Statistics and Research Design for the DNP Project

Christi D. Doherty, DNP, MSN, RNC-OB, CNE, CHSE, CDP, Associate Professor, Nursing, American Sentinel University, Denver, CO

Kris Skalsky, EdD, MSNEd, RN, Professor, American Sentinel University, Denver, CO  

978-1-60595-384-7, January 2021, 332 pages, 6×9, Softcover book

  • Provides a clear and methodical guide to addressing the research design and statistics mastery specifically for the DNP project
  • Concepts are presented in a highly readable and easy to understand manner
  • Explains how to analyze and present data collected throughout the DNP project
  • Includes concrete, nursing practice examples which are consistently threaded through the book
  • Content directly aligns with the AACN DNP Essentials

This concise guide provides a comprehensive yet easy-to-understand guide to statistical analysis, specifically focused on the requirements for the final DNP project. The inclusion of concrete examples connected to nursing practice allows for a thorough understanding of the power of statistics in the assessment and evaluation of clinical guidelines, quality improvement processes, and a multitude of implementation science initiatives. Numerous charts and tables are included to reinforce the material.

Preface
Acknowledgments
Introduction

Chapter 1. Research Design

  • The Quantitative Approach
  • The Qualitative Research Approach
  • Mixed-Method Approach
  • Delphi Approach

Chapter 2. Sampling

  • Probability Sampling
  • Non-Probability Sampling
  • Sample Size
  • Type I and Type II Errors
  • A Priori Analysis

Chapter 3. Project Variables

  • Types of Research Variables
  • Variable Measurement

Chapter 4. Codebook

  • Data Coding
  • Data Entry
  • Data Manipulation
  • Qualitative Coding
  • Qualitative Software

Chapter 5. Choosing the Right Statistic

  • Chi-Square
  • Partial Correlation
  • Pearson’s Correlation/Spearman’s Rho
  • Multiple Regression
  • Independent Samples T-Test/Mann Whitney U Test
  • Paired Samples T-Test/Wilcoxon Signed Rank Test
  • One-Way Between Groups Analysis of Variance/Kruskalwallis Test
  • Two-Way Between Groups Analysis of Variance
  • Mixed Between-Within Analysis of Variance
  • Multivariate Analysis of Variance
  • Analysis of Covariance
  • Parametric Assumptions
  • Independence of Observations
  • Random Sampling
  • Level of Measurement
  • Homogeneity of Variance
  • Sample Size
  • Missing Data
  • Outliers
  • Type I and Type II Errors
  • Effect Size
  • Descriptive Statistics
  • Frequency
  • Percentage
  • Reliability and Validity Testing

Chapter 6. Statistics to Explore Relationships

  • Pearson Product-Moment Correlation
  • Spearman Rank Order Correlation
  • Partial Correlation

Chapter 7. Statistics Used to Predict Outcomes

  • Regression Statistical Assumptions
  • Standard Multiple Regression
  • Hierarchical Multiple Regression
  • Logistic Regression

Chapter 8. Statistics Used to Compare Groups: Nonparametric Tests

  • Nonparametric Statistics
  • McNemar’s Test
  • Cochran’s Q Test
  • Kappa Measure of Agreement
  • Mann-Whitney U Test
  • Wilcoxon Signed Rank Test
  • Kruskal-Wallis Test
  • Friedman Test

Chapter 9. Statistics Used to Compare Groups: Parametric Tests

  • Parametric Statistics
  • Independent Samples T-Test
  • Paired Samples T-Test

Chapter 10. Statistics Used to Determine Variances Among Groups

  • One-Way Analysis of Variance
  • One-Way Between Groups Analysis of Variance (ANOVA) with Planned Comparisons
  • One-Way Repeated Measures Analysis of Variance
  • Two-Way Between Groups Analysis of Variance (ANOVA)

Chapter 11. Advanced ANOVA Statistics

  • Mixed Between-Within Subjects Analysis of Variance (ANOVA)
  • Multivariate Analysis of Variance
  • One-Way Analysis of Covariance
  • Two-Way Analysis of Covariance

Appendix I: About the Skalsky Clinical Judgment Scale
Glossary of Terms
References
Index

 

Statistics and Research Design for the DNP Project (Entire eBook)
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Chapter 1: Research Design
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Chapter 2: Sampling
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Chapter 3: Project Variables
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Chapter 4: Codebook
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Chapter 5: Choosing the Right Statistic
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Chapter 6: Statistics to Explore Relationships
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Chapter 7: Statistics Used to Predict Outcomes
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Chapter 8: Statistics Used to Compare Groups: Nonparametric Tests
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Chapter 9: Statistics Used to Compare Groups: Parametric Tests
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Chapter 10: Statistics Used to Determine Variances Among Groups
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Chapter 11: Advanced ANOVA Statistics
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