Big Data in Omics and Imaging: Integrated Analysis and Causal Inference 1st Edition PDF ebook

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eBook Details:

Full title: Big Data in Omics and Imaging: Integrated Analysis and Causal Inference 1st Edition
Edition: 1st
Copyright year: 2018
Publisher: Chapman & Hall
Author: Momiao Xiong
ISBN: 9781351172646, 9780429788758
Format: PDF

Description of Big Data in Omics and Imaging: Integrated Analysis and Causal Inference 1st Edition:
This book takes readers from very basic research concepts, such as ‘causality’ and ‘variables’, to the application of different types of statistical analyses. The first two chapters introduce the scientific method and causality, and assess the degree to which the major types of research designs used in health care studies allow researchers to make causal inferences. The book concludes with a detailed description of the seven critical factors that must be controlled to draw causal inferences from experimental studies. The rest of the book covers levels of measurement, i.e. nominal, ordinal, interval, and ratio scales; operational definitions; risk factors, independent and dependent variables, and other kinds of variables; how to calculate and interpret measures of central tendency and variability; the normal curve; commonly used measures of association and what they mean; criteria that have been suggested for inferring causality from nonexperimental research; and different types of t-tests. This book provides fundamental and practical knowledge about research methodology that is essential for health care chaplains, and students and professionals in other health care fields and the social sciences. The chapters in this book were originally published as articles in the Journal of Health Care Chaplaincy.

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