Statistics and Data Analysis for Nursing Research

Description

Statistics and Data Analysis for Nursing Research 2e

Denise F. Polit, PdD

Users praised the accessibility, clarity, and user-friendliness of the first edition of Statistics and Data Analysis for Nursing Research. Now, the push for evidence-based practice (EBP) in nursing and health care makes this new edition timely.  The style and practical emphasis of the first edition have been retained, but important innovations have also been introduced, making it even easier to embark on a professional pathway that includes statistical analysis. As in the first edition, the content includes descriptive statistics, bivariate inferential statistics, and many widely-used multivariate statistics. It assumes virtually no prior knowledge of statistics.

NEW TO THIS EDITION

• Emphasis on evidence-based practice

·        SPSS Version 16.0 was used to generate output for the book

·        Missing Values are demystified

·        Factor Analysis content is expanded

·        Power Analysis methods are explained

Additional Resources:

Online Applications Manual for Statistics and Data Analysis for Nursing Research 2e

Online resource for Application Exercises with three complete data sets, compatible with SPSS, as well as additional resources.

www.pearsonhighered.com/polit

[Pearson Education]

Chapter Chapter Title

1 Introduction to Data Analysis in an Evidence-Based Practice Environment

2 Frequency Distribution: Tabulating and Displaying Data

3 Central Tendency, Variability, and Location

4 Correlation, Crosstabulation, and Risk Indexes: Describing Relationships:

5 Statistical Inference

6 t Tests

7 Analysis of Variance

8 Chi Square and Other Nonparametric Tests

9 Correlation and Simple Regression

10 Multiple Regression

11 Analysis of Covariance, MANOVA, and Other Related Multivariate Techniques

12 Using Logistic Regression

13 Factor Analysis and Internal Consistency Reliability Analysis

14 Missing Values

Appendix A: Theoretical Probability Tables

Appendix B: Power Analysis/Effect Size Tables

Appendix C: Tips on Handling Missing Data

Appendix D: Answers for Selected Exercises

The second edition of Statistics and Data Analysis for Nursing, uses a conversational style to teach students how to use statistical methods and procedures to analyse research findings. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to “clean” data, and how to work around missing data, is discussed.

Susan Norwood is a professor of nursing at Saint Anselm College in Manchester, New Hampshire, where she teaches critical care nursing, professional nursing, ethics, and understanding suffering. She received her bachelor’s degree from the University of Massachusetts, Amherst, her master’s degree from Boston College, and her PhD from Union Institute and University in Cincinnati, Ohio. She has been a practicing critical care nurse for over 30 years and a member of the American Association of Critical Care Nurses for nearly as long. She has published and presented in the areas of critical care nursing, nursing ethics, nursing history, suffering experienced by patients as well as health care providers, and conflict among members of the health care team.

• Research Examples – are used to illustrate key points in the text and to stimulate students’ thinking about research questions and analytic options.
• Clear, “user friendly” style – used in this book was designed to make the content digestible and nonintimidating. Concepts are introduced carefully and systematically, difficult ideas are presented clearly.
• Specific practical tips on performing analyses – every chapter includes several tips for applying the chapter’s lessons to real-life situations. 
• Guidance on presenting statistical results – indicates what information to report in the text versus in tables and figures, and includes exemplary tables that can be used as templates for many statistical analyses.
• Exercises – Student exercises are included at the end of every chapter.
• Power Point slides – offer a more dynamic and colourful way to review textbook content, and also provide explicit guidance for undertaking SPSS analyses.
• Further aids to student learning – bolded terms when new concepts are introduced; succinct, bulleted summaries at the end of each chapter; and tables and figures that provide examples and graphic materials in support of the text discussion.   

The second edition of Statistics and Data Analysis for Nursing, uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Readers are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. Special focus is given to quantitative methods. Other features include management of data, how to “clean” data, and how to work around missing data. New to this edition are

updated research examples utilizinging examples from an international mix of studies published by nurse researchers in 2006-2009.

New to This Edition

• UPDATED! –  Research Examples utilizinging examples from an international mix of studies published by nurse researchers in 2006-2009 

• Emphasis on Evidence-Based Practice
  • Virtually every chapter in this edition offers content on evaluating the reliability of statistical results (as communicated through p values), the precision of statistical results (as communicated through confidence intervals), and the magnitude of results (as communicated through effect size indexes). Information on effect size is especially important, given its crucial role in meta-analyses.
• SPSS Version 16.0
  • Computer output from statistical analyses is presented throughout the book, together with guidance on how to read the output. Three SPSS datasets are offered with the book on the book’s website.
• Missing Values
  • The final chapter of the book covers strategies for detecting patterns of missing values, and approaches to dealing with ensuing problems. State-of-the-art imputation techniques are discussed.
• Scale Development
  • In this edition, the chapter on factor analysis has been expanded, and a new section on evaluating internal consistency reliability has been added.
• Power Analysis
  • Approaches for doing a power analysis to estimate sample size needs have been expanded and greatly simplified in this edition.

Additional information