Confidence intervals for proportions and related measures of effect size
 Responsibility
 Robert G. Newcombe.
 Imprint
 Boca Raton, FL : CRC Press, c2013.
 Physical description
 xxvii, 442 p. : ill. ; 24 cm.
 Series
 Chapman & Hall/CRC biostatistics series (Unnumbered)
Access
Available online
Science Library (Li and Ma)
Stacks
Call number  Status 

QH323.5 .N49 2013  Unknown 
More options
Creators/Contributors
 Author/Creator
 Newcombe, Robert G.
Contents/Summary
 Bibliography
 Includes bibliographical references and index.
 Contents

 Hypothesis Tests and Confidence Intervals Sample and Population Hypothesis Testing and Confidence Intervals: The Fundamentals Why Confidence Intervals Are Generally More Informative Than pValues Measures of Effect Size When Are Point and Interval Estimates Less Helpful? Frequentist, Bayesian and Likelihood Intervals Just What Is Meant by the Population? The Unit of Data Sample Size Planning Means and Their Differences Confidence Interval for a Mean Confidence Interval for the Difference between Means of Independent Samples Confidence Interval for the Difference between Two Means Based on Individually Paired Samples Scale Transformation NonParametric Methods The Effect of Dichotomising Continuous Variables Confidence Intervals for a Simple Binomial Proportion Introduction The Wald Interval Boundary Anomalies Alternative Intervals Algebraic Definitions for Several Confidence Intervals for the Binomial Proportion Implementation of Wilson Score Interval in MS Excel Sample Size for Estimating a Proportion Criteria for Optimality How Can We Say Which Methods Are Good Ones? Coverage Expected Width Interval Location Computational Ease and Transparency Evaluation of Performance of Confidence Interval Methods Introduction An Example of Evaluation Approaches Used in Evaluations for the Binomial Proportion The Need for Illustrative Examples Intervals for the Poisson Parameter and the Substitution Approach The Poisson Distribution and Its Applications Confidence Intervals for the Poisson Parameter and Related Quantities Widening the Applicability of Confidence Interval Methods: The Substitution Approach Difference between Independent Proportions and the SquareandAdd Approach The Ordinary 2 x 2 Table for Unpaired Data The Wald Interval The SquareandAdd or MOVER Approach Other WellBehaved Intervals for the Difference between Independent Proportions Evaluation of Performance Number Needed to Treat Bayesian Intervals Interpreting Overlapping Intervals Sample Size Planning Difference between Proportions Based on Individually Paired Data The 2 x 2 Table for Paired Binary Data Wald and Conditional Intervals Intervals Based on Profile Likelihoods ScoreBased Intervals Evaluation of Performance Methods for Triads of Proportions Introduction Trinomial Variables on Equally Spaced Scales Unordered Trinomial Data: Generalising the TailBased pValue to Characterise Conformity to Prescribed Norms A Ternary Plot for Unordered Trinomial Data Relative Risk and Rate Ratio A Ratio of Independent Proportions Three Effect Size Measures Comparing Proportions Ratio Measures Behave Best on a Log Scale Intervals Corresponding to the Empirical Estimate Infinite Bias in Ratio Estimates Intervals Based on Mesially Shrunk Estimated Risks A Ratio of Proportions Based on Paired Data A Ratio of Sizes of Overlapping Groups A Ratio of Two Rates Implementation in MS Excel The Odds Ratio and Logistic Regression The Rationale for the Odds Ratio Disadvantages of the Odds Ratio Intervals Corresponding to the Empirical Estimate Deterministic Bootstrap Intervals Based on Median Unbiased Estimates Logistic Regression An Odds Ratio Based on Paired Data Implementation Screening and Diagnostic Tests Background Sensitivity and Specificity Positive and Negative Predictive Values TradeOff between Sensitivity and Specificity: The ROC Curve Simultaneous Comparison of Sensitivity and Specificity between Two Tests Widening the Applicability of Confidence Interval Methods: The Propagating Imprecision Approach Background The Origin of the PropImp Approach The PropImp Method Defined PropImp and MOVER Wilson Intervals for Measures Comparing Two Proportions Implementation of the PropImp Method Evaluation The Thorny Issue of Monotonicity Some Issues Relating to MOVER and PropImp Approaches Several Applications of the MOVER and PropImp Approaches Introduction AdditiveScale Interaction for Proportions Radiation Dose Ratio Levin's Attributable Risk Population Risk Difference and Population Impact Number Quantification of Copy Number Variations Standardised Mortality Ratio Adjusted for Incomplete Data on Cause of Death RD and NNT from Baseline Risk and Relative Risk Reduction Projected Positive and Negative Predictive Values Estimating Centiles of a Gaussian Distribution Ratio Measures Comparing Means Winding the Clock Back: The Healthy Hearts Study Grass Fires Incremental RiskBenefit Ratio Adjustment of Prevalence Estimate Using Partial Validation Data Comparison of Two Proportions Based on Overlapping Samples Standardised Difference of Proportions Generalised MannWhitney Measure Absolute and Relative Effect Size Measures for Continuous and Ordinal Scales The Generalised MannWhitney Measure Definitions of Eight Methods Illustrative Examples Evaluation Results of the Evaluation Implementation in MS Excel Interpretation Generalised Wilcoxon Measure The Rationale for the Generalised Wilcoxon Measure psi Paired and Unpaired Effect Size Measures Compared Estimating the Index psi Development of a Confidence Interval for psi Evaluation of Coverage Properties: Continuous Case Results of Evaluation for the Continuous Case Coverage Properties for Discrete Distributions Discussion References Appendices.
 (source: Nielsen Book Data)9781439812785 20160610
 Publisher's Summary
 Confidence Intervals for Proportions and Related Measures of Effect Size illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests. The book provides you with a deep understanding of what happens when these statistical methods are applied in situations far removed from the familiar Gaussian case. Drawing on his extensive work as a statistician and professor at Cardiff University School of Medicine, the author brings together methods for calculating confidence intervals for proportions and several other important measures, including differences, ratios, and nonparametric effect size measures generalizing MannWhitney and Wilcoxon tests. He also explains three important approaches to obtaining intervals for related measures. Many examples illustrate the application of the methods in the health and social sciences. Requiring little computational skills, the book offers userfriendly Excel spreadsheets for download at www.crcpress.com, enabling you to easily apply the methods to your own empirical data.
(source: Nielsen Book Data)9781439812785 20160610
Subjects
Bibliographic information
 Publication date
 2013
 Series
 Chapman & Hall/CRC biostatistics series
 ISBN
 9781439812785 (hardback : alk. paper)
 1439812780 (hardback : alk. paper)