RealWorld Evaluation


Book Description

This book addresses the challenges of conducting program evaluations in real-world contexts where evaluators and the agencies face budget and time constraints and where critical data is missing. The book is organized around a seven-step model developed by the authors, which has been tested and refined in workshops. Vignettes and case studies—representing evaluations from a variety of geographic regions and sectors—demonstrate adaptive possibilities for small projects with budgets of a few thousand dollars to large-scale, long-term evaluations. The text incorporates quantitative, qualitative, and mixed-method designs and this Second Edition reflects important developments in the field over the last five years.




RealWorld Evaluation


Book Description

RealWorld Evaluation: Working Under Budget, Time, Data, and Political Constraints addresses the challenges of conducting program evaluations in real-world contexts where evaluators and their clients face budget and time constraints. The book is organized around the authors’ seven-step model that has been tested in workshops and practice environments to help the evaluation implementers and managers make the best choices when faced with real world constraints. The Third Edition includes a new chapter on gender equality and women’s empowerment and discussion of digital technology and data science.




Evaluation for the Real World


Book Description

Evaluation research findings should be a key element of the policy-making process, yet in reality they are often disregarded. This valuable book examines the development of evaluation and its impact on public policy by analysing evaluation frameworks and criteria which are available when evaluating public policies and services. It further examines the nature of evidence and its use and non-use by decision-makers and assesses the work of influential academics in the USA and UK in the context of evaluation and policy making. The book emphasises the 'real world' of decision-makers in the public sector and recognises how political demands and economic pressures can affect the decisions of those who commission evaluation research while providing recommendations for policymakers on adopting a different approach to evaluation. This is essential reading for under-graduate and post-graduate students of policy analysis and public sector management, and those who are involved in the planning and evaluation of public policies and services.




Impact Evaluation in Practice, Second Edition


Book Description

The second edition of the Impact Evaluation in Practice handbook is a comprehensive and accessible introduction to impact evaluation for policy makers and development practitioners. First published in 2011, it has been used widely across the development and academic communities. The book incorporates real-world examples to present practical guidelines for designing and implementing impact evaluations. Readers will gain an understanding of impact evaluations and the best ways to use them to design evidence-based policies and programs. The updated version covers the newest techniques for evaluating programs and includes state-of-the-art implementation advice, as well as an expanded set of examples and case studies that draw on recent development challenges. It also includes new material on research ethics and partnerships to conduct impact evaluation. The handbook is divided into four sections: Part One discusses what to evaluate and why; Part Two presents the main impact evaluation methods; Part Three addresses how to manage impact evaluations; Part Four reviews impact evaluation sampling and data collection. Case studies illustrate different applications of impact evaluations. The book links to complementary instructional material available online, including an applied case as well as questions and answers. The updated second edition will be a valuable resource for the international development community, universities, and policy makers looking to build better evidence around what works in development.




Real-World Evidence Generation and Evaluation of Therapeutics


Book Description

The volume and complexity of information about individual patients is greatly increasing with use of electronic records and personal devices. Potential effects on medical product development in the context of this wealth of real-world data could be numerous and varied, ranging from the ability to determine both large-scale and patient-specific effects of treatments to the ability to assess how therapeutics affect patients' lives through measurement of lifestyle changes. In October 2016, the National Academies of Sciences, Engineering, and Medicine held a workshop to facilitate dialogue among stakeholders about the opportunities and challenges for incorporating real-world evidence into all stages in the process for the generation and evaluation of therapeutics. Participants explored unmet stakeholder needs and opportunities to generate new kinds of evidence that meet those needs. This publication summarizes the presentations and discussions from the workshop.




Real-World Evidence in Drug Development and Evaluation


Book Description

Real-world evidence (RWE) has been at the forefront of pharmaceutical innovations. It plays an important role in transforming drug development from a process aimed at meeting regulatory expectations to an operating model that leverages data from disparate sources to aid business, regulatory, and healthcare decision making. Despite its many benefits, there is no single book systematically covering the latest development in the field. Written specifically for pharmaceutical practitioners, Real-World Evidence in Drug Development and Evaluation, presents a wide range of RWE applications throughout the lifecycle of drug product development. With contributions from experienced researchers in the pharmaceutical industry, the book discusses at length RWE opportunities, challenges, and solutions. Features Provides the first book and a single source of information on RWE in drug development Covers a broad array of topics on outcomes- and value-based RWE assessments Demonstrates proper Bayesian application and causal inference for real-world data (RWD) Presents real-world use cases to illustrate the use of advanced analytics and statistical methods to generate insights Offers a balanced discussion of practical RWE issues at hand and technical solutions suitable for practitioners with limited data science expertise




Evaluation for the Real World


Book Description

This valuable book examines the development of evaluation and its impact on public policy by analysing evaluation frameworks and criteria which are available when evaluating public policies and services.




Real-World Machine Learning


Book Description

Summary Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning systems help you find valuable insights and patterns in data, which you'd never recognize with traditional methods. In the real world, ML techniques give you a way to identify trends, forecast behavior, and make fact-based recommendations. It's a hot and growing field, and up-to-speed ML developers are in demand. About the Book Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems. What's Inside Predicting future behavior Performance evaluation and optimization Analyzing sentiment and making recommendations About the Reader No prior machine learning experience assumed. Readers should know Python. About the Authors Henrik Brink, Joseph Richards and Mark Fetherolf are experienced data scientists engaged in the daily practice of machine learning. Table of Contents PART 1: THE MACHINE-LEARNING WORKFLOW What is machine learning? Real-world data Modeling and prediction Model evaluation and optimization Basic feature engineering PART 2: PRACTICAL APPLICATION Example: NYC taxi data Advanced feature engineering Advanced NLP example: movie review sentiment Scaling machine-learning workflows Example: digital display advertising




Doing Research in the Real World


Book Description

Available with free access to the interactive eBook* for 12 months when you buy the paperback version (ISBN 9781446295311 only), this is the companion for any student undertaking a research project. Click on the icons in the margins of the eBook to access a wealth of resources including: Video Content Chapter introductions and top tips from the author along with tried and tested open access videos on YouTube introduce you to key chapter contents Datasets Play around with real data in SPSS and put your statistics knowledge into practice Weblinks Direct you to real world examples to broaden your knowledge Checklists Guide you through a specific research process such as running a focus group or conducting an interview Further Reading Link you to a range of resources to deepen your understanding of a topic However you access the content the Third Edition guides you smoothly through the research process from start to finish setting out the skills needed to design and conduct effective research and introduces the reader to the reality of conducting research in the real world. It gives practical advice on how best to select appropriate projects, design strategies, sources and methods and provides the tools needed to collect, analyze and present data. Applicable to any discipline and firmly rooted in the practicalities of research there are new and exciting chapters on: - Using SPSS for quantitative data analysis - Sampling strategies in quantitative and qualitative research - Approaches to secondary analysis - Using focus groups - Ethnography and participant observation (*interactivity only available through Vitalsource eBook) Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.




Intervention Effectiveness Research: Quality Improvement and Program Evaluation


Book Description

Do interventions improve health outcomes? This volume provides a model and road map to answer clinical questions related to intervention effectiveness research, quality improvement, and program evaluations. It offers clear and simple guidance for all phases of a clinical inquiry projects from planning through dissemination and communication of results and findings. The book emphasizes the value and importance of leveraging existing data to advance research, practice, and quality improvement efforts. Intervention and Effectiveness Research is a practical guide for organizing and navigating the intersections of research and practice. Structure, process and outcome worksheets for every step are provided together with examples from diverse settings and populations to lead readers through the process of implementing their own projects. The author guides readers through the process of designing, implementing, and evaluating project s. This book is intended for teachers of DNP and PhD programs in nursing and other disciplines, their students, and healthcare leaders who need to leverage data to demonstrate care quality and outcomes.




Recent Books