Testing Statistical Hypotheses of Equivalence and Noninferiority

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A01=Stefan Wellek
advanced biostatistics
alternative
Author_Stefan Wellek
Bayesian Test
Bayesian tests
bioequivalence
Bioequivalence Assessment
Category=PBT
clinical trial statistics
Common Unknown Variance ?2
Common Unknown Variance Σ2
Critical Interval
Cumulative Distribution Function
Data Set
Distribution Functions
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Equivalence Hypothesis
Equivalence Interval
Equivalence Margin
Equivalence Range
Equivalence Test
equivalence testing
equivalence testing in clinical research
goodness-of-fit tests
hypothesis
inclusion
Intersection Union Principle
interval
Interval Inclusion
Interval Inclusion Test
medical data analysis
multivariate hypothesis testing
noninferiority testing
nonparametric tests
Nonrandomized Version
Null Alternative
Null Hypothesis
Null Hypothesis H1
Objective Bayesian Approach
probability
problem
R programming for statistics
region
rejection
Rejection Probability
Rejection Region
SAS Macro
Simulated Rejection Probabilities
statistical hypothesis testing
tests
treatment comparison methods
two-sided equivalence
UMPU Test

Product details

  • ISBN 9781439808184
  • Weight: 748g
  • Dimensions: 156 x 234mm
  • Publication Date: 24 Jun 2010
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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While continuing to focus on methods of testing for two-sided equivalence, Testing Statistical Hypotheses of Equivalence and Noninferiority, Second Edition gives much more attention to noninferiority testing. It covers a spectrum of equivalence testing problems of both types, ranging from a one-sample problem with normally distributed observations of fixed known variance to problems involving several dependent or independent samples and multivariate data. Along with expanding the material on noninferiority problems, this edition includes new chapters on equivalence tests for multivariate data and tests for relevant differences between treatments. A majority of the computer programs offered online are now available not only in SAS or Fortran but also as R scripts or as shared objects that can be called within the R system.

This book provides readers with a rich repertoire of efficient solutions to specific equivalence and noninferiority testing problems frequently encountered in the analysis of real data sets. It first presents general approaches to problems of testing for noninferiority and two-sided equivalence. Each subsequent chapter then focuses on a specific procedure and its practical implementation. The last chapter describes basic theoretical results about tests for relevant differences as well as solutions for some specific settings often arising in practice. Drawing from real-life medical research, the author uses numerous examples throughout to illustrate the methods.

Stefan Wellek is a professor of biostatistics at the University of Heidelberg and head of the Department of Biostatistics at the Central Institute of Mental Health in Mannheim, Germany.

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