Credibility, Validity, and Assumptions in Program Evaluation Methodology by
This book focuses on assumptions underlying methods choice in program evaluation. Credible program evaluation extends beyond the accuracy of research designs to include arguments justifying the appropriateness of methods. An important part of this justification is explaining the assumptions made about the validity of methods. This book provides a framework for understanding methodological assumptions, identifying the decisions made at each stage of the evaluation process, the major forms of validity affected by those decisions, and the preconditions for and assumptions about those validities. Though the selection of appropriate research methodology is not a new topic within social development research, previous publications suggest only advantages and disadvantages of using various methods and when to use them. This book goes beyond other publications to analyze the assumptions underlying actual methodological choices in evaluation studies and how these eventually influence evaluation quality. The analysis offered is supported by a collation of assumptions collected from a case study of 34 evaluations. Due to its in-depth analysis, strong theoretical basis, and practice examples, Credibility, Validity and Assumptions is a must-have resource for researchers, students, university professors and practitioners in program evaluation. Importantly, it provides tools for the application of appropriate research methods in program evaluation
Discovering Knowledge in Data: an introduction to data mining by
The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before. This book provides the tools needed to thrive in today's big data world. The author demonstrates how to leverage a company's existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will "learn data mining by doing data mining". By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on data mining. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis. Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization Offers extensive coverage of the R statistical programming language Contains 280 end-of-chapter exercises Includes a companion website with further resources for all readers, and Powerpoint slides, a solutions manual, and suggested projects for instructors who adopt the book
Handbook of Health Survey Methods by
Guides readers through the development of sample designs, data collection procedures, and analytic methods for studies aimed at gathering health information on general and targeted populations.
Handbook of Nonresponse in Household Surveys by
A comprehensive, one-stop guide to identifying, reducing, and managing nonresponse in household surveys<br /> <br /> <p>Nonresponse and its impact on the sample selection mechanism of a survey is a common problem that often arises while collecting survey data. Handbook of Nonresponse in Household Surveys is a complete guide to handling the nonresponse problem, outlining statistical methods and techniques for improving response rates and correcting response data.</p> <p>The authors begin with an introduction to the nonresponse problem along with basic concepts and definitions. Subsequent chapters present current theories and methods that enable survey researchers to skillfully account for nonresponse in their research. Exploring the latest developments in the field, the book also features:</p> <ul> <li> <p>An introduction to the R-indicator as an indicator of survey quality</p> </li> <li> <p>Discussion of the different causes of nonresponse</p> </li> <li> <p>Extensive treatment of the selection and use of auxiliary information</p> </li> <li> <p>Best practices for re-approaching nonrespondents</p> </li> <li> <p>An overview of advanced nonresponse correction techniques</p> </li> <li> <p>Coverage of adaptive survey design</p> </li> </ul> <p>Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. Discussion concludes with a summary of the main concepts as well as a glossary of key terms and a set of exercises that allows readers to test their comprehension of the presented material. Examples using real survey data are provided, and a related website features additional data sets, which can be easily analyzed using Stata® or SPSS® software.</p> <p>Handbook of Nonresponse in Household Surveys is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.</p>
Handbook of Statistical Data Editing and Imputation by
A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error. In particular, the data collection stage is a potential source of errors and missing values. As a result, the important role of statistical data editing, and the amount of resources involved, has motivated considerable research efforts to enhance the efficiency and effectiveness of this process. Handbook of Statistical Data Editing and Imputation equips readers with the essential statistical procedures for detecting and correcting inconsistencies and filling in missing values with estimates. The authors supply an easily accessible treatment of the existing methodology in this field, featuring an overview of common errors encountered in practice and techniques for resolving these issues. The book begins with an overview of methods and strategies for statistical data editing and imputation. Subsequent chapters provide detailed treatment of the central theoretical methods and modern applications, with topics of coverage including: Localization of errors in continuous data, with an outline of selective editing strategies, automatic editing for systematic and random errors, and other relevant state-of-the-art methods Extensions of automatic editing to categorical data and integer data The basic framework for imputation, with a breakdown of key methods and models and a comparison of imputation with the weighting approach to correct for missing values More advanced imputation methods, including imputation under edit restraints Throughout the book, the treatment of each topic is presented in a uniform fashion. Following an introduction, each chapter presents the key theories and formulas underlying the topic and then illustrates common applications. The discussion concludes with a summary of the main concepts and a real-world example that incorporates realistic data along with professional insight into common challenges and best practices. Handbook of Statistical Data Editing and Imputation is an essential reference for survey researchers working in the fields of business, economics, government, and the social sciences who gather, analyze, and draw results from data. It is also a suitable supplement for courses on survey methods at the upper-undergraduate and graduate levels.
Mixed Methods and Credibility of Evidence in Evaluation by
Mixed methods in evaluation have the potential to enhance the credibility of evaluation and the outcomes of evaluation. This issue explores advances in understanding mixed methods in philosophical, theoretical, and methodological terms and presents specific illustrations of the application of these concepts in evaluation practice. Leading thinkers in the mixed methods evaluation community provide frameworks and strategies that are associated with improving the probability of reaching the goals of enhanced credibility for evaluations, the evidence they produce, and the actions taken as a result of the evaluation findings. This is the 138th volume of the Jossey-Bass quarterly report series New Directions for Evaluation, an official publication of the American Evaluation Association.
The SAGE Handbook of Survey Methodology by
Survey Methodology is becoming a more structuredfield of research, deserving of more and more academic attention. TheSAGE Handbook of Survey Methodology explores boththe increasingly scientific endeavour of surveys and their growing complexity,as different data collection modes and information sources are combined. The handbooktakes a global approach, with a team of international experts looking at localand national specificities, as well as problems of cross-national, comparativesurvey research. The chapters are organized into seven major sections, each ofwhich represents a stage in the survey life-cycle: Surveys and Societies Planning a Survey Measurement Sampling Data Collection Preparing Data for Use Assessing and Improving Data Quality The SAGE Handbook of SurveyMethodology is a landmark andessential tool for any scholar within the social sciences.
Survey Methods for Medical and Health Professions Education by
Offering a practical, six-step approach to effective survey design, delivery, and analysis, Survey Methods for Medical and Health Professions Education provides a real-world framework for successful research and evaluation. Focused entirely on medical and healthcare education and research, this unique text features quick-reference checklists, high-yield explanations, and case examples throughout, making it both a foundational reference and a go-to resource for all health professions researchers who use surveys. Provides a detailed and practical discussion of the steps in survey methodology, along with just enough theory to inform common decisions. Includes numerous real-world examples, both simple and complex, covering the wide range of problems researchers are likely to face. Addresses issues of survey fatigue and addresses the challenge of how to get "good data." Features "Voice of Experience" boxes-pearls based on authors' actual experiences. Concludes each chapter with a checklist so readers can quickly ensure they have covered every necessary step of survey design and implementation. Contains a convenient glossary of terms. Offers guidance from expert international contributors in medical and health professions research. Summarizes the most current standards and understanding of survey research so that experienced and novice researchers alike can directly apply content to improve research rigor. Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices.
Wiley Handbook of Web Surveys by
Methodological issues related to web surveys, covering both theoretical and practical aspects of the topic. The book first approaches the subject of web survey design, addressing the main question: How can an electronic questionnaire be designed such that respondents can complete it on the Internet without introducing (too many) errors? The second portion of the book is devoted to sampling issues and helping readers understanding how proper samples for web surveys can be selected to allow for unbiased estimation of population characteristics.
