and Multivariate Statistics

Larry Hatcher, Ph.D. and Edward J. Stepanski, Ph.D.

Acknowledgements vii

Using This Book ix

- 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

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

- 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

- 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

- 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

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

References

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

References

- 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

References

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

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

References

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

References

- 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

Factors and Between-Groups Factors

References

- 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

References:

- 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

References

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

Introduction: Thinking about the Number and Scale of Your Variables

Guidelines for Choosing the Correct Statistic

Conclusion

References