Munro's Statistical Methods for Health Care Research / Edition 6

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Overview

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.

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Editorial Reviews

Doody's Review Service
Reviewer: James C. Torner, PhD, MS (University of Iowa College of Public Health)
Description: This book on the structure, requirements, and use of statistical methods in healthcare research details the essentials needed for data acquisition and analysis, from description to complex interrelationships between variables. It uses SPSS as a tool for performing analysis and demonstrating methods. The previous edition was published in 2005.
Purpose: The purpose is to provide background and details on developing a research question, collecting data, describing data, and analyzing associations between variables. The book covers a broad set of topics that researchers need to consider in producing analysis suitable for reporting or publication, describing the methods in an accessible and useful format.
Audience: It is written at a level appropriate for a variety of researchers and practitioners. Chapters present the fundamentals, assumptions, specific methods, examples, and samples of SPSS output. Most students and practitioners should be able to understand the book without significant preparation or comprehension of statistics. This edition is based on the past version, but has been enhanced. The authors have experience in public health education and have recruited a credible supporting group of contributors.
Features: The three sections of the book cover obtaining and understanding data, analysis of data, and model building and presenting data. It has a logical flow from the proposal and research question to describing, analyzing, and modeling data and concludes with chapter on shaping and publishing. The examples help understanding, and plenty of questions assist and test readers' grasp of the concepts. The tables are useful for demonstrating methods and graphs facilitate understanding. Readers should be a user of SPSS to take full advantage of what this book offers. The book also includes additional online features.
Assessment: Although similar to other introductory statistical methods books, this one has chapters on regression methods, factor analysis, path analysis, and structural equation methods that go beyond most of them. This can provide a useful educational resource for beginning students, particularly those who use SPSS.
From The Critics
Reviewer: James C. Torner, MS, PhD (University of Iowa College of Public Health)
Description: This book on the structure, requirements, and use of statistical methods in healthcare research details the essentials needed for data acquisition and analysis, from description to complex interrelationships between variables. It uses SPSS as a tool for performing analysis and demonstrating methods. The previous edition was published in 2005.
Purpose: The purpose is to provide background and details on developing a research question, collecting data, describing data, and analyzing associations between variables. The book covers a broad set of topics that researchers need to consider in producing analysis suitable for reporting or publication, describing the methods in an accessible and useful format.
Audience: It is written at a level appropriate for a variety of researchers and practitioners. Chapters present the fundamentals, assumptions, specific methods, examples, and samples of SPSS output. Most students and practitioners should be able to understand the book without significant preparation or comprehension of statistics. This edition is based on the past version, but has been enhanced. The authors have experience in public health education and have recruited a credible supporting group of contributors.
Features: The three sections of the book cover obtaining and understanding data, analysis of data, and model building and presenting data. It has a logical flow from the proposal and research question to describing, analyzing, and modeling data and concludes with chapter on shaping and publishing. The examples help understanding, and plenty of questions assist and test readers' grasp of the concepts. The tables are useful for demonstrating methods and graphs facilitate understanding. Readers should be a user of SPSS to take full advantage of what this book offers. The book also includes additional online features.
Assessment: Although similar to other introductory statistical methods books, this one has chapters on regression methods, factor analysis, path analysis, and structural equation methods that go beyond most of them. This can provide a useful educational resource for beginning students, particularly those who use SPSS.
From The Critics
Reviewer: James C. Torner, MS, PhD (University of Iowa College of Public Health)
Description: This book on the structure, requirements, and use of statistical methods in healthcare research details the essentials needed for data acquisition and analysis, from description to complex interrelationships between variables. It uses SPSS as a tool for performing analysis and demonstrating methods. The previous edition was published in 2005.
Purpose: The purpose is to provide background and details on developing a research question, collecting data, describing data, and analyzing associations between variables. The book covers a broad set of topics that researchers need to consider in producing analysis suitable for reporting or publication, describing the methods in an accessible and useful format.
Audience: It is written at a level appropriate for a variety of researchers and practitioners. Chapters present the fundamentals, assumptions, specific methods, examples, and samples of SPSS output. Most students and practitioners should be able to understand the book without significant preparation or comprehension of statistics. This edition is based on the past version, but has been enhanced. The authors have experience in public health education and have recruited a credible supporting group of contributors.
Features: The three sections of the book cover obtaining and understanding data, analysis of data, and model building and presenting data. It has a logical flow from the proposal and research question to describing, analyzing, and modeling data and concludes with chapter on shaping and publishing. The examples help understanding, and plenty of questions assist and test readers' grasp of the concepts. The tables are useful for demonstrating methods and graphs facilitate understanding. Readers should be a user of SPSS to take full advantage of what this book offers. The book also includes additional online features.
Assessment: Although similar to other introductory statistical methods books, this one has chapters on regression methods, factor analysis, path analysis, and structural equation methods that go beyond most of them. This can provide a useful educational resource for beginning students, particularly those who use SPSS.
Read More Show Less

Product Details

  • ISBN-13: 9781451187946
  • Publisher: Lippincott Williams & Wilkins
  • Publication date: 9/6/2012
  • Edition description: Revised Reprint
  • Edition number: 6
  • Pages: 576
  • Sales rank: 118,540
  • Product dimensions: 7.00 (w) x 8.90 (h) x 1.30 (d)

Table of Contents

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 Friedman's 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 Diagnostic

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 Dunn's Q for Nonparametric Multiple Comparison Testing
Appendix I: Exact Distribution of the Friedman's χ2 for the Friedman'Xs 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

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