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Synthesizing Qualitative Research
A considerable number of journal publications using a range of qualitative synthesis approaches has been published. Mary Dixon-Woods and colleagues (Mary Dixon-Woods, Booth, & Sutton, 2007) identified 42 qualitative evidence synthesis papers published in health care literature between 1990 and 2004. An ongoing update by Hannes and Macaitis (2010)identified around 100 additional qualitative or mixed methods syntheses. Yet these generally lack a clear, detailed description of what was done and why (Greenhalgh et al, 2007; McInnes & Wimpenny, 2008). Choices are most commonly influenced by what others have successfully used in the past or by a particular school of thought (Atkins et al, 2008; Britten et al, 2002). This is a substantive limitation.
This book brings balance to the options available to researchers, including approaches that have not had a substantial uptake among researchers. It provides arguments for when and why researchers or other parties of interest should opt for a certain approach to synthesis, which challenges they might face in adopting it and what the potential strengths and weaknesses are compared with other approaches.
This book acts as a resource for readers who would otherwise have to piece together the methodology from a range of journal articles. In addition, it should stimulate further development and documentation of synthesis methodology in a field that is characterized by diversity.
eBook
Interpreting biomedical science : experiment, evidence, and belief
Interpreting Biomedical Science: Experiment, Evidence, and Belief discusses what can go wrong in biological science, providing an unbiased view and cohesive understanding of scientific methods, statistics, data interpretation, and scientific ethics that are illustrated with practical examples and real-life applications. Casting a wide net, the reader is exposed to scientific problems and solutions through informed perspectives from history, philosophy, sociology, and the social psychology of science. The book shows the differences and similarities between disciplines and different eras and illustrates the concept that while sound methodology is necessary for the progress of science, we cannot succeed without a right culture of doing things.
Book
Quantitative methods for health research
A practical introduction to epidemiology, biostatistics, and research methodology for the whole health care community
This comprehensive text, which has been extensively revised with new material and additional topics, utilizes a practical slant to introduce health professionals and students to epidemiology, biostatistics, and research methodology. It draws examples from a wide range of topics, covering all of the main contemporary health research methods, including survival analysis, Cox regression, and systematic reviews and meta-analysis—the explanation of which go beyond introductory concepts. This second edition of Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics also helps develop critical skills that will prepare students to move on to more advanced and specialized methods.
A clear distinction is made between knowledge and concepts that all students should ensure they understand, and those that can be pursued further by those who wish to do so. Self-assessment exercises throughout the text help students explore and reflect on their understanding. A program of practical exercises in SPSS (using a prepared data set) helps to consolidate the theory and develop skills and confidence in data handling, analysis, and interpretation. Highlights of the book include:
* Combining epidemiology and bio-statistics to demonstrate the relevance and strength of statistical methods
* Emphasis on the interpretation of statistics using examples from a variety of public health and health care situations to stress relevance and application
* Use of concepts related to examples of published research to show the application of methods and balance between ideals and the realities of research in practice
* Integration of practical data analysis exercises to develop skills and confidence
* Supplementation by a student companion website which provides guidance on data handling in SPSS and study data sets as referred to in the text
Quantitative Methods for Health Research, Second Edition is a practical learning resource for students, practitioners and researchers in public health, health care and related disciplines, providing both a course book and a useful introductory reference.
eBook
Data analysis in sport
\"Making sense of sports performance data can be a challenging task but is nevertheless an essential part of performance analysis investigations. Focusing on techniques used in the analysis of sport performance, this book introduces the fundamental principles of data analysis, explores the most important tools used in data analysis, and offers guidance on the presentation of results. The book covers key topics such as: The purpose of data analysis, from statistical analysis to algorithmic processing Commercial packages for performance and data analysis, including Focus, Sportscode, Dartfish, Prozone, Excel, SPSS and Matlab Effective use of statistical procedures in sport performance analysis Analysing data from manual notation systems, player tracking systems and computerized match analysis systems Creating visually appealing 'dashboard' interfaces for presenting data Assessing reliability. The book includes worked examples from real sport, offering clear guidance to the reader and bringing the subject to life. This book is invaluable reading for any student, researcher or analyst working in sport performance or undertaking a sport-related research project or methods course\"-- Provided by publisher.
Book
Research design and analysis : a primer for the non-statistician
A concise, straightforward overview of research design and analysis, helping readers form a general basis for designing and conducting research
The practice of designing and analyzing research continues to evolve with advances in technology that enable greater technical analysis of data—strengthening the ability of researchers to study the interventions and relationships of factors and assisting consumers of research to understand and evaluate research reports. Research Design and Analysis is an accessible, wide-ranging overview of how to design, conduct, analyze, interpret, and present research. This book helps those in the sciences conduct their own research without requiring expertise in statistics and related fields and enables informed reading of published research.
Requiring no background in statistics, this book reviews the purpose, ethics, and rules of research, explains the fundamentals of research design and validity, and describes how to select and employ appropriate statistical techniques and reporting methods. Readers gain knowledge central to various research scenarios, from sifting through reports of meta-analyses and preparing a research paper for submission to a peer-reviewed journal to discussing, evaluating, and communicating research results. This book:
* Provides end-to-end guidance on the entire research design and analysis process
* Teaches readers how to both conduct their own research and evaluate the research of others
* Offers a clear, concise introduction to fundamental topics ideal for both reference and general education functions
* Presents information derived from the author's experience teaching the subject in real-world classroom settings
* Includes a full array of learning tools including tables, examples, additional resource suggestions, complete references, and appendices that cover statistical analysis software and data sets
Research Design and Analysis: A Primer for the Non-Statistician is a valuable source of information for students and trainees in medical and allied health professions, journalism, education, and those interested in reading and comprehending research literature.
eBook
Medical statistics
Holistic approach to understanding medical statistics. This hands-on guide is much more than a basic medical statistics introduction. It equips you with the statistical tools required for evidence-based clinical research. Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs. Showing you how to:.:.; analyse data with the help of data set examples (Click here to download datasets).; select the correct statistics and report results for publication o.
eBook
Multiple imputation and its application
A practical guide to analysing partially observed data.
Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods.
This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures.
Multiple Imputation and its Application:
* Discusses the issues raised by the analysis of partially observed data, and the assumptions on which analyses rest.
* Presents a practical guide to the issues to consider when analysing incomplete data from both observational studies and randomized trials.
* Provides a detailed discussion of the practical use of MI with real-world examples drawn from medical and social statistics.
* Explores handling non-linear relationships and interactions with multiple imputation, survival analysis, multilevel multiple imputation, sensitivity analysis via multiple imputation, using non-response weights with multiple imputation and doubly robust multiple imputation.
Multiple Imputation and its Application is aimed at quantitative researchers and students in the medical and social sciences with the aim of clarifying the issues raised by the analysis of incomplete data data, outlining the rationale for MI and describing how to consider and address the issues that arise in its application.
eBook
Statistical modeling for biomedical researchers : a simple introduction to the analysis of complex data
This text will enable biomedical researchers to use several advanced statistical methods that have proven valuable in medical research. The emphasis is on understanding the assumptions underlying each method, using exploratory techniques to determine the most appropriate method, and presenting results in a way that will be readily understood.
eBook