Designing Experiments and Analyzing Data: A Model Comparison Perspective, Third Edition – Ebook PDF Version

Designing Experiments and Analyzing Data: A Model Comparison Perspective, Third Edition – Ebook PDF Version – Digital Instant Dowload.

Product details:

• ISBN-10 ‏ : ‎ 1138892289
• ISBN-13 ‏ : ‎ 978-1138892286
• Author: Scott E. Maxwell, Harold D. Delaney, Ken Kelley

Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis that is appropriate for a wide variety of designs, which allows for the introduction of more complex topics that are generally omitted from other books.

Table contents:

Part I: Conceptual Bases of Experimental Design and Analysis

1. The Logic of Experimental Design and Analysis

2. Drawing Valid Inferences from Experiments

Part II: Model Comparisons for Between-Subjects Designs

3. Introduction to Model Comparisons: One-Way Between-Subjects Designs

4. Individual Comparisons of Means

5. Testing Several Contrasts: The Multiple-Comparisons Problem

6. Trend Analysis

7. Two-Way Between-Subjects Factorial Designs

8. Higher Order Between-Subjects Factorial Designs

9. Designs with Covariates: ANCOVA and Blocking Extensions

10. Designs with Random or Nested Factors

Part III: Model Comparisons for Designs Involving Within-Subjects Factors

11. One-Way Within-Subjects Designs: Univariate Approach

12. Higher-Order Designs with Within-Subjects Factors: Univariate Approach

13. One-Way Within-Subjects Designs: Multivariate Approach

14. Higher Order Designs with Within-Subjects Factors: The Multivariate Approach Part IV: Mixed-Effects Models

15. An Introduction to Mixed-Effects Models: Within-Subjects Designs

16. An Introduction to Mixed-Effect Models: Nested Designs