Using Regression Using a Dedicated Package (AMOS) to do Path Analysis Reporting Results Reference Factor Analysis Introduction Exploratory Factor Analysis (EFA) The Reliability of Factor Scales: Internal Consistency of Scales Confirmatory Factor Analysis (CFA) Structural Equation Modelling Reporting Results Reference Discriminant Analysis and Logistic Regression Discriminant Analysis A Psychology Example of a Discriminant Analysis Problem Reporting Results: Discriminant Analysis Logistic Regression: An Alternative Approach to Classification into Two Groups An Example with Psychology Data Reporting Results: Logistic Regression Cluster Analysis Introduction Calculating Distance Between Cases Using the Distance Matrix to Form Clusters Some Examples and (Fabricated) Data Results for Other Datasets Deciding How Many Clusters There are Clustering Variables and Some (Fabricated) Binary Data Reporting Results References Multidimensional Scaling Introduction and Intuitive Explication Multidimensional Scaling: A Psychology Example and (Fabricated) Data Multidimensional Scaling and Seriation Reporting Results Reference Loglinear Models Introduction and Intuitive Explication A Psychology Example of Loglinear Analysis Selecting a Reduced Model Automating Model Selection Measures of Association and Size of Effects Variables with More Than Two Categories Reporting Results Poisson Regression Introduction A Psychology Experiment and (Fabricated) Data with Equal Observation Periods Poisson Models with Unequal Observation Periods A Psychology Experiment and (Fabricated) Data with Unequal Observation Periods Reporting Results Survival Analysis Introduction A Psychology Example: An Experiment with Fabricated Data Incomplete Records Reporting Results Longitudinal Data Introduction Some Benefits and Some Problems ANCOVA Within-Subjects ANOVA MANOVA Regression Generalized Estimating Equations Poisson Regression and Survival Analysis Time Series Reference Appendix: SPSS and SAS Syntax Introduction An Example of SPSS and Sas Syntax Uses of SPSS and SAS Syntax How to Create an SPSS Syntax File How to Edit an SPSS Syntax File How to Perform Analyses Using An SPSS Syntax File SPSS and SAS Syntax for Selected Analyses Further Reading Glossary Abbreviations Author Index Subject Index

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dugard p approaching multivariate analysis 2ed 2022