Cleophas Quantile Regression in Clinical Research 9783030828424

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Автор: Cleophas
Название: Quantile Regression in Clinical Research
ISBN: 9783030828424
Издательство: Springer
Классификация:

Медицинские исследования

Вероятность и статистика

Извлечение знаний из данных

Экспертные системы / системы баз знаний

ISBN-10: 3030828425
Обложка/Формат: Soft cover
Страницы: 290
Вес: 0.56 кг.
Дата издания: 02.02.2023
Язык: English
Издание: 1st ed. 2021
Иллюстрации: 1 illustrations, black and white; xii, 290 p. 1 illus.
Размер: 235 x 155
Основная тема: Biomedicine
Подзаголовок: Complete analysis for data at a loss of homogeneity
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Quantile regression is an approach to data at a loss of homogeneity, for example (1) data with outliers, (2) skewed data like corona - deaths data, (3) data with inconstant variability, (4) big data. In clinical research many examples can be given like circadian phenomena, and diseases where spreading may be dependent on subsets with frailty, low weight, low hygiene, and many forms of lack of healthiness. Stratified analyses is the laborious and rather explorative way of analysis, but quantile analysis is a more fruitful, faster and completer alternative for the purpose. Considering all of this, we are on the verge of a revolution in data analysis. The current edition is the first textbook and tutorial of quantile regressions for medical and healthcare students as well as recollection/update bench, and help desk for professionals. Each chapter can be studied as a standalone and covers one of the many fields in the fast growing world of quantile regressions. Step by step analyses of over 20 data files stored at extras.springer.com are included for self-assessment. We should add that the authors are well qualified in their field. Professor Zwinderman is past-president of the International Society of Biostatistics (2012-2015) and Professor Cleophas is past-president of the American College of Angiology(2000-2002). From their expertise they should be able to make adequate selections of modern quantile regression methods for the benefit of physicians, students, and investigators.
Дополнительное описание: Chapter 1. General Introduction.- Chapter 2. Mathematical Models for Separating Quantiles from One Another.- Part I: Simple Univariate Regressions versus Quantile.- Chapter 3. Traditional and Robust Regressions versus Quantile.- Chapter 4. Autoregressions

Quantile Regression in Clinical Research, Cleophas