

ADVANCED & MULTIVARIATE STATISTICAL METHODS FOR SOCIAL SCIENCE RESEARCH
Soleman H. AbuBader, Howard University
Unlike other advanced statistical texts, this book combines the theory and practice behind a number of statistical techniques which students of the social sciences need to evaluate, analyze, and test their research hypotheses.
Each chapter discusses the purpose, rationale, and assumptions for using each statistical test, rather than focusing on the memorization of formulas. The tests are further elucidated throughout the text by real examples of analysis. Of particular value to students is the book’s detailed discussion of how to utilize SPSS to run each test, read its output, interpret, and write the results.
Advanced & Multivariate Statistical Methods for Social Science Research is an indispensable resource for students of disciplines as varied as social work, nursing, public health, psychology, and education.
Electronic database files are available for student and instructor use.
Features
 Reviews bivariate statistical tests to ensure comprehension of advanced steps
 Covers simple, multiple, and logistic regression analyses; repeated measures; analysis of variances and covariances; and canonical correlation analysis
 Discusses in depth the processes of data cleaning, missing values, outlier cases, normality, and data transformation
 Illustrates how to present the results of tests in readable tables and graphs
Table of Contents
Preface
CHAPTER 1: 
REVIEW OF BIVARIATE STATISTICAL TESTS 


Parametric and Nonparametric Tests
Pearson’s ProductMoment Correlation Coefficient
Independent tTest
Dependent tTest
OneWay Analysis of Variance
ChiSquare Test of Association 


CHAPTER 2: 
DATA EVALUATION: DATA CLEANING, MIISING VALUES, OUTLIER CASES, NORMALITY, AND DATA TRANSFORMATION 


Data Cleaning and Categorical Coding
Missing Data
Outliers
Normality and Data Transformation 


CHAPTER 3: 
SIMPLE LINEAR REGRESSION 


Equation of Simple Linear Regression
Coefficients of Simple Linear Regression
Confidence Interval
Assumptions
Practical Example
Writing the Results 


CHAPTER 4: 
MULTIPLE REGRESSION ANALYSIS 


Equation of Multiple Regression
Coefficients of Multiple Regression
Assumptions
Selecting Appropriate Factors for Regression
Methods of Data Entry in Multiple Regression Analysis
Practical Example
Writing the Results 


CHAPTER 5: 
LOGISTIC REGRESSION ANALYSIS 


Equation of Logistic Regression
Research Questions of Logistic Regression
Coefficients of Logistic Regression
Assumptions
Methods of Data Entry in Logistic Regression
Practical Example
Writing the Results 


CHAPTER 6: 
TWOWAY ANALYSIS OF VARIANCE 


Sources of Variation
Advantages
Research Questions and Hypotheses
Assumptions
Post Hoc Tests
Practical Example
Hypothesis Testing
Writing the Results 


CHAPTER 7: 
TWOWAY ANALYSIS OF COVARIANCE 


Sources of Variation
Advantages
Research Questions and Hypotheses
Assumptions
Post Hoc Tests
Practical Example
Writing the Results 


CHAPTER 8: 
REPEATED MEASURES ANALYSIS OF VARIANCE 


Types of Analysis of Variance
Sources of Variation
Advantages
Research Questions and Hypotheses
Assumptions
Correction for Sphericity
Post Hoc Tests
First Practical Example – WithinSubjects ANOVA
Writing the Results of WithinSubjects ANOVA
Second Practical Example – Mixed BetweenWithinSubjects ANOVA
Writing the Results of Mixed BetweenWithinSubjects ANOVA 


CHAPTER 9: 
MULTIVARIATE ANALYSIS OF VARIANCE AND COVARIANCE 


Advantages
Sources of Variance
Multivariate Tests
Post Hoc Tests
Assumptions
RESEARCH QUESTIONS AND HYPOTHESES
First Practical Example – Multivariate ANOVA
Writing the Results of MANOVA
Second Practical Example – MANCOVA
Writing the Results of Mixed BetweenWithinSubjects ANOVA 


CHAPTER 10: 
CANONICAL CORRELATION ANALYSIS 


Concepts of Canonical Correlation
Statistical Tests
Advantages of Canonical Correlation
Research Questions and Hypotheses
Assumptions
Practical Example
Writing the Results 


APPENDIX – Data Files
REFERENCES
INDEX
About the Author
Soleman H. AbuBader (Ph.D. University of Utah, MSW Augsburg College) is associate professor in the School of Social Work at Howard University. He has worked as a social work practitioner, researcher, and teacher. He is the author of Using Statistical Methods in Social Work Practice (2006)as well as several articles that focus on the elderly, welfare, depression, and organizational behavior.
2010, Paper, 350 Pages, ISBN: 9781933478821, Price $84.95 