Applied Multivariate Research: Design and Interpretation / Edition 2

Applied Multivariate Research: Design and Interpretation / Edition 2

by Lawrence S. Meyers, Glenn C. Gamst, Anthony J. Guarino
     
 

ISBN-10: 141298811X

ISBN-13: 9781412988117

Pub. Date: 08/17/2012

Publisher: SAGE Publications

This book provides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter, using a conceptual, non-mathematical, approach. Addressing correlation, multiple regression, exploratory factor analysis, MANOVA, path analysis, and structural equation modeling, it is geared toward the needs, level of…  See more details below

Overview

This book provides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter, using a conceptual, non-mathematical, approach. Addressing correlation, multiple regression, exploratory factor analysis, MANOVA, path analysis, and structural equation modeling, it is geared toward the needs, level of sophistication, and interest in multivariate methodology that serves students in applied programs in the social and behavioral sciences. Readers are encouraged to focus on design and interpretation rather than the intricacies of specific computations.

Product Details

ISBN-13:
9781412988117
Publisher:
SAGE Publications
Publication date:
08/17/2012
Edition description:
Second Edition
Pages:
1104
Sales rank:
893,352
Product dimensions:
7.70(w) x 9.20(h) x 2.20(d)

Related Subjects

Table of Contents

Part I. The Basics of Multivariate Design
Chapter 1. An Introduction to Multivariate Design
Chapter 2. Some Fundamental Research Design Concepts
Chapter 3A. Data Screening
Chapter 3B. Data Screening Using IBM SPSS
Part II. Comparisons of Means
Chapter 4A. Univariate Comparison of Means
Chapter 4B. Univariate Comparison of Means Using IBM SPSS
Chapter 5A. Multivariate Analysis of Variance (MANOVA)
Chapter 5B. Multivariate Analysis of Variance (MANOVA) Using IBM SPSS
Part III. Predicting the Value of a Single Variable
Chapter 6A. Bivariate Correlation and Simple Linear Regression
Chapter 6B. Bivariate Correlation and Simple Linear Regression Using IBM SPSS
Chapter 7A. Multiple Regression: Statistical Methods
Chapter 7B. Multiple Regression: Statistical Methods Using IBM SPSS
Chapter 8A. Multiple Regression: Beyond Statistical Regression
Chapter 8B. Multiple Regression: Beyong Statistical Regression Using IBM SPSS
Chapter 9A. Multilevel Modeling
Chapter 9B. Multilevel Modeling Using IBM SPSS
Chapter 10A. Binary and Multinomial Logistic Regression and ROC Analysis
Chapter 10B. Binary and Multinomial Logistic Regression and ROC Analysis Using IBM SPSS
Part IV. Analysis of Structure
Chapter 11A. Discriminant Function Analysis
Chapter 11B. Discriminant Function Analysis Using IBM SPSS
Chapter 12A. Principal Components and Exploratory Factor Analysis
Chapter 12B. Principal Components and Exploratory Factor Analysis Using IBM SPSS
Chapter 13A. Canonical Correlation Analysis
Chapter 13B. Canonical Correlation Analysis Using IBM SPSS
Chapter 14A. Multidimensional Scaling
Chapter 14B. Multidimensional Scaling Using IBM SPSS
Chapter 15A. Cluster Analysis
Chapter 15B. Cluster Analysis Using IBM SPSS
Part V. Fitting Models to Data
Chapter 16A. Confirmatory Factor Analysis
Chapter 16B. Confirmatory Factor Analysis Using Amos
Chapter 17A. Path Analysis: Multiple Regression
Chapter 17B. Path Analysis: Multiple Regression Using IBM SPSS
Chapter 18A. Path Analysis: Structural Modeling
Chapter 18B. Path Analysis: Structural Modeling Using Amos
Chapter 19A. Structural Equation Modeling
Chapter 19B. Structural Equation Modeling Using Amos
Chapter 20A. Model Invariance: Applying a Model to Different Groups
Chapter 20B. Assessing Model Invariance Using Amos

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