Meyers L.S., Gamst G.C., Guarino A.J. Performing Data Analysis Using IBM SPSS

Wiley, 2013. — 736 p. — ISBN: 1118357019, 9781118357019Performing Data Analysis Using IBM SPSS20 uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and manipulate output.
Designed as a user’s guide for students and other interested readers to perform statistical data analysis with IBM SPSS, this book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of readers in social and behavioral science, business, health-related, and education programs. Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis.Author Information
Lawrence S. Meyers, Ph.D., is Professor in the Depart-ment of Psychology at California State University, Sacramento. The author of numerous books, Dr. Meyers is a member of the Association for Psychological Science and the Society for Industrial and Organiza-tional Psychology.
Glenn C. Gamst, Ph.D., is Chair and Professor in the Department of Psychology at the University of La Verne. His research interests include univariate and multivariate statistics as well as multicultural community mental health outcome research.
A. J. Guarino, Ph.D., is Professor of Biostatistics at Massachusetts General Hospital, Institute of Health Professions, where he serves as the methodologist for capstones and dissertations as well as teaching advanced Biostatistics courses. Dr. Guarino is also the statistician on numerous National Institutes of Health grants and coauthor of several statistical textbooks.Getting Started With Ibm SPSS
Introduction To Ibm SPSS
Entering Data In Ibm SPSS
Importing Data From Excel To Ibm SPSS
Obtaining, Editing, And Saving Statistical output
Performing Statistical Procedures in ibm SPSS
Editing Output
Saving And Copying Output
Manipulating Data
Sorting And Selecting Cases
Splitting Data Files
Merging Data From Separate Files
Descriptive Statistics Procedures
Frequencies
Descriptives
Explore
Simple Data Transformations
Standardizing Variables To Z Scores
Recoding Variables
Visual Binning
Computing New Variables
Transforming Dates To Age
Evaluating Score Distribution assumptions
Detecting Univariate Outliers
Detecting Multivariate Outliers
Assessing Distribution Shape: Normality, skewness, and kurtosis
Transforming Data To Remedy Statistical assumption violations
Bivariate Correlation
Pearson Correlation
Spearman Rho And Kendall Tau-B Rank-Order correlations
Regressing (Predicting) Quantitative variables
Simple Linear Regression
Centering The Predictor Variable In Simple linear regression
Multiple Linear Regression
Hierarchical Linear Regression
Polynomial Regression
Multilevel Modeling
Regressing (Predicting) Categorical variables
Binary Logistic Regression
Roc Analysis
Multinominal Logistic Regression
Survival Analysis
Survival Analysis: Life Tables
The Kaplan–Meier Survival Analysis
Cox Regression
Reliability As A Gauge Of Measurement quality
Reliability Analysis: Internal Consistency
Reliability Analysis: Assessing Rater Consistency
Analysis Of Structure
Principal Components And Factor Analysis
Confirmatory Factor Analysis
Evaluating Causal (Predictive) Models
Simple Mediation
Path Analysis Using Multiple Regression
Path Analysis Using Structural Equation modeling
Structural Equation Modeling
T Test
One-Sample T Test
Independent-Samples T Test
Paired-Samples T Test
Univariate Group Differences: Anova And ancova
One-Way Between-Subjects Anova
Polynomial Trend Analysis
One-Way Between-Subjects Ancova
Two-Way Between-Subjects Anova
One-Way Within-Subjects Anova
Repeated Measures Using Linear Mixed Models
Two-Way Mixed Anova
Multivariate Group Differences: Manova and discriminant function analysis
One-Way Between-Subjects Manova
Discriminant Function Analysis
Two-Way Between-Subjects Manova
Multidimensional Scaling
Multidimensional Scaling: Classical Metric
Multidimensional Scaling: Metric Weighted
Cluster Analysis
Hierarchical Cluster Analysis
K-Means Cluster Analysis
Nonparametric Procedures For analyzing frequency data
Single-Sample Binomial And Chi-Square Tests: binary categories
Single-Sample (One-Way) Multinominal chi-square tests
Two-Way Chi-Square Test Of Independence
Risk Analysis
Chi-Square Layers
Hierarchical Loglinear AnalysisStatistics Tables