Whilst the ‘health sciences’ are a broad and diverse area, and includes public health, primary care, health psychology, psychiatry and epidemiology, the research methods and data analysis skills required to analyse them are very similar. Moreover, the ability to appraise and conduct research is emphasised within the health sciences – and students are expected increasingly to do both. Introduction to Research Methods and Data Analysis in the Health Sciences presents a balanced blend of quantitative research methods, and the most widely used techniques for collecting and analysing data in the health sciences. Highly practical in nature, the book guides you, step-by-step, through the research process, and covers both the consumption and the production of research and data analysis. Divided into the three strands that run throughout quantitative health science research – critical numbers, critical appraisal of existing research, and conducting new research – this accessible textbook introduces: Descriptive statistics Measures of association for categorical and continuous outcomes Confounding, effect modification, mediation and causal inference Critical appraisal Searching the literature Randomised controlled trials Cohort studies Case-control studies Research ethics and data management Dissemination and publication Linear regression for continuous outcomes Logistic regression for categorical outcomes. A dedicated companion website offers additional teaching and learning resources for students and lecturers, including screenshots, R programming code, and extensive self-assessment material linked to the book’s exercises and activities. Clear and accessible with a comprehensive coverage to equip the reader with an understanding of the research process and the practical skills they need to collect and analyse data, it is essential reading for all undergraduate and postgraduate students in the health and medical sciences.
This third edition of Introduction to Research Methods and Data Analysis in Psychology provides you with a unique, balanced blend of quantitative and qualitative research methods. Highly practical in nature, the book guides you, step-by-step, through the research process and is underpinned by SPSS screenshots, diagrams and examples throughout.
A step-by-step guide to conducting research in medicine, public health, and other health sciences, this clear, practical, and straightforward text demystifies the research process and empowers students (and other new investigators) to conduct their own original research projects.
This popular textbook provides a concise, but comprehensive, overview of health research as an integrated, problem-solving process. It bridges the gap between health research methods and evidence-based clinical practice, making it an essential tool for students embarking on research. Practitioners also benefit from guidance on interpreting the ever-expanding published research in clinical and scientific journals, to ensure their practice is up to date and evidence-based and to help patients understand information obtained online. - Uses simple language and demystifies research jargon - Covers both quantitative and qualitative research methodology, taking a very practical approach - Gives examples directly related to the health sciences - Each chapter contains a self-assessment test so that the reader can be sure they know all the important points - Provides an extensive glossary for better understanding of the language of researchOnline interactive self-assessment tests: - Multiple choice questions - True or false questions - Short answer questions Log on to evolve.elsevier.com/Polgar/research and register to access the above assets.
The Sage Handbook of Qualitative Methods in Health Research is a comprehensive and authoritative source on qualitative research methods. The Handbook compiles accessible yet vigorous academic contributions by respected academics from the fast-growing field of qualitative methods in health research and consists of: - A series of case studies in the ways in which qualitative methods have contributed to the development of thinking in fields relevant to policy and practice in health care. - A section examining the main theoretical sources drawn on by qualitative researchers. - A section on specific techniques for the collection of data. - A section exploring issues relevant to the strategic place of qualitative research in health care environments. The Sage Handbook of Qualitative Methods in Health Research is an invaluable source of reference for all students, researchers and practitioners with a background in the health professions or health sciences.
Provides well-organized coverage of statistical analysis and applications in biology, kinesiology, and physical anthropology with comprehensive insights into the techniques and interpretations of R, SPSS®, Excel®, and Numbers® output An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences develops a conceptual foundation in statistical analysis while providing readers with opportunities to practice these skills via research-based data sets in biology, kinesiology, and physical anthropology. Readers are provided with a detailed introduction and orientation to statistical analysis as well as practical examples to ensure a thorough understanding of the concepts and methodology. In addition, the book addresses not just the statistical concepts researchers should be familiar with, but also demonstrates their relevance to real-world research questions and how to perform them using easily available software packages including R, SPSS®, Excel®, and Numbers®. Specific emphasis is on the practical application of statistics in the biological and life sciences, while enhancing reader skills in identifying the research questions and testable hypotheses, determining the appropriate experimental methodology and statistical analyses, processing data, and reporting the research outcomes. In addition, this book: • Aims to develop readers’ skills including how to report research outcomes, determine the appropriate experimental methodology and statistical analysis, and identify the needed research questions and testable hypotheses • Includes pedagogical elements throughout that enhance the overall learning experience including case studies and tutorials, all in an effort to gain full comprehension of designing an experiment, considering biases and uncontrolled variables, analyzing data, and applying the appropriate statistical application with valid justification • Fills the gap between theoretically driven, mathematically heavy texts and introductory, step-by-step type books while preparing readers with the programming skills needed to carry out basic statistical tests, build support figures, and interpret the results • Provides a companion website that features related R, SPSS, Excel, and Numbers data sets, sample PowerPoint® lecture slides, end of the chapter review questions, software video tutorials that highlight basic statistical concepts, and a student workbook and instructor manual An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences is an ideal textbook for upper-undergraduate and graduate-level courses in research methods, biostatistics, statistics, biology, kinesiology, sports science and medicine, health and physical education, medicine, and nutrition. The book is also appropriate as a reference for researchers and professionals in the fields of anthropology, sports research, sports science, and physical education. KATHLEEN F. WEAVER, PhD, is Associate Dean of Learning, Innovation, and Teaching and Professor in the Department of Biology at the University of La Verne. The author of numerous journal articles, she received her PhD in Ecology and Evolutionary Biology from the University of Colorado. VANESSA C. MORALES, BS, is Assistant Director of the Academic Success Center at the University of La Verne. SARAH L. DUNN, PhD, is Associate Professor in the Department of Kinesiology at the University of La Verne and is Director of Research and Sponsored Programs. She has authored numerous journal articles and received her PhD in Health and Exercise Science from the University of New South Wales. KANYA GODDE, PhD, is Assistant Professor in the Department of Anthropology and is Director/Chair of Institutional Review Board at the University of La Verne. The author of numerous journal articles and a member of the American Statistical Association, she received her PhD in Anthropology from the University of Tennessee. PABLO F. WEAVER, PhD, is Instructor in the Department of Biology at the University of La Verne. The author of numerous journal articles, he received his PhD in Ecology and Evolutionary Biology from the University of Colorado.
This title provides step-by-step directions for how to conduct a meta-study, as well as recommendations for tools and standards for the application of this approach.
Using detailed examples, the authors introduce readers to the use of facet theory as a method for integrating content design with data analysis. They show how facet theory provides a strategy for conceptualizing a study, for formulating the study's variables in terms of its purposes, for systematic sampling of the variables and for formulating hypotheses. The first part of the book introduces mapping with specific emphasis on mapping sentences. Part Two explores procedures for processing multivariate data. In conclusion there is a discussion of the nature of scientific enquiry and the difference between research questions and observational questions.
Covering the general process of data analysis to finding, collecting, organizing, and presenting data, this book offers a complete introduction to the fundamentals of data analysis. Using real-world case studies as illustrations, it helps readers understand theories behind and develop techniques for conducting quantitative, qualitative, and mixed methods data analysis. With an easy-to-follow organization and clear, jargon-free language, it helps readers not only become proficient data analysts, but also develop the critical thinking skills necessary to assess analyses presented by others in both academic research and the popular media. It includes advice on: - Data analysis frameworks - Validity and credibility of data - Sampling techniques - Data management - The big data phenomenon - Data visualisation - Effective data communication Whether you are new to data analysis or looking for a quick-reference guide to key principles of the process, this book will help you uncover nuances, complexities, patterns, and relationships among all types of data.
INTRODUCTION TO RESEARCH provides the reader with a foundation from which to critique and understand research designs and their applications to healthcare and human service settings. It is divided into four parts: Introduction, Thinking Processes, Design Approaches, and Action Processes. The text reflects a new school of thought that recognizes and values multiple research strategies. This perspective proposes that naturalistic and experimental-type research strategies have equal value and contribute in complementary and distinct ways to a science of practice. Knowledge of these different research traditions presents new opportunities for addressing the complex health-related research questions that are emerging in today's health and human service environments.
