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Author: James P. Stevens Publisher: Routledge ISBN: 1136910697 Category : Education Languages : en Pages : 666
Book Description
This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.
Author: James P. Stevens Publisher: Routledge ISBN: 1136910697 Category : Education Languages : en Pages : 666
Book Description
This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size by providing guidelines so that the results can be generalized. The book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.
Author: James Paul Stevens Publisher: Lawrence Erlbaum Associates ISBN: Category : Mathematics Languages : en Pages : 656
Book Description
This book was written for those who will be using, rather than developing, advanced statistical methods. It focuses on a conceptual understanding of the material rather than proving results. It is a graduate level textbook with abundant examples.
Author: James Stevens Publisher: Psychology Press ISBN: Category : Education Languages : en Pages : 718
Book Description
Of Important Points -- Two-Group Multivariate Analysis Of Variance -- Four Statistical Reasons for Preferring a Multivariate Analysis -- The Multivariate Test Statistic as a Generalization of Univariate t -- Numerical Calculations for a Two-Group Problem -- Three Post Hoc Procedures -- SAS and SPSS Control Lines for Sample Problem and Selected Printout -- Multivariate Significance but No Univariate Significance -- Multivariate Regression Analysis for the Sample Problem -- Power Analysis -- Ways of Improving Power -- Power Estimation on SPSS MANOVA -- Multivariate Estimation of Power -- K-Group Manova: A Priori And Post Hoc Procedures -- Multivariate Regression Analysis for a Sample Problem -- Traditional Multivariate Analysis of Variance -- Multivariate Analysis of Variance for Sample Data -- Post Hoc Procedures -- The Tukey Procedure -- Planned Comparisons -- Test Statistics for Planned Comparisons -- Multivariate Planned Comparisons on SPSS MANOVA -- Correlated Contrasts -- Studies Using Multivariate Planned Comparisons -- Stepdown Analysis -- Other Multivariate Test Statistics -- How Many Dependent Variables for a MANOVA? -- Power Analysis--A Priori Determination of Sample Size -- Novince (1977) Data for Multivariate Analysis of Variance Presented in Tables 5.3 and 5.4 -- Assumptions In Manova -- ANOVA and MANOVA Assumptions -- Independence Assumption -- What Should Be Done With Correlated Observations? -- Normality Assumption -- Multivariate Normality -- Assessing Univariate Normality -- Homogeneity of Variance Assumption.
Author: James P. Stevens Publisher: ISBN: 9780805801859 Category : Languages : en Pages : 528
Book Description
This book was written for those who will be using, rather than developing, advanced statistical methods. It focuses on a conceptual understanding of the material rather than proving results. It is a graduate level textbook with abundant examples.
Author: Stevens Publisher: Lawrence Erlbaum Assoc Incorporated ISBN: 9780805831924 Category : Mathematics Languages : en Pages : 672
Book Description
This successful text includes: *coverage of both exploratory and confirmatory factor analysis plus illustrations of LISREL and EQS; *the EXAMINE procedure from SPSSX--terrific for exploring data; *a new section on the doubly multivariate problem in which subjects are measured on several dependent outcome variables at each point in time, or for each treatment/condition; and *added exercises on categorical data analysis and the answers for the more difficult problems. There is a 3.5" disk (free to those adopting the text) of all data sets in the book, along with several large data sets.
Author: Keenan A. Pituch Publisher: Routledge ISBN: 1317805917 Category : Psychology Languages : en Pages : 827
Book Description
Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises) Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.
Author: Neil H. Timm Publisher: Springer Science & Business Media ISBN: 0387953477 Category : Mathematics Languages : en Pages : 709
Book Description
This book provides a broad overview of the basic theory and methods of applied multivariate analysis. The presentation integrates both theory and practice including both the analysis of formal linear multivariate models and exploratory data analysis techniques. Each chapter contains the development of basic theoretical results with numerous applications illustrated using examples from the social and behavioral sciences, and other disciplines. All examples are analyzed using SAS for Windows Version 8.0.
Author: Abdelmonem Afifi Publisher: CRC Press ISBN: 1351788906 Category : Mathematics Languages : en Pages : 528
Book Description
This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.
Author: Lawrence S. Meyers Publisher: SAGE ISBN: 9781412904124 Category : Mathematics Languages : en Pages : 768
Book Description
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 behavioural 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 author gears toward the needs, level of sophistication, and interest in multivariate methodology of students in applied areas that need to focus on design and interpretation rather than the intricacies of specific computations. The book includes: - 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.
Author: James P. Stevens
Author: James P. Stevens
Author: James Paul Stevens
Author: James Stevens
Author: James P. Stevens
Author: J.P. STEVENS
Author: Stevens
Author: Keenan A. Pituch
Author: Neil H. Timm
Author: Abdelmonem Afifi
Author: Lawrence S. Meyers