Nonparametric Statistics for Health Care Research

Marjorie A. Pett, MStat, DSW, is a Research Professor in the College of Nursing at the University of Utah, Salt Lake City, Utah, having been on the faculty since 1980. By her own admission, she is a “collector” of academic degrees: BA (Brown University), MS in sociology (University of Stockholm, Sweden), MSW (Smith College), DSW (University of Utah), and MStat (Biostatistics) (University of Utah). Dr. Pett has a strong commitment to facilitating the practical application of statistics in the social, behavioral, and biological sciences, especially among practitioners in health care settings. She has designed and taught graduate courses to students from a variety of disciplines at the beginning and advanced levels, including research design and data management, parametric and nonparametric statistics, biostatistics, multivariate statistics, instrument development, and factor analysis. She has tried to approach the teaching of statistics with humor and from a clinician’s perspective and has been the recipient of several distinguished teaching awards both at the College and University levels.Her most recent research interests include the development of client-centered assessment tools and interventions to evaluate and enhance health-related quality of life (HRQoL) for persons with intellectual disabilities. She is the author of numerous research articles and chapters, and is an author of the Sage publication, Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research. When not engaged in research, writing, or teaching, Marge is a (now retired) state soccer referee, devotee of tennis, an avid (high handicap) golfer, student of Italian and French, reader of mystery novels, grandmother to three, mother to two, and wife to (only) one.

• Chapter 1: Overview of Nonparametric StatisticsCommon Characteristics of Parametric TestsDevelopment of Nonparametric TestsCharacteristics of Nonparametric StatisticsUse of Nonparametric Tests in Health Care ResearchSome Common Misperceptions About Nonparametric TestsTypes of Nonparametric TestsChapter 2: The Process of Statistical Hypothesis TestingChoosing Between a Parametric and a Nonparametric TestChapter 3: Evaluating the Characteristics of DataCharacteristics of Levels of MeasurementAssessing the Normality of a DistributionDealing With OutliersData Transformation ConsiderationsExamining Homogeneity of VarianceEvaluating Sample SizesReporting Testing Assumptions and Violations in a Research ReportChapter 4: “Goodness-of-Fit” TestsThe Binomial TestThe Chi-Square Goodness-of-Fit TestThe Kolmogorov-Smirnov One-Sample TestThe Kolmogorov-Smirnov Two-Sample TestChapter 5: Tests for Two Related Samples: Pretest-Posttest Measures for a Single SampleThe McNemar TestThe Sign TestThe Wilcoxon Signed Ranks TestChapter 6: Repeated Measures for More Than Two Time Periods or Matched ConditionsCochran’s Q TestThe Friedman TestChapter 7: Tests for Two Independent SamplesFisher’s Exact testThe Chi-Square Test for Two Independent SamplesThe Wilcoxon-Mann-Whitney U testChapter 8: Assessing Differences Among Several Independent GroupsThe Chi-Square Test for k Independent SamplesThe Mantel-Haenszel Chi-Square Test for TrendsThe Median TestThe Kruskal-Wallis One-Way ANOVA by RanksThe Two-Way ANOVA by RanksChapter 9: Tests of Association Between VariablesThe Phi CoefficientCramér’s V CoefficientThe Kappa CoefficientThe Point Biserial CorrelationChapter 10: Logistic RegressionThe Logic of Logistic RegressionThe Odds Ratio and Relative RiskSimple Bivariate Logistic RegressionMultiple Logistic Regression