### Upcoming Workshops:

Thank you for visiting my course notes. Here are some upcoming opportunities to learn from me and my colleagues in person:

Workshop | Dates | Location | Instructor |
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Currently no workshops are planned |

##### Multivariate Methods in Education (ERSH 8350)

Fall, 2011: University of Georgia

##### Course Documents

Materials |
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Downloadable Course Syllabus |

Course Facebook Page |

##### Final Examination

Final Exam Instructions | Data File | Audio File of Final Discussion |

##### Lecture Slides and Example Files

##### References

Week | Number | Reference |
---|---|---|

2 | R2.1 | Chapter 2: Matrix algebra and random vectors. Johnson, R. A. & Wichern, D. W. (2002). Applied Multivariate Statistical Analysis (5th Ed.). Upper Saddle River, N.J., Prentice-Hall. |

R2.2 | Chapter 8: Principal components. Johnson, R. A. & Wichern, D. W. (2002). Applied Multivariate Statistical Analysis (5th Ed.). Upper Saddle River, N.J., Prentice-Hall. | |

R2.3 | Kramer, J. R., Chan, G. C., Hellelbrock, V. M., Kuperman, S., Bucholz, K. K., Edenberg, H. J., Schuckit, M. A., Nurnberger, J. I., Foroud, T., Dick, D. M., Bierut, L. J., Porjesz, B. (2010). A principal components analysis of the abbreviated desires for alcohol questionnaire (DAQ). Journal of Studies on Alcohol and Drugs, 71, 150-155. | |

3 | R3.1 | Chapter 3: Sample geometry and random sampling. Johnson, R. A. & Wichern, D. W. (2002). Applied Multivariate Statistical Analysis (5th Ed.). Upper Saddle River, N.J., Prentice-Hall. |

R3.2 | Chapter 4: The multivariate normal distribution. Johnson, R. A. & Wichern, D. W. (2002). Applied Multivariate Statistical Analysis (5th Ed.). Upper Saddle River, N.J., Prentice-Hall. | |

R3.3 | Burdenski, T. (2000). Evaluating univariate, bivariate, and multivariate normality using graphical and statistical procedures. Multiple Linear Regression Viewpoints, 26, 15-28. | |

4 | R4.1 | Chapter 13: Repeated measures analysis. Stevens, J. P. (2002). Applied Multivariate Statistics for the Social Sciences (4th Ed.). Mahwah, N.J., Erlbaum. |

R4.2 | Chapter 6: Comparisons of several multivariate means. Johnson, R. A. & Wichern, D. W. (2002). Applied Multivariate Statistical Analysis (5th Ed.). Upper Saddle River, N.J., Prentice-Hall. | |

R4.3 | Lau, S., & Chueng, P. C. (2010). Creativity assessment: Comparability of the electronic and paper-and-pencil versions of the Wallach-Kogan creativity tests. Thinking Skills and Creativity, 5 101-107. | |

5 | R5.1 | Chapter 1: An introduction to missing data. Enders, C. K. (2010) Applied Missing Data Analysis. New York: Guildford. |

R5.2 | Chapter 2: Traditional methods for dealing with missing data. Enders, C. K. (2010) Applied Missing Data Analysis. New York: Guildford. | |

R5.3 | Chapter 7: The imputation phase of multiple imputation. Enders, C. K. (2010) Applied Missing Data Analysis. New York: Guildford. | |

R5.4 | Chapter 8: The analysis and pooling phases of multiple imputation. Enders, C. K. (2010) Applied Missing Data Analysis.New York: Guildford. | |

R5.5 | Chapter 9: Practical issues in multiple imputation. Enders, C. K. (2010) Applied Missing Data Analysis. New York: Guildford. | |

7 | R7.1 | Chapter 3: An introduction to maximum likelihood estimation. Enders, C. K. (2010) Applied Missing Data Analysis. New York: Guildford. |

R7.2 | Chapter 4: Maximum likelihood missing data handling. Enders, C. K. (2010) Applied Missing Data Analysis. New York: Guildford. | |

R7.3 | Chapter 5: Improving the accuracy of maximum likelihood analyses. Enders, C. K. (2010) Applied Missing Data Analysis.New York: Guildford. | |

R7.4 | Chapter 6: An introduction to Bayesian estimation. Enders, C. K. (2010) Applied Missing Data Analysis. New York: Guildford. | |

11 | R11.1 | Chapter 8: Principal components. Johnson, R. A. & Wichern, D. W. (2002). Applied Multivariate Statistical Analysis (5th Ed.). Upper Saddle River, N.J., Prentice-Hall. |

R11.2 | Chapter 9: Factor analysis and inference for structured covariance matrices. Johnson, R. A. & Wichern, D. W. (2002).Applied Multivariate Statistical Analysis (5th Ed.). Upper Saddle River, N.J., Prentice-Hall. | |

12 | R12.1 | Chapter 1: Historical foundations of structural equation modeling for continuous and categorical latent variables. Kaplan (2009). Structural Equation Modeling: Foundations and Extensions (2nd Ed.). Thousand Oaks, C.A.: Sage. |

R12.2 | Chapter 2: Path analysis. Kaplan (2009). Structural Equation Modeling: Foundations and Extensions (2nd Ed.). Thousand Oaks, C.A.: Sage. | |

R12.3 | Chapter 1: Factor analysis. Kaplan (2009). Structural Equation Modeling: Foundations and Extensions (2nd Ed.).Thousand Oaks, C.A.: Sage. | |

R12.4 | Chapter 4: Structural equation models in single and multiple groups. Kaplan (2009). Structural Equation Modeling: Foundations and Extensions (2nd Ed.). Thousand Oaks, C.A.: Sage. |