Confidence Intervals for Proportions and Related Measures of Effect Size

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A01=Robert Gordon Newcombe
advanced effect size estimation
Agresti Coull Interval
Author_Robert Gordon Newcombe
Binomial Proportion
biostatistics methods
Category=JMB
Category=PBT
Category=PS
CI
Clopper Pearson Interval
Clopper Pearson Method
Confidence Interval Methods
confidence intervals
confidence intervals in the health and social sciences
Confidence Region
Continuity Correction
Coverage Probability
criteria for optimality
Distal Non-coverage
Effect Size Measure
effect size measures
epidemiological research tools
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
eq_society-politics
hypothesis testing techniques
Independent Proportions
Interval Width
medical data analysis
methods for calculating confidence intervals for proportions
Mid-p Interval
non-coverage
Non-coverage Probabilities
Noncoverage Probability
nonparametric statistics
odds
Pa Ce
parameter
Parameter Space Points
point and interval estimates
points
probability
ratio
score
Score Interval
Sentinel Node
Single Proportion
space
Standardised Difference
statistical inference
statistical inference applications
wald
Wald Interval
wilson
Wilson Interval
Wilson Score Interval

Product details

  • ISBN 9780367576707
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Jun 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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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 Mann-Whitney 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 user-friendly Excel spreadsheets for download at www.crcpress.com, enabling you to easily apply the methods to your own empirical data.

Robert G. Newcombe is a professor in the Institute of Primary Care and Public Health at Cardiff University School of Medicine, where he teaches medical statistics and epidemiology and is involved in medical and dental research. Dr. Newcombe is a member of the editorial board of Statistical Methods in Medical Research and serves on the Cardiff & Vale Research Review Service and Wales Ambulance Service Trust Research & Development panels.

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