A Step-by-Step Approach to Using the SAS System for Univariate and Multivariate Statistics

A Step-by-Step Approach to Using the SAS System for Univatiate
and Multivariate Statistics
Larry Hatcher, Ph.D. and Edward J. Stepanski, Ph.D.
Acknowledgements vii
Using This Book ix
Chapter 1 Basic Concepts in Research and Dadta Analysis

Introduction: A Common Language for Researchers
Steps to Follow when Conducting Research
Variables, Values, and Observations
Scales of Measurement
Basic Approaches to Research
Descriptive Versus Inferential Statistical Analysis
Hypothesis Testing
Conclusion
References 19

Chapter 2 Introduction to SAS Programs, SAS Logs, and SAS Output

Introduction: What Is the SAS System?
Three Types of SAS System Files
Conclusion

Chapter 3 Data Input

Introduction: Inputting Questionnaire Data versus Other Types of Data
Keying Data: An Illustrative Example
Inputting Data Using the CARDS Statement
Additional Guidelines
Inputting a Correlation or Covariance Matrix
Inputting Data Using the INFILE Statement Rather than the CARDS Statement
Controlling the Size of the Output and Log Pages with the OPTIONS Statement
Conclusion
References

Chapter 4 Working with Variables and Observations in SAS Data Sets

Introduction: Manipulating, Subsetting, Concatenating, and Merging Data
Placement of Data Manipulation and Data Subsetting Statements
Data Manipulation
Data Subsetting
A More Comprehensive Example
Concatenating and Merging Data Sets
Conclusion
References

Chapter 5 Exploring Data with PROC MEANS, PROC FREQ, PROC PRINT, and

PROC UNIVATIATE
Introduction: Why Perform Simple Descriptive Analyses?
Example: A Revised Volunteerism Survey
Computing Descriptive Statistics with PROC MEANS
Creating Frequency Tables with PROC FREQ
Printing Raw Data with PROC PRINT
Testing for Normality with PROC UNIVARIATE
Conclusion
References

Chapter 6 Measures of Bivariate Association

Introduction: Significance Tests versus Measures of Association
Choosing the Correct Statistic
Pearson Correlations
Spearman Correlations
The Chi-Square Test of Independence
Conclusion

Appendix: Assumptions Underlying the Tests 170
References
Chapter 7 t Tests: Independent Samples and Paired Samples

Introduction: Two Types of t Tests
The Independent-Samples t Test
The Paired-Samples t Test
Conclusion

Appendix: Assumptions Underlying the t Test 209
References
Chapter 8 One-Way ANOVA with One Between-Groups Factor

Introduction: The Basics of One-Way ANOVA, Between-Groups Design
Example with Significant Differences between Experimental Conditions
Understanding the Meaning of the F Statistic
Conclusion

Appendix: Assumptions Underlying One-Way ANOVA with One Between-Groups Factor 236
References
Chapter 9 Factorial ANOVA with Two Between-Groups Factors

Introduction to Factorial Designs
Some Possible Results from a Factorial ANOVA
Example with a Nonsignificant Interaction
Example with a Significant Interaction
Conclusion

Appendix: Assumptions Underlying Factorial ANOVA with Two Between-Groups Factors 280
Chapter 10 Multivatiate Analysis of Variance (MANOVA), with One Between-Groups Factor

Introduction: The Basics of Multivariate Analysis of Variance
Example with Significant Differences between Experimental Conditions
Example with Nonsignificant Differences between Experimental Conditions
Conclusion

Appendix: Assumptions Underlying Multivariate ANOVA with One Between-Groups Factor 302
References
Chapter 11 One-Way ANOVA with One Repeated-Measures Factor

Introduction: What is a Repeated-Measures Design?
Example: Significant Differences in Investment Size across Time
Further Notes on Repeated-Measures Analyses
Conclusion

Appendix: Assumptions Underlying the One-Way ANOVA with One Repeated-Measures Factor 329
References
Chapter 12 Factorial ANOVA with Repeated-Measures Factors and Between-Groups Factors

Introduction: The Basics of Mixed-Design ANOVA
Some Possible Results from a Two-Way Mixed-Design ANOVA
Problems with the Mixed-Design ANOVA
Example with a Nonsignificant Interaction
Example with a Significant Interaction
Use of Other Post-Hoc Tests with the Repeated-Measures Variable
Conclusion

Appendix: Assumptions Underlying Factorial ANOVA with Repeated-Measures
Factors and Between-Groups Factors
References
Chapter 13 Multiple Regression

Introduction: Answering Questions with Multiple Regression
Background: Predicting a Criterion Variable from Multiple Predictors
The Results of a Multiple Reression Analysis
Example: A Test of the Investment Model
Overview of the Analysis
Gathering and Inputting Data
Computing Bivariate Correlations with PROC CORR
Estimating the Full Multiple Regression Equation with PROC REG
Computing Uniqueness Indices with PROC REG
Summarizing the Results in Tables
Getting the Big Picture
Formal Description of Results for a Paper
Conclusion: Learning More about Multiple Regression

Appendix: Assumptions Underlying Multiple Regression 446
References:
Chapter 14 Principal Component Analysis

Introduction: The Basics of Principal Component Analysis
Example: Analysis of the Prosocial Orientation Inventory
SAS Program and Output
Steps in Conducting Principal Component Analysis
An Example with Three Retained Components
Conclusion

Appendix: Assumptions Underlying Principal Component Analysis 503
References
Chapter 15 Assessing Scale Reliability with Coefficient Alpha

Introduction: The Basics of Scale Reliability
Coefficient Alpha
Assessing Coefficient Alpha with PROC CORR
Summarizing the Results
Conclusion
References

Appendix A Choosing the Correct Statistic 517
Introduction: Thinking about the Number and Scale of Your Variables
Guidelines for Choosing the Correct Statistic
Conclusion
References

Appendix B Data Sets 525

Appendix C Critical Values of the F Distribution 529
Index