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These chapters are understandable for a reader who wants to study multiple testing methods beyond the post-hoc tests presented in a course on design of experiments The final chapter provides an accessible description of problems in testing data from microarrays. Journal of Biopharmaceutical Statistics: If you are a statistician in the pharmaceutical industry looking for a comprehensive description of multiple testing in a clinical trial, this book is for you. Each of the main sources of multiplicity in clinical trials, such as several doses, endpoints, interim analyses etc.

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On the way, you will encounter dose-finding, adaptive designs and even microarray experiments. The book can undoubtedly be of value to wider groups-in fact we would rank it as the best book on multiplicity given its up-to-date material Mohammad Huque U. This chapter gives a broad introduction to different types of multiplicity problems that commonly arise in confirmatory controlled clinical trials. It focuses on multiplicity induced by multiple endpoints as well as other multiple comparison problems, including problems encountered in trials with multiple dose-control comparisons, trials with multiple subgroups, trials with an active control, etc.

The chapter also discusses multiplicity considerations for safety endpoints and multiplicity concerns for several special situations. Wiens Alcon Laboratories , Ajit C. Tamhane Northwestern University , Jason C.

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Hsu Ohio State University. This chapter gives an overview of concepts and principles that play a central role in multiple testing. This includes definitions of error rates and popular testing principles closure and partitioning principles. The chapter also introduces multiple testing procedures widely used in pre-clinical and clinical studies, including procedures based on univariate p-values, parametric procedures and resampling-based procedures.

These topics provide a foundation for the pharmaceutical applications considered in the subsequent chapters. Frank Bretz Novartis , Ajit C. This chapter provides an overview of statistical methods for analyzing clinical dose response studies comparing several dose levels with a control. Three distinct classes of methods are discussed. This chapter begins with a review of trend tests to detect an overall dose response effect.

Next, problems of finding the minimum effective dose and the maximum safe dose using multiple hypotheses testing methods are considered. Finally, the chapter discusses fitting models to dose response curves, and combining the modeling information with hypotheses testing approaches to obtain more powerful hybrid multiple comparison procedures. Illustrative numerical examples are given and available software is mentioned. This chapter provides an overview of statistical methods for analyzing multiple endpoints in clinical trials for comparing a treatment with a control placebo.

Four classes of methods are discussed in the chapter:. Procedures based on p-values, normal theory and resampling are discussed.

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Illustrative examples are given from recent clinical trials. This chapter describes a class of procedures, called gatekeeping procedures, for testing hierarchically ordered hypotheses.

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Such hypotheses commonly arise in clinical trials when dealing with multiple endpoints, dose-control comparisons and subgroup analyses. Sequential generalized least squares estimator of an autoregressive parameter. Sequential Analysis.

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  5. Statistics and Probability Letters. Journal of Applied Statistics. Sequential estimation of a tail probability of an unknown distribution. Vexler, A. Approximations to expected stopping times with applications to sequential estimation.

    Fleming, S. A comprehensive prognostic index to predict survival based on multiple comorbidities: a focus on breast cancer. Medical Care. Sequential confidence regions for maximum likelihood estimates. Annals of Statistics. On sequential estimation of the variance of an unknown distribution. Journal of Statistical Planning and Inference. The bootstrap point estimation: sequential approach. Analysis of QT interval in clinical trials.

    Drug Information Journal. Abraham, E. Critical Care Medicine 31, Repeated-measures models in the analysis of QT interval. Pharmaceutical Statistics 2, Gatekeeping strategies for clinical trials that do not require all primary effects to be significant.

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    Statistics in Medicine. Modeling paired categorical outcomes in clinical trials. Covariate-adjusted reference intervals for diagnostic data. Journal of Biopharmaceutical Statistics 13, Zeiher, B. Critical Care Medicine 32, Wiens, B. Fallback and gatekeeping strategies for primary and secondary endpoints. Bowton, D. Journal of Asthma 41, Bradley, J. A randomized, double-blinded, placebo-controlled clinical trial of LY, a selective inhibitor of group II secretory phospholipase A2, in the treatment of rheumatoid arthritis.

    Journal of Rheumatology. Beasley, C. Jr, Mitchell, M. Jr, Kloner, R.

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    The combined use of ibutilide as an active control with intensive ECG sampling and signal averaging as a sensitive method to assess the effects of tadalafil on the human QT interval. Journal of American College of Cardiology. The fallback procedure for evaluating a single family of hypotheses.

    • Multiple Testing Problems in Pharmaceutical Statistics Chapman & Hall CRC Biostatistics Series;
    • Sample Size Calculation for Clinical Trials with Multiple Primary Endpoints.
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    Journal of Biopharmaceutical Statistics. Sequential estimation in binary response models with fixed and random covariates. Patterson, S. Investigating drug-induced QT and QTc prolongation in the clinic: A review of statistical design and analysis considerations. This paper received the Donald E. Electrocardiogram reference ranges derived from a standardized clinical trial population. Multiple testing in clinical trials. Encyclopedia of Statistical Sciences. Second Edition. Balakrishnan editor , Wiley. Gatekeeping procedures in dose-response clinical trials based on the Dunnett test.

    Understand and master multiplicity in practical situations – Interview with Alex Dmitrienko

    Pharmaceutical Statistics. Bayesian predictive approach to interim monitoring in clinical trials. Fallback tests in dose-response clinical trials. Stepwise gatekeeping procedures in clinical trial applications. Biometrical Journal. Offen, W. Multiple co-primary endpoints: Medical and statistical solutions. This paper received the Thomas W. Design and analysis of dose-ranging clinical studies. Chuang-Stein, C. Challenge of multiple co-primary endpoints: A new approach. Tree-structured gatekeeping tests in clinical trials with hierarchically ordered multiple objectives.