Success Probability Estimation with Applications to Clinical Trials

Inbunden, Engelska, 2013

Av Daniele De Martini, Daniele de Martini

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Provides an introduction to the various statistical techniques involved in medical research and drug development with a focus on estimating the success probability of an experiment Success Probability Estimation with Applications to Clinical Trials details the use of success probability estimation in both the planning and analyzing of clinical trials and in widely used statistical tests.Devoted to both statisticians and non-statisticians who are involved in clinical trials, Part I of the book presents new concepts related to success probability estimation and their usefulness in clinical trials, and each section begins with a non-technical explanation of the presented concepts. Part II delves deeper into the techniques for success probability estimation and features applications to both reproducibility probability estimation and conservative sample size estimation.Success Probability Estimation with Applications to Clinical Trials:• Addresses the theoretical and practical aspects of the topic and introduces new and promising techniques in the statistical and pharmaceutical industries Features practical solutions for problems that are often encountered in clinical trialsIncludes success probability estimation for widely used statistical tests, such as parametric and nonparametric modelsFocuses on experimental planning, specifically the sample size of clinical trials using phase II results and data for planning phase III trialsIntroduces statistical concepts related to success probability estimation and their usefulness in clinical trialsSuccess Probability Estimation with Applications to Clinical Trials is an ideal reference for statisticians and biostatisticians in the pharmaceutical industry as well as researchers and practitioners in medical centers who are actively involved in health policy, clinical research, and the design and evaluation of clinical trials.

Produktinformation

Utgivningsdatum2013-05-17
Mått163 x 244 x 18 mm
Vikt454 g
FormatInbunden
SpråkEngelska
Antal sidor232
FörlagJohn Wiley & Sons Inc
ISBN9781118335789

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Preface xvAcknowledgments xviiAcronyms xixIntroduction xxiI.1 Overview of clinical trials xxiiI.2 Success rates of clinical trials xxivI.3 Success probability xxvI.4 Starting from practice xxviiPART I SUCCESS PROBABILITY ESTIMATION IN PLANNING AND ANALYZING CLINICAL TRIALS1 Basic statistical tools 31.1 Pointwise estimation 41.2 Confidence interval estimation, conservative estimation 61.3 The statistical hypotheses, the statistical test and the type I error for one-tailed tests 101.4 The power function and the type II error 111.5 The p-value 141.6 The success probability and its estimation 171.7 Basic statistical tools for two tailed tests 191.8 Other statistical hypotheses and tests 23 2 Reproducibility Probability Estimation 252.1 Pointwise RP estimation 262.2 RP-testing 292.3 The RP estimate and the p-value 322.4 Statistical lower bounds for the RP 352.5 The stability criterion for statistical significance 372.6 Other stability criteria for statistical significance 402.7 Comparing stability criteria 432.8 Regulatory agencies and the single study 452.9 The RP for two-tailed tests 462.10 Discussing Situation I in Section I.4.1 49 3 Sample Size Estimation 513.1 The classical paradigm of sample size determination 523.2 SP estimation for adapting the sample size 553.3 Launching the trial in practice 573.4 Practical aspects of SSE 603.5 Frequentist conservative SSE 673.6 Optimal frequentist CSSE 703.7 Bayesian CSSE 753.8 A comparison of CSSE strategies 803.9 Discussing Situations I and II in Section I.4 833.10 Sample size estimation for the two-tailed setting 854 Robustness and Corrections in Sample Size Estimation 894.1 CSSE strategies with different effect sizes in phases II and III 904.2 Comparing CSSE strategies in different Scenarios 914.3 Corrections for CSSE strategies 944.4 A comparison among Corrected CSSE strategies 97PART II SUCCESS PROBABILITY ESTIMATION FOR SOME WIDELY USED STATISTICAL TESTS5 General parametric SP estimation 1055.1 The parametric model 1055.2 Power, SP and noncentrality parameter estimation 1065.3 RP estimation and testing 1075.4 Sample size estimation 1085.5 Statistical tests included in the model 1096 SP estimation for Student’s t statistical tests 1136.1 Test for two means equal variances 1146.1.1 Power and RP estimation 1146.2 Test for two means unequal variances 1176.3 On Student’s t RP estimates 1207 SP estimation for Gaussian distributed test statistics 1237.1 Test for two proportions 1237.2 Test for survival: the log-rank test 1278 SP estimation for Chi-square statistical tests 1338.1 Test for two multinomial distributions: 2 x C comparative trial 1338.2 Test for S couples of binomial distributions: the Mantel-Haenszel test 1378.3 On χ2 RP estimates 1419 General nonparametric SP estimation with - applications to the Wilcoxon test 1439.1 The nonparametric model 1449.2 General nonparametric SP estimation 1459.3 The Wilcoxon rank-sum test 146A Tables of quantiles 161B Tables of RP estimates for the one-tailed Z test 169References 179Topic index 185Author index 193