Munros Statistical Methods for Health Care Research

重量：0.8kg 　頁數：566    裝訂：平裝 　開數：22.8*17.8 　印刷：雙色

Description

This text provides students with a solid foundation for understanding data analysis and specific statistical techniques. Focusing on the most current and frequently used statistical methods in today's health care literature, the book covers essential material for a variety of program levels including in-depth courses beyond the basic statistics course. Well-organized, clear text discussions and great learning tools help students overcome the complexities and fully comprehend the concepts of this often intimidating area of study.

Feature
* The book covers essential material for a variety of program levels including in-depth courses beyond the basic statistics course.
* New author team based the book on the organizational framework that Barbara Hazard Munro developed, which a generation of students and health care providers have used.
* Included are chapter-by-chapter sections on the research question, examples from the literature, types of data required, assumptions, details of the specific technique under discussion, and a fully worked out example of how to compute the statistic both by hand and with IBM SPSS.
* The software that is referenced has been updated to SPSS 18.
* Expanded discussions of nonparametric (distribution free) statistics and the chi-square statistic are included.
* The book is organized into three sections: Section 1 focuses on obtaining and understanding your data, Section 2 focuses on analyzing the data (largely with bivariate statistics), and Section 3 focuses on model building and presenting your data.

Table of Contents
Preface Section 1: Obtaining and Understanding Data Chapter 1: Using Research and Statistics in Health Care Chapter 2: Descriptive Statistics: Getting to Know the Data Chapter 3: Key Principles of Statistical Inference Chapter 4: Hypothesis Testing with Inferential Statistics Section 2: Analyzing the Data Chapter 5: Measuring the Differences Between the Means Two Unrelated Group Means: Independent t-tests and Mann-Whitney U-tests Chapter 6: Measuring the Differences Between the Means of Two Related Groups: Paired t-tests and Wilcoxon Matched Pairs tests Chapter 7: Measuring the Differences Between the Means of Three or More Unrelated Groups: One -Way ANOVAs and the Kruskal-Wallis H-tests Chapter 8: Differences Among the Means of Three or More Unrelated Groups Defined by Two or More Independent Variables: N-Way ANOVA Chapter 9: Comparing the Means of Three or More Related Groups: Repeated Measures ANOVA and FriedmanÆs ANOVA by Rank Chapter 10: Analysis of Covariance (ANCOVA) Chapter 11: Measuring the Association of two Variables: Pearson and Spearman Correlation Chapter 12: Examining Cross tabulations: The Chi-square Statistic and The McNemar Test Section 3: Model Building and Presentation Chapter 13: Logistic Regression Chapter 14: Linear Regression and Regression Diagnostics Chapter 15: Factor Analysis Chapter 16: Path Analysis Chapter 17: Structural Equation Modeling Chapter 18: Writing for Presentation and Publication Appendices and other end of book items Glossary Appendix A: Entering Data into SPSS Appendix B: Percent of Total Area of Normal Curve Between a z-score and the Mean Appendix C: Distribution of t Appendix D: Critical Values of the U-statistic Appendix E: Critical Values of the Wilcoxon Signed-Rank Statistic Appendix F: The 5% and 1% Points for the Distribution of F Appendix G: Critical Values of H for the Kruskal-Wallis ANOVA by Rank Appendix H: Critical Values of DunnÆs Q for Nonparametric Multiple Comparison Testing Appendix I: Exact Distribution of the FriedmanÆs χ2 for the FriedmanÆs ANOVA by Rank Comparing Three Related Groups Appendix J: Critical Values of the Pearson Correlation Coefficient Appendix K: Critical Value of the Spearman Correlation Coefficient Appendix L: Distribution of χ2  Probability Bibliography Index