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For research to be effective, it is essential that every aspect of the study is well planned. Health Science Research has been written to help researchers from all disciplines conduct their studies with this kind of integrity. Each chapter covers a specific area fo conducting a study, including: - formulating the research question - preparing a grant application - subject recruitment - data collection and analysis - interpreting the results of the study This informative text is designed to be a user friendly research, reference and study tool. It has been organised into eight chapters, each of which covers a specific area of conducting a research study. This book will be of particular value to scientists, research assistants, qualified or trainee physicians, nurses and allied health workers. The book will also be an essential companion for students in all disciplines who want to learn more about how to do good research.
The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource.
Quantitative Research Methods for Health Professionals: A Practical Interactive Course is a superb introduction to epidemiology, biostatistics, and research methodology for the whole health care community. Drawing examples from a wide range of health research, this practical handbook covers important contemporary health research methods such as survival analysis, Cox regression, and meta-analysis, the understanding of which go beyond introductory concepts. The book includes self-assessment exercises throughout to help students explore and reflect on their understanding and a clear distinction is made between a) knowledge and concepts that all students should ensure they understand and b) those that can be pursued by students who wish to do so. The authors incorporate a program of practical exercises in SPSS using a prepared data set that helps to consolidate the theory and develop skills and confidence in data handling, analysis and interpretation.
As part of their research activities, researchers in all areas of education develop measuring instruments, design and conduct experiments and surveys, and analyze data resulting from these activities. Educational research has a strong tradition of employing state-of-the-art statistical and psychometric (psychological measurement) techniques. Commonly referred to as quantitative methods, these techniques cover a range of statistical tests and tools. Quantitative research is essentially about collecting numerical data to explain a particular phenomenon of interest. Over the years, many methods and models have been developed to address the increasingly complex issues that educational researchers seek to address. This handbook serves to act as a reference for educational researchers and practitioners who desire to acquire knowledge and skills in quantitative methods for data analysis or to obtain deeper insights from published works. Written by experienced researchers and educators, each chapter in this handbook covers a methodological topic with attention paid to the theory, procedures, and the challenges on the use of that particular methodology. It is hoped that readers will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area.
`I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology' - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.
Mixed Methods in Health Sciences Research: A Practical Primer, by Leslie Curry and Marcella Nunez-Smith, presents key theories, concepts, and approaches in an accessible way. Packed with illustrations from the health sciences literature, this ready-to-use guidebook shows readers how to design, conduct, review, and use mixed methods research findings. Helpful checklists, figures, tables, templates, and much more give readers examples that will elevate the quality of their research, facilitate communication about their methods, and improve efficiency over the course of their projects. Real-world examples and insights from mixed methods researchers provide unique perspectives on every aspect of mixed methods research. This book successfully pulls together foundational mixed methods principles, synthesizes the knowledge base in the field, and translates it for a health science researcher audience. “The content is highly applicable to real life research teams in the areas of clinical research, health services research, and implementation science, providing sound content and practical advice. The authors have synthesized and pull key concepts from a variety of sources to provide a concise resource.” —Linda M. Herrick, South Dakota State University “Everything from the references, to the topics, checklists, conceptual graphic representations, and organizers, interviews, and resources, all contribute to the content and aid with understanding and/or application. … It addresses specific MM research as it pertains to health sciences in a way that other texts just do not even attempt.” —Denise L. Winsor, University of Memphis “[This text is] a very pragmatic approach to mixed methods research; excellent resources, tables, and figures [are] provided, along with cases and examples of value to researchers and grant reviewers. Its relevance to practice, education, and research, as well as to potential policy implications, is a strong focus that would make this a valued textbook for any researcher!” ? —Karen Devereaux Melillo, University of Massachusetts Lowell “The text is cutting edge. It leads the way with its focus on team dynamics. [The authors] succeed in making the book relevant and practical. They also articulate a number of key insights in the area of mixed methods that rarely get addressed, such as teams and conflict. Great read with a lot of good, practical information for mixed methods researchers at all levels. The practical approach of this text makes it an innovative and valuable resource.” —John G. Schumacher, University of Maryland
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.

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