Published January, 2023
By Jialiang Li and Shuangge Ma
Publisher: Taylor & Francis
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Using real data sets throughout, this text introduces the latest methods for analyzing high-dimensional survival data. With an emphasis on the applications of survival analysis techniques in genetics, it presents a statistical framework for burgeoning research in this area and offers a set of established approaches for statistical analysis. The

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Published January, 2023
By Alvan R. Feinstein
Publisher: Taylor & Francis
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It covers many of the newew statistical methods and approaches and is arranged in a logical sequence that advances from simple to more elaborate results. The text describes all the conventional statistical procedures and offers reasonably rigorous accounts of many of their mathematical justifications.

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Published January, 2023
By Alex Dmitrienko, Frank Bretz and Ajit C. Tamhane
Publisher: Taylor & Francis
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Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, this volume explores the rapidly growing area of multiple comparison research with an emphasis on pharmaceutical applications. It describes important multiplicity problems encountered in pre-clinical and clinic

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Published January, 2023
By Robert D. Gibbons and Anup Amatya
Publisher: Taylor & Francis
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This book presents a wide variety of statistical approaches for analyzing pharmacoepidemiologic data. It covers both commonly used techniques, such as proportional reporting ratios for the analysis of spontaneous adverse event reports, and newer approaches, such as the use of marginal structural models for controlling dynamic selection bias in t

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Published January, 2023
By Gordon Claridge
Publisher: Taylor & Francis
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This fascinating collection charts the development of a model that blurs the line between madness and sanity, seeing mental illness not as a pathology suffered by a few, but as the end of a continuum experienced by us all.

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Published January, 2023
By Jen-pei Liu and Shein-Chung Chow
Publisher: Taylor & Francis
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Taking into account the regulatory and scientific developments that have occurred since its predecessor, this third edition presents a comprehensive summary of the ever-expanding literature and research in the field. It focuses on regulatory requirements, current scientific and practical issues, and the statistical methodology of designing and a

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Published January, 2023
By Annette Karmiloff-Smith, Mark H. Johnson and Michael S. C. Thomas
Publisher: Taylor & Francis
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This influential volume of papers, chosen by Professor Annette Karmiloff-Smith, recognises her major contribution to the field of developmental psychology. Published over a 40-year period, the papers included here address the major themes that permeate through Annette's work: from typical to atypical development, genetics and computation modelli

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Published January, 2023
By Marc Lavielle
Publisher: Taylor & Francis
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This book provides wide-ranging coverage of parametric modeling in linear and nonlinear mixed effects models. It presents a rigorous approach for describing, implementing, and using mixed effects models. With these models, readers can perform parameter estimation and modeling across a whole population of individuals at the same time. The book ta

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Published January, 2023
By Werner Vach
Publisher: Taylor & Francis
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While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners. This text presents the fundamental concepts and important aspects of regression models most commonly used in medical research, including the classical regression mode

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Published January, 2023
By Dimitris Rizopoulos
Publisher: Taylor & Francis
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Longitudinal studies often investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest. An example is prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. This book provides a full treatment of joint models for longitudinal a

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