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The Data Book: Collection and Management of Research Data is the first practical book written for researchers and research team members covering how to collect and manage data for research. The book covers basic types of data and fundamentals of how data grow, move and change over time. Focusing on pre-publication data collection and handling, the text illustrates use of these key concepts to match data collection and management methods to a particular study, in essence, making good decisions about data. The first section of the book defines data, introduces fundamental types of data that bear on methodology to collect and manage them, and covers data management planning and research reproducibility. The second section covers basic principles of and options for data collection and processing emphasizing error resistance and traceability. The third section focuses on managing the data collection and processing stages of research such that quality is consistent and ultimately capable of supporting conclusions drawn from data. The final section of the book covers principles of data security, sharing, and archival. This book will help graduate students and researchers systematically identify and implement appropriate data collection and handling methods.
Tired of a trial-and-error approach to collecting and managing data? Data Collection and Management offers helpful information on managing research projects. By stressing how to use good standards for data collecting and processing, the authors cover such important how-tos as planning research activities; making budgetary decisions and keeping the budget under control; hiring, training, and supervising field interviewing staff; establishing whether interviewers are ready to start interviewing; and ensuring high participant acquisition and retention rates. The book also covers using computerized information systems for tracking data collected and the data management process. Proposal writers, principal investigators, graduate research students, and project coordinators of research requiring large-scale field data collection will find the book to be an indispensable tool.
'The book is very simplistically written and, I consider that undergraduate students would find maximum chapters easy to comprehend and apply. I strongly recommend Qualitative Methodologies and Data Collection Methods: Toward Increased Rigour in Management Research for general and qualitative methodology courses and for practitioners and researchers searching for direction in planning or gaining a superior comprehension of qualitative research. It is an excellent book that gives brief and accommodating portrayals of major ascribes of qualitative research and priceless examples for planning and conducting research studies and various data collection methods in qualitative exploration.'Technological Forecasting & Social Change Globalisation opens new frontiers of research that require advanced research methods. While quantitative methods are ideal in some situations, qualitative methods are more appropriate for responding to 'how' questions in new contexts. They aim to understand and provide a holistic picture via interaction — a unique advantage over quantitative methods. This textbook for graduate students introduces qualitative research and covers major qualitative methodologies and data collection methods.The choice of methodologies in this book is based on their actual applicability in management research. This approach provides a hands-on emphasis while maintaining both scientific rigour and rooting, and a high practicality level with respect to problem analysis, the collection of data, and the way this data should be analysed.Students and researchers will benefit from features including explanations of the advantages and disadvantages of methodological choices, and elaborated examples of good articles. The reader will acquire an overview of current methodologies, which will facilitate the choice process with respect to research approaches, and is also encouraged to bring personal research skills to a higher level.
Provides a very practical and step-by-step guide to collecting and managing qualitative data,
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
The process of collecting accurate data through interviewing, questionnaires, and other methods has not always been clear. However, data collection in field settings can be done in a structured, systematic and scientific way. These authors show us how. First, they focus on the importance of finding the right questions to ask. By providing a variety of formats - triadic comparisons and rating scales for data collection, both oral and written methods - and stressing cultural relativity, Weller and Romney suggest ways to improve not only the data collected, but also the interpretation and analysis of such data. Primarily addressed to qualitative social scientists, this volume is also appropriate for anyone who wants to study attitudes and beliefs. In particular, it is an ideal text for courses in anthropology, linguistics, qualitative research methods, health care, and survey research.
Data Collection Data Collection is the second of six books in the Measurement and Evaluation Series from Pfeiffer. The proven ROI Methodology--developed by the ROI Institute--provides a practical system for evaluation planning, data collection, data analysis, and reporting. All six books in the series offer the latest tools, most current research, and practical advice for measuring ROI in a variety of settings. Data Collection offers an effective process for collecting data that is essential to the implementation of the ROI Methodology. The authors outline the techniques, processes, and critical issues involved in successful data collection. The book examines the various methods of data collection, including questionnaires, interviews, focus groups, observation, action plans, performance contracts, and monitoring records. Written for evaluators, facilitators, analysts, designers, coordinators, and managers, Data Collection is a valuable guide for collecting data that are adequate in quantity and quality to produce a complete and credible analysis.
Effective Research Data Management (RDM) is a key component of research integrity and reproducible research, and its importance is increasingly emphasised by funding bodies, governments, and research institutions around the world. However, many researchers are unfamiliar with RDM best practices, and research support staff are faced with the difficult task of delivering support to researchers across different disciplines and career stages. What strategies can institutions use to solve these problems? Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM. These case studies together illustrate the variety of innovative strategies research institutions have developed to engage with their researchers about managing research data. Each study is presented concisely and clearly, highlighting the essential ingredients that led to its success and challenges encountered along the way. By interviewing key staff about their experiences and the organisational context, the authors of this book have created an essential resource for organisations looking to increase engagement with their research communities. This handbook is a collaboration by research institutions, for research institutions. It aims not only to inspire and engage, but also to help drive cultural change towards better data management. It has been written for anyone interested in RDM, or simply, good research practice.
In Analysing Quantitative Survey Data, Jeremy Dawson introduces you to the key elements of analysing quantitative survey data using classical test theory, the measurement theory that underlies the techniques described in the book. The methodological assumptions, basic components and strengths and limitations of this analysis are explained and with the help of illustrative examples, you are guided through how to conduct the key procedures involved, including reliability analysis, exploratory and confirmatory factor analysis. Ideal for Business and Management students reading for a Master’s degree, each book in the series may also serve as reference books for doctoral students and faculty members interested in the method. Part of SAGE’s Mastering Business Research Methods series, conceived and edited by Bill Lee, Mark N. K. Saunders and Vadake K. Narayanan and designed to support researchers by providing in-depth and practical guidance on using a chosen method of data collection or analysis.
The SAGE Handbook of Qualitative Data Collection is a timely overview of the methodological developments available to social science researchers, covering key themes including: Concepts, Contexts, Basics Verbal Data Digital and Internet Data Triangulation and Mixed Methods Collecting Data in Specific Populations.