Published January, 2023
By Mark Chang and Shein-Chung Chow
Publisher: Taylor & Francis
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Availability: Available

This second edition reflects recent developments and regulatory positions on the use of adaptive designs in clinical trials. It unifies the vast and continuously growing literature and research activities on regulatory requirements, scientific and practical issues, and statistical methodology. This edition significantly updates the chapters on p

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Published January, 2023
By Pallav Shah
Publisher: Taylor & Francis
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Flexible bronchoscopy is one of the most exciting and challenging procedures in respiratory medicine today. This unique and comprehensive atlas by an expert practitioner provides an innovative pictorial guide to this procedure. The book is invaluable to those training in respiratory medicine as well as specialist respiratory nurses and practicin

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Published January, 2023
By Lyle D. Broemeling
Publisher: Taylor & Francis
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Exploring Bayesian statistics at an introductory level, this book illustrates how to apply these methods to solve important problems in medicine and biology. After focusing on the wide range of areas where diagnostic medicine is used, the book introduces Bayesian statistics and the estimation of accuracy.

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Published January, 2023
By Jay Liebowitz and Amanda Dawson
Publisher: Taylor & Francis
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Availability: Available

Actionable Intelligence in Healthcare cuts through the hype and misconceptions regarding healthcare data analytics, provides a realistic assessment of the state of healthcare data analytics today, and offers an insightful forecast of both the near-term and longer-term development in the field. By considering the pe

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Published January, 2023
By Jen-pei Liu and Shein-Chung Chow
Publisher: Taylor & Francis
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Availability: Available

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 David Shirley
Publisher: Taylor & Francis
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Updated for agile project management and the latest standards on project management, this bestseller explores the discipline of project management from the perspective of the healthcare environment.

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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 u Bhattacharya and Richard Callahan
Publisher: Taylor & Francis
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With a practice-based approach, this book presents cutting-edge topics in healthcare and public health, drawing on the premise that there is no single perspective or stakeholder. The work demonstrates the complexity of intersecting interests and responsibilities in a graspable way, and includes case studies contributed by leading experts. Topics

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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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Availability: Available

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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