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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

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
November 28, 2015

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
October 22, 2015

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

Dr Gary Hackbarth
Management Dept, Valdosta State University
October 3, 2015

Sample Materials & Chapters

Chapter 3

Chapter 5

For instructors

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