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Chapter 13 General Linear Model

Part III: Additional Hypothesis Tests. Chapter 13 General Linear Model. Renee R. Ha, Ph.D. James C. Ha, Ph.D. Integrative Statistics for the Social & Behavioral Sciences. ANOVA/ t test. Linear Regression. Linear Equation for Regression. Linear or Additive Equation. Multifactorial ANOVA.

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Chapter 13 General Linear Model

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  1. Part III: Additional Hypothesis Tests Chapter 13 General Linear Model Renee R. Ha, Ph.D. James C. Ha, Ph.D Integrative Statistics for the Social & Behavioral Sciences

  2. ANOVA/t test

  3. Linear Regression

  4. Linear Equation for Regression

  5. Linear or Additive Equation

  6. Multifactorial ANOVA • Also called MANOVA

  7. Repeated-Measures ANOVA

  8. Linear Equation for Multiple Regression

  9. Assumptions of General Linear Model • All of these formulas share in common similar assumptions (i.e., normal distribution) and a linear form where the effects of each variable on the score are additive. • All of these equations are fundamentally the same form of linear equation or model, and they can all be solved using the same process (matrix algebra).

  10. Advantages of Understanding GLM 1. You know why there is an F-obtained value in you’re linear regression output. 2. You can mix and match the measurement scales of your independent variables. 3. You can address the problem of predictor variables that are correlated with one another.

  11. Raw Data Files for SPSS

  12. Figure 13.1 • Choosing the General Linear Model Option in SPSS

  13. Selecting your Independent and Dependent Variables in SPSS

  14. Choosing the Model in SPSS

  15. Table 13.1 • Tests of Between-Subjects Effects • Dependent Variable: DAYS a R Squared = .926 (Adjusted R Squared = .347)

  16. ANCOVA • ANCOVA: a specialized form of ANOVA that is used when an investigator wishes to remove the effects of a variable that is known to influence the dependent variable but is not the subject of the current experiment and analysis.

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