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Nonparametric Statistics for Health Care Research

Nonparametric Statistics for Health Care Research
Statistics for Small Samples and Unusual Distributions

Second Edition
Additional resources:

August 2015 | 472 pages | SAGE Publications, Inc

What do you do when you realize that the data set from the study that you have just completed violates the sample size or other requirements needed to apply parametric statistics? Nonparametric Statistics for Health Care Research was developed for such scenarios—research undertaken with limited funds, often using a small sample size, with the primary objective of improving client care and obtaining better client outcomes. Covering the most commonly used nonparametric statistical techniques available in statistical packages and on open-resource statistical websites, this well-organized and accessible Second Edition helps readers, including those beyond the health sciences field, to understand when to use a particular nonparametric statistic, how to generate and interpret the resulting computer printouts, and how to present the results in table and text format. 

Chapter 1: Overview of Nonparametric Statistics
Common Characteristics of Parametric Tests  
Development of Nonparametric Tests  
Characteristics of Nonparametric Statistics  
Use of Nonparametric Tests in Health Care Research  
Some Common Misperceptions About Nonparametric Tests  
Types of Nonparametric Tests  
Chapter 2: The Process of Statistical Hypothesis Testing
Choosing Between a Parametric and a Nonparametric Test  
Chapter 3: Evaluating the Characteristics of Data
Characteristics of Levels of Measurement  
Assessing the Normality of a Distribution  
Dealing With Outliers  
Data Transformation Considerations  
Examining Homogeneity of Variance  
Evaluating Sample Sizes  
Reporting Testing Assumptions and Violations in a Research Report  
Chapter 4: “Goodness-of-Fit” Tests
The Binomial Test  
The Chi-Square Goodness-of-Fit Test  
The Kolmogorov-Smirnov One-Sample Test  
The Kolmogorov-Smirnov Two-Sample Test  
Chapter 5: Tests for Two Related Samples: Pretest-Posttest Measures for a Single Sample
The McNemar Test  
The Sign Test  
The Wilcoxon Signed Ranks Test  
Chapter 6: Repeated Measures for More Than Two Time Periods or Matched Conditions
Cochran’s Q Test  
The Friedman Test  
Chapter 7: Tests for Two Independent Samples
Fisher’s Exact test  
The Chi-Square Test for Two Independent Samples  
The Wilcoxon-Mann-Whitney U test  
Chapter 8: Assessing Differences Among Several Independent Groups
The Chi-Square Test for k Independent Samples  
The Mantel-Haenszel Chi-Square Test for Trends  
The Median Test  
The Kruskal-Wallis One-Way ANOVA by Ranks  
The Two-Way ANOVA by Ranks  
Chapter 9: Tests of Association Between Variables
The Phi Coefficient  
Cramér’s V Coefficient  
The Kappa Coefficient  
The Point Biserial Correlation  
Chapter 10: Logistic Regression
The Logic of Logistic Regression  
The Odds Ratio and Relative Risk  
Simple Bivariate Logistic Regression  
Multiple Logistic Regression  


This is a very easy to understand and use book that sheds light on nonparametric statistics. It has been a welcome addition to my stat resources!

Dr Michele M Wood
Health Science Dept., California St Univ-Fullerton
October 13, 2016

2nd Ed of a classic text for nonparametric stats in health care book available for this topic

Dr Kathleen Nora Dunemn
School Of Nursing, Univ Of Northern Colorado
March 19, 2015

Better as a supplemental textbook and not as a primary textbook.

Dr Gary Hackbarth
Management Dept, Valdosta State University
January 31, 2015

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ISBN: 9781452281964