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

Second Edition
Additional resources:


July 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

 

Supplements

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 research....best 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
Key features

NEW TO THIS EDITION:

  • New coverage of confidence intervals, estimations/evaluations of effect sizes, useful Internet resources, and in-depth coverage of additional nonparametric multivariate statistics
  • New Test Your Knowledge, Points to Remember, and Computer Exercises at the end of chapters
  • Tables of distributions added to an appendix for the most commonly used nonparametric statistics (normal distribution, chi square distribution, etc.)
  • Copies of the syntax and datasets for both SPSS and SAS available on a student study site

 KEY FEATURES:

  • A general overview of nonparametric statistics, as well as a review of statistical hypothesis testing and the characteristics of data to help readers build a foundational understanding
  • A wide variety of tests explored, including "goodness-of-fit" tests, tests for two related samples, repeated measures for multiple time periods or matched conditions, etc.

Sample Materials & Chapters

Chapter 3

Chapter 5


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