## Applied Multivariate Research: Design and InterpretationMultivariate designs were once the province of the very few exalted researchers who understood the underlying advanced mathematics. Today, through the sophistication of statistical software packages such as SPSS, virtually all graduate students across the social and behavioural sciences are exposed to the complex multivariate statistical techniques without having to learn the mathematical computations needed to acquire the data output. These students - in psychology, education, political science, etc. - will never be statisticians and appropriately so, their preparation and coursework reflects less of an emphasis on the mathematical complexities of multivariate statistics and more on the analysis and the interpretation of the methods themselves and the actual data output. This book provides full coverage of the wide range of multivariate topics in a conceptual, rather than mathematical, approach. The author gears toward the needs, level of sophistication, and interest in multivariate methodology of students in applied areas that need to focus on design and interpretation rather than the intricacies of specific computations. The book includes: - Coverage of the most widely used multivariate designs: multiple regression, exploratory factor analysis, MANOVA, and structural equation modeling. - Integrated SPSS examples for hands-on learning from one large study (for consistency of application throughout the text). - Examples of written results to enable students to learn how the results of these procedures are communicated. - Practical application of the techniques using contemporary studies that will resonate with students. |

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### Contents

List of Figures | xxv |

Preface | xxxi |

FOUNDATIONS | xxxvi |

Some Fundamental Research Design Concepts | 17 |

3A Data Screening | 43 |

Figure 3a 1 Histogram Showing | 50 |

3B Data Screening Using SPSS | 75 |

Figure 3b 1 Frequencies Main Dialog Box | 77 |

7B TwoGroup Discriminant Function Analysis Using SPSS | 267 |

THE DEPENDENT WARIABLE VARIATE | 279 |

8B Univariate Comparisons of Means Using SPSS | 315 |

Comparing Two Groups | 365 |

9B TwoGroup MANOVA Using SPSS | 385 |

Comparing Three or More Groups | 405 |

Comparing | 415 |

TwoWay Factorial | 439 |

Figure 3b 12 Compute Variable Dialog | 90 |

Figure 3b 15 Scatterplot Main Dialog Box and Its Matrix Box | 93 |

Chapter 4 | 106 |

THE INDEPENDENT VARIABLE VARIATE | 107 |

Figure 4a 7 Scatterplot of SelfEsteem | 122 |

Figure 4a 15 Actual Values of YASSOciated With | 134 |

4B Bivariate Correlation | 137 |

5A Multiple Regression | 147 |

Figure 5a 1 SelfEsteem Dependent | 156 |

Figure 5a 6 Unique Contribution of Variable | 175 |

5B Multiple Regression Using SPSS | 197 |

Figure 5b 1 Output From Explore Showing Extreme | 199 |

If Dialog Box | 204 |

Chapter 6 | 220 |

6A Logistic Regression | 221 |

6B Logistic Regression Using SPSS | 243 |

Figure 6b 1 Logistic Regression Main Dialog | 244 |

7A Discriminant Function Analysis | 255 |

Figure 7a 1 Classification Table | 263 |

TwoWay Factorial Using SPSS | 453 |

THE EMERGENT WARIATE | 465 |

12B Principal Components | 515 |

13A Confirmatory Factor Analysis | 539 |

13B Confirmatory Factor Analysis Using AMOS | 569 |

MODEL FITTING | 585 |

Structuring the Path Analyses | 594 |

The Multiple Regression Strategy to Perform a Path Analysis | 600 |

Structural Equation Modeling | 611 |

617 | |

14B Path Analysis Using SPSS and AMOS | 619 |

15A Applying a Model to Different Groups | 645 |

15B Assessing Model Invariance | 655 |

Appendix | 673 |

695 | |

701 | |

About the Authors | 721 |