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Educational policy-makers around the world constantly make decisions about how to use scarce resources to improve the education of children. Unfortunately, their decisions are rarely informed by evidence on the consequences of these initiatives in other settings. Nor are decisions typically accompanied by well-formulated plans to evaluate their causal impacts. As a result, knowledge about what works in different situations has been very slow to accumulate.
Over the last several decades, advances in research methodology, administrative record keeping, and statistical software have dramatically increased the potential for researchers to conduct compelling evaluations of the causal impacts of educational interventions, and the number of well-designed studies is growing. Written in clear, concise prose, Methods Matter: Improving Causal Inference in Educational and Social Science Research offers essential guidance for those who evaluate educational policies. Using numerous examples of high-quality studies that have evaluated the causal impacts of important educational interventions, the authors go beyond the simple presentation of new analytical methods to discuss the controversies surrounding each study, and provide heuristic explanations that are also broadly accessible. Murnane and Willett offer strong methodological insights on causal inference, while also examining the consequences of a wide variety of educational policies implemented in the U.S. and abroad. Representing a unique contribution to the literature surrounding educational research, this landmark text will be invaluable for students and researchers in education and public policy, as well as those interested in social science.
- Sales Rank: #74332 in Books
- Brand: Brand: Oxford University Press, USA
- Published on: 2010-09-17
- Original language: English
- Number of items: 1
- Dimensions: 6.50" h x 1.00" w x 9.50" l, 1.60 pounds
- Binding: Hardcover
- 416 pages
Features
- Used Book in Good Condition
Review
"Policy discussions today routinely demand that proposals be evidence-based -- without really understanding that the reliability and validity of what passes as evidence varies widely. Murnane and Willett have done a remarkable job of helping both producers and consumers to understand what is good evidence and how it can be produced. Methods Matter explains lucidly how the causal impact of educational and social interventions can be estimated from quantitative data, using a panoply of innovative empirical approaches." --Eric A. Hanushek, Senior Fellow, Hoover Institution, Stanford University
"Methods Matter is about research designs and statistical analyses for drawing valid and reliable causal inferences from data about real-world problems. The book's most telling feature is the wide range of education research examples that it uses to illustrate each point made. By presenting powerful research methods in the context of important research questions the authors are able to draw readers quickly and deeply into the material covered. New and experienced researchers from many fields will learn a lot from reading Methods Matter and will enjoy doing so."--Howard S. Bloom, Chief Social Scientist, MDRC
"Richard J. Murnane and John B. Willett provide a broadly accessible account of causal inference in educational research. They consider basic principles- how to define causal effects, frame causal questions, and design experiments- while also gently introducing important topics that have previously been obscure to non-specialists: randomization by group, natural experiments, instrumental variables, regression discontinuity, and propensity scores. Using a wide range or examples, the authors teach their readers to identify and challenge key assumptions underlying claims about what works in education. This book will improve educational research by challenging researchers and policy-makers to think more rigorously about the evidence and assumptions underlying their work." -- Stephen W. Raudenbush, Lewis Sebring Distinguished Service Professor, Department of Sociology, University of Chicago
"I strongly recommend Methods Matter to anyone who intends to conduct research on the causal impact of education programs and policies. Henceforth, a graduate course in education research methods that doesn't rely on it should be considered suspect. Methods Matter should also be essential reading for those who want to be critical consumers of advanced education research. Methods Matter very much, and so does this book. It is a very good book that signals a coming of age of the field."
--Grover Whitehurst, Director, Brown Center on Education Policy, Brookings Institute
"To be useful for development policy, educational research has to shed more light on how resources for education can produce more learning, more knowledge, more skills. In this book, Professors Richard Murnane and John Willett discuss a range of empirical methods for estimating causal relationships and review their applications in educational research. They translate complex statistical concepts into clear, accessible language and provide the kind of analytical guidance that a graduate student or young researcher might obtain only after years of experience with these methods. This volume is a very readable companion to any statistics textbook or statistical program on evaluation methods."
--Elizabeth M. King, Director, Education, The World Bank
About the Author
Richard J. Murnane, Juliana W. and William Foss Thompson Professor of Education and Society at Harvard University, is an economist who focuses his research on the relationships between education and the economy, teacher labor markets, the determinants of children's achievement, and strategies for making schools more effective.
John B. Willett, Charles William Eliot Professor of Education at Harvard University, is a quantitative methodologist who has devoted his career to improving the research design and data-analytic methods used in education and the social sciences, with a particular emphasis on the design of longitudinal research and the analysis of longitudinal data .
Most helpful customer reviews
5 of 5 people found the following review helpful.
Superb methods text.....
By Dale
I picked up "Method Matters" at the APA convention this past summer, and finally got to reading the chapter on Instrumental variables this week; and I must say, this is the clearest explication of IVE I have ever come upon. I will be recommending this text (alongside Shadish et al) to many students and colleagues for years to come!
3 of 3 people found the following review helpful.
Why didn't someone explain all of this earlier?
By Anonymous grad student
This book is great. As a graduate student in the social sciences, I have heard about all these methods before and have taken plenty of statistics and methodology classes but hadn't yet put all the pieces together in my head on causal inference. Murnane and Willet do an awesome job explaining how all the pieces fit together, in an intuitive and non-technical way (likely accessible to those who have taken basic statistics through regression). The examples are well-chosen to illustrate the pros and cons of the methods they discuss. The quality of the writing in this book is really excellent. I really just want to finish it all in one sitting, but I have to stop (I have only read the first five chapters so far) to work on my dissertation and fulfill other commitments. I wish I had read this book long ago (preferably before I started on my dissertation). Take my advice, don't wait on this one. So, Murnane and Willett, if your busy lives don't prevent you from stopping by Amazon from time to time to check out the reviews of your book, I want to say THANK YOU for all your work on this and hopefully this will push social scientists towards higher quality research and ultimately better public policies!
2 of 2 people found the following review helpful.
Intuitive applied econometrics for the social sciences.
By Nathaniel Lane
Methods Matter is pretty fantastic. Though I know it isn't quite fair: one could think this text as an intuitive, broadened "Mostly Harmless Econometrics" for the rest of the social sciences, replacing conditional expectation functions with clear, verbose reasoning. One does not necessarily need a theoretic statistics background to grasp the concepts, which makes it a useful book for intuitively motivating concepts such as instrumental variables, regression discontinuity, and difference-in-differences for social scientists with a solid background in regression analysis. While the book emphasizes education research, highlighting canonical examples from labor economics, it easily extends to other disciplines and questions.
I'd argue, maybe controversially, that even those with strong econometric chops could gain from the intuition. I thought the authors' handling of instrumental variables and exogenous variation was nuanced--dare I say useful to PhD researchers wanting intuition. While those with advanced training might scoff at the lack of expectation operators and formalism, I think the book does justice in popularizing some insights from applied econometric research in interesting ways. For instance, I was surprised by their exposition of Eric Verhoogen and Miguel Urquiola's research on regression discontinuity with sorting. I was also impressed that the authors incorporated some of the more critical considerations on "reduced form" methods into their suggested readings.
I think this is a verbose, well-written introduction for those in the early stages of graduate studies--particularly policy research; a perfect text for an MPA class on empirical methods.
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