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ISBN10: 0071822445 | ISBN13: 9780071822442

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A textbook on the use of advanced statistical methods in healthcare sciences Primer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods. The book has been acclaimed for its user-friendly style that makes complicated material understandable to readers who do not have an extensive math background. The text is packed with learning aids that include chapter-ending summaries and end-of-chapter problems that quickly assess mastery of the material. Examples from biological and health sciences are included to clarify and illustrate key points. The techniques discussed apply to a wide range of disciplines, including social and behavioral science as well as health and life sciences. Typical courses that would use this text include those that cover multiple linear regression and ANOVA. Four completely new chapters Completely updated software information and examples
1. Why Do Multivarite Analysis?
2. Understanding Simple Linear Regression
3. Regression with Two or More Independent Variables
4. Do the Data Fit the Assumptions?
5. Multicollinearity and What to Do About it?
6. Selecting the "Best" Regression Model
7. Missing Data (NEW)
8. One-Way Analysis of Variance
9. Two-Way Analysis of Variance
10. Nonlinear Regression (NEW)
11. Repeated Measures
12. Mixing Continuous and Categorical Variables: Analysis of Covariance
13. Survival Analysis (NEW)
14. Logistic Regression (NEW)
Appendices
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