Description
Taylor & Francis Ltd Design And Analysis Of Cross Over Trials 3Rd Edition 2014 by Byron Jones, Michael G. Kenward
Design and Analysis of Cross-Over Trials is concerned with a specific kind of comparative trial known as the cross-over trial, in which subjects receive different sequences of treatments. Such trials are widely used in clinical and medical research, and in other diverse areas such as veterinary science, psychology, sports science, and agriculture.The first edition of this book was the first to be wholly devoted to the subject. The second edition was revised to mirror growth and development in areas where the design remained in widespread use and new areas where it had grown in importance. This new Third Edition:Contains seven new chapters written in the form of short case studies that address re-estimating sample size when testing for average bioequivalence, fitting a nonlinear dose response function, estimating a dose to take forward from phase two to phase three, establishing proof of concept, and recalculating the sample size using conditional powerEmploys the R package Crossover, specially created to accompany the book and provide a graphical user interface for locating designs in a large catalog and for searching for new designsIncludes updates regarding the use of period baselines and the analysis of data from very small trialsReflects the availability of new procedures in SAS, particularly proc glimmix Presents the SAS procedure proc mcmc as an alternative to WinBUGS for Bayesian analysisComplete with real data and downloadable SAS code, Design and Analysis of Cross-Over Trials, Third Edition provides a practical understanding of the latest methods along with the necessary tools for implementation. List of FiguresList of TablesPreface to the Third EditionIntroductionWhat Is a Cross-Over Trial?With Which Sort of Cross-Over Trial Are We Concerned?Why Do Cross-Over Trials Need Special Consideration?A Brief HistoryNotation, Models, and AnalysisAims of This BookStructure of the BookThe 2x2 Cross-Over TrialIntroductionPlotting the DataAnalysis Using T-TestsSample Size CalculationsAnalysis of VarianceAliasing of EffectsConsequences of Preliminary TestingAnalyzing the ResidualsA Bayesian Analysis of the 2x2 TrialBayes Using ApproximationsBayes Using Gibbs SamplingUse of Baseline MeasurementsUse of CovariatesNonparametric AnalysisTesting 1 = 2Testing t1 =t2, Given that 1 = 2Testing 1 = 2, Given that 1 = 2Obtaining the Exact Version of the Wilcoxon Ranksum Test Using TablesPoint Estimate and Confidence Interval for =t1 t2 A More General Approach to Nonparametric TestingNonparametric Analysis of Ordinal DataAnalysis of a Multicenter TrialTests Based on Nonparametric Measures of AssociationBinary DataIntroductionMcNemar's TestThe Mainland-Gart TestFisher's Exact Version of the Mainland-Gart TestPrescott's TestHigher-Order Designs for Two TreatmentsIntroduction"Optimal" DesignsBalaam's Design for Two TreatmentsEffect of Preliminary Testing in Balaam's DesignThree-Period Designs with Two SequencesThree-Period Designs with Four SequencesA Three-Period Six-Sequence DesignWhich Three-Period Design to Use?Four-Period Designs with Two SequencesFour-Period Designs with Four SequencesFour-Period Designs with Six SequencesWhich Four-Period Design to Use?Which Two-Treatment Design to Use?Designing Cross-Over TrialsIntroductionVariance-Balanced DesignsDesigns with p = t Designs with p < t Designs with p > t Designs with Many PeriodsOptimality Results for Cross-Over DesignsWhich Variance-Balanced Design to Use? Partially Balanced Designs Comparing Test Treatments to a ControlFactorial Treatment Combinations Extending the Simple Model for Carry-Over Effects Computer Search Algorithms Analysis of Continuous DataIntroductionExample: INNOVO Trial: Dose-Response StudyFixed Subject Effects ModelIgnoring the Baseline MeasurementsAdjusting for Carry-Over EffectsRandom Subject Effects ModelRandom Subject EffectsRecovery of Between-Subject InformationSmall Sample Inference with Random EffectsMissing ValuesUse of Baseline MeasurementsIntroduction and ExamplesNotation and Basic ResultsPre-Randomization CovariatesPeriod-Dependent Baseline CovariatesBaselines as Response VariablesIncomplete DataAnalyses for Higher-Order Two-Treatment DesignsAnalysis for Balaam's DesignGeneral Linear Mixed ModelAnalysis of Repeated Measurements within PeriodsExample: Insulin MixturesCross-Over Data as Repeated MeasurementsAllowing More General Covariance Structures Robust Analyses for Two-Treatment Designs Higher-Order DesignsCase Study: An Analysis of a Trial with Many Periods Example: McNulty's Experiment McNulty's AnalysisFixed Effects Analysis Random Subject Effects and Covariance Structure Modeling the Period Effects Analysis of Discrete Data Introduction Modeling Dependent Categorical DataTypes of Model Binary Data: Subject Effect Models Dealing with the Subject Effects Conditional Likelihood Binary Data: Marginal Models Marginal Model Categorical Data Example: Trial on Patients with Primary Dysmenorrhea Types of Model for Categorical Outcomes Subject Effects Models Marginal Models Further Topics Count DataTime to Event DataIssues Associated with ScaleBioequivalence TrialsWhat Is Bioequivalence? Testing for Average BioequivalenceCase Study: Phase I Dose-Response Noninferiority TrialIntroductionModel for Dose Response Testing for NoninferiorityChoosing Doses for the Fifth PeriodAnalysis of the Design Post-Interim Case Study: Choosing a Dose-Response Model IntroductionAnalysis of Variance Dose-Response Modeling Case Study: Conditional PowerIntroduction Variance Spending Approach Interim Analysis of Sleep Trial Case Study: Proof of Concept Trial with Sample Size Re-EstimationIntroductionCalculating the Sample SizeInterim AnalysisData Analysis Case Study: Blinded Sample Size Re-Estimation in a Bioequivalence StudyIntroductionBlinded Sample Size Re-Estimation (BSSR) Example Case Study: Unblinded Sample Size Re-Estimation in a Bioequivalence Study That Has a Group Sequential Design Introduction Sample Size Re-Estimation in a Group Sequential Design Modification of Sample Size Re-Estimation in a Group Sequential Design Case Study: Various Methods for an Unblinded Sample Size Re-Estimation in a Bioequivalence StudyIntroductionMethodsExampleAppendix A: Least Squares EstimationCase 1Case 2Case 3BibliographyIndex