Read ebook Wiley Series in Probability and Statistics: Randomization in Clinical Trials : Theory and Practice by William F. Rosenberger FB2, PDF, DOC
9781118742242 English 1118742249 Praise for the First Edition "All medical statisticians involved in clinical trials should read this book..." - Controlled Clinical Trials Featuring a unique combination of the applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. Randomization in Clinical Trials: Theory and Practice, Second Edition features: Discussions on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adaptive randomization, including minimization techniques and inference New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Plenty of problem sets, theoretical exercises, and short computer simulations using SAS(R) to facilitate classroom teaching, simplify the mathematics, and ease readers' understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics. William F. Rosenberger, PhD, is University Professor and Chairman of the Department of Statistics at George Mason University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and author of over 80 refereed journal articles, as well as The Theory of Response-Adaptive Randomization in Clinical Trials, also published by Wiley. John M. Lachin, ScD, is Research Professor in the Department of Epidemiology and Biostatistics as well as in the Department of Statistics at The George Washington University. A Fellow of the American Statistical Association and the Society for Clinical Trials, Dr. Lachin is actively involved in coordinating center activities for clinical trials of diabetes. He is the author of Biostatistical Methods: The Assessment of Relative Risks, Second Edition , also published by Wiley., Praise for the First Edition : All medical statisticians involved in clinical trials should read this book Controlled Clinical Trials Featuring a unique combination ofthe applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. A consolidated review of the field, the Second Edition focuses on computation of randomized tests rather than the asymptotic theory of randomized tests. Randomization in Clinical Trials: Theory and Practice, Second Edition features: A discussion on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adjusted response-adaptive randomization, including minimization techniques and inference for covariate-adaptive randomization New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Many problem sets, theoretical exercises, and short computer simulations using SAS® to facilitate classroom teaching, to simplify the mathematics, and to ease understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics., This "Second Edition "features a unique overview that melds the concepts of conditional probability and stochastic processes into real-life applications. By combining the applied aspects of randomization in clinical trials with a nonparametric approach to inference, the book has become a 'must have' for biostatisticians and pharmaceutical industry statisticians. The book also focuses on the linear rank test under a randomization model, with added discussion on likelihood-based inference as it relates to sufficiency and ancillarity.Developments in stochastic processes and applied probability are presented where appropriate and includes response-adaptive randomization, Bayesian designs, CARA randomization, and covariate-adaptive randomization in theory and practice. Additional coverage of "randomization in practice," such as cluster randomization, new developments in restricted randomization, and increased discussions on philosophical issues in randomization, have also been included. This new edition also has an increased focus on computation of randomized tests rather than the asymptotic theory of randomized tests. Chapter coverage includes: randomization and the clinical trial; issues in the design of clinical trials; restrited randomization; balancing on covariates; accidental bias; selection bias; randomization as a basis for inference; inference for stratified, blocked, and covariate-adjusted analysesl randomization in practice; cluster randomization; response-adaptive randomization; response-adaptive randomization in practice; inference for response-adaptive and covariate-adaptive randomization; and covariate-adjusted response-adaptive randomization., This& Second Edition& features a unique overview that melds the concepts of conditional probability and stochastic processes into reallife applications.&& By combining the applied aspects of randomization in clinical trials with a& nonparametric approach to inference, the book has become a must have for biostatisticians and pharmaceutical industry statisticians.& The book also focuses on the linear rank test under a randomization model, with added discussion on likelihoodbased inference as it relates to sufficiency and ancillarity.Developments in stochastic processes and applied probability are presented where appropriate and includes responseadaptive randomization, Bayesian designs, CARA randomization, and covariateadaptive randomization in theory and practice.&& Additional coverage of "randomization in practice", such as cluster randomization, new developments in restricted randomization, and increased discussions on philosophical issues in randomization,& have also been included.& This new edition also has an increased focus on computation of randomized tests rather than the asymptotic theory of randomized tests.& Chapter coverage includes: randomization and the clinical trial; issues in the design of clinical trials; restrited randomization; balancing on covariates; accidental bias; selection bias; randomization as a basis for inference; inference for stratified, blocked, and covariateadjusted analysesl randomization in practice; cluster randomization; responseadaptive randomization; responseadaptive randomization in practice; inference for responseadaptive and covariateadaptive randomization; and covariateadjusted responseadaptive randomization.
9781118742242 English 1118742249 Praise for the First Edition "All medical statisticians involved in clinical trials should read this book..." - Controlled Clinical Trials Featuring a unique combination of the applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. Randomization in Clinical Trials: Theory and Practice, Second Edition features: Discussions on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adaptive randomization, including minimization techniques and inference New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Plenty of problem sets, theoretical exercises, and short computer simulations using SAS(R) to facilitate classroom teaching, simplify the mathematics, and ease readers' understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics. William F. Rosenberger, PhD, is University Professor and Chairman of the Department of Statistics at George Mason University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and author of over 80 refereed journal articles, as well as The Theory of Response-Adaptive Randomization in Clinical Trials, also published by Wiley. John M. Lachin, ScD, is Research Professor in the Department of Epidemiology and Biostatistics as well as in the Department of Statistics at The George Washington University. A Fellow of the American Statistical Association and the Society for Clinical Trials, Dr. Lachin is actively involved in coordinating center activities for clinical trials of diabetes. He is the author of Biostatistical Methods: The Assessment of Relative Risks, Second Edition , also published by Wiley., Praise for the First Edition : All medical statisticians involved in clinical trials should read this book Controlled Clinical Trials Featuring a unique combination ofthe applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. A consolidated review of the field, the Second Edition focuses on computation of randomized tests rather than the asymptotic theory of randomized tests. Randomization in Clinical Trials: Theory and Practice, Second Edition features: A discussion on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adjusted response-adaptive randomization, including minimization techniques and inference for covariate-adaptive randomization New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Many problem sets, theoretical exercises, and short computer simulations using SAS® to facilitate classroom teaching, to simplify the mathematics, and to ease understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics., This "Second Edition "features a unique overview that melds the concepts of conditional probability and stochastic processes into real-life applications. By combining the applied aspects of randomization in clinical trials with a nonparametric approach to inference, the book has become a 'must have' for biostatisticians and pharmaceutical industry statisticians. The book also focuses on the linear rank test under a randomization model, with added discussion on likelihood-based inference as it relates to sufficiency and ancillarity.Developments in stochastic processes and applied probability are presented where appropriate and includes response-adaptive randomization, Bayesian designs, CARA randomization, and covariate-adaptive randomization in theory and practice. Additional coverage of "randomization in practice," such as cluster randomization, new developments in restricted randomization, and increased discussions on philosophical issues in randomization, have also been included. This new edition also has an increased focus on computation of randomized tests rather than the asymptotic theory of randomized tests. Chapter coverage includes: randomization and the clinical trial; issues in the design of clinical trials; restrited randomization; balancing on covariates; accidental bias; selection bias; randomization as a basis for inference; inference for stratified, blocked, and covariate-adjusted analysesl randomization in practice; cluster randomization; response-adaptive randomization; response-adaptive randomization in practice; inference for response-adaptive and covariate-adaptive randomization; and covariate-adjusted response-adaptive randomization., This& Second Edition& features a unique overview that melds the concepts of conditional probability and stochastic processes into reallife applications.&& By combining the applied aspects of randomization in clinical trials with a& nonparametric approach to inference, the book has become a must have for biostatisticians and pharmaceutical industry statisticians.& The book also focuses on the linear rank test under a randomization model, with added discussion on likelihoodbased inference as it relates to sufficiency and ancillarity.Developments in stochastic processes and applied probability are presented where appropriate and includes responseadaptive randomization, Bayesian designs, CARA randomization, and covariateadaptive randomization in theory and practice.&& Additional coverage of "randomization in practice", such as cluster randomization, new developments in restricted randomization, and increased discussions on philosophical issues in randomization,& have also been included.& This new edition also has an increased focus on computation of randomized tests rather than the asymptotic theory of randomized tests.& Chapter coverage includes: randomization and the clinical trial; issues in the design of clinical trials; restrited randomization; balancing on covariates; accidental bias; selection bias; randomization as a basis for inference; inference for stratified, blocked, and covariateadjusted analysesl randomization in practice; cluster randomization; responseadaptive randomization; responseadaptive randomization in practice; inference for responseadaptive and covariateadaptive randomization; and covariateadjusted responseadaptive randomization.