Volume 38 of Advances in Econometrics collects twelve innovative and thought-provoking contributions to the literature on Regression Discontinuity designs, covering a wide range of methodological and practical topics such as identification, interpretation, implementation, falsification testing, estimation and inference.

In this Element, which continues our discussion in Foundations, the authors provide an accessible and practical guide for the analysis and interpretation of Regression Discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. The focus is on extensions to the canonical sharp RD setup that we discussed in Foundations. The discussion covers (i) the local randomization framework for RD analysis, (ii) the fuzzy RD design where compliance with treatment is imperfect, (iii) RD designs with discrete scores, and (iv) and multi-dimensional RD designs.

Volume 38 of Advances in Econometrics collects twelve innovative and thought-provoking contributions to the literature on Regression Discontinuity designs, covering a wide range of methodological and practical topics such as identification, interpretation, implementation, falsification testing, estimation and inference.

The Handbook series provides a compendium of thorough and integrative literature reviews on a diverse array of topics of interest to the higher education scholarly and policy communities. Each chapter provides a comprehensive review of research findings on a selected topic, critiques the research literature in terms of its conceptual and methodological rigor, and sets forth an agenda for future research intended to advance knowledge on the chosen topic.

This volume, first published in 2000, provides an overview of research methods in contemporary social psychology.

The book is oriented to the practitioner.

This unique book is the first comprehensive guide to the discovery, analysis, and evaluation of natural experiments - an increasingly popular methodology in the social sciences. Thad Dunning provides an introduction to key issues in causal inference, including model specification, and emphasizes the importance of strong research design over complex statistical analysis. Surveying many examples of standard natural experiments, regression-discontinuity designs, and instrumental-variables designs, Dunning highlights both the strengths and potential weaknesses of these methods, aiding researchers in better harnessing the promise of natural experiments while avoiding the pitfalls. Dunning also demonstrates the contribution of qualitative methods to natural experiments and proposes new ways to integrate qualitative and quantitative techniques. Chapters complete with exercises and appendices covering specialized topics such as cluster-randomized natural experiments, make this an ideal teaching tool as well as a valuable book for professional researchers.

The first of three volumes, the five sections of this book cover a variety of issues important in developing, designing, and analyzing data to produce high-quality research efforts and cultivate a productive research career. First, leading scholars from around the world provide a step-by-step guide to doing research in the social and behavioral sciences. After discussing some of the basics, the various authors next focus on the important building blocks of any study. In section three, various types of quantitative and qualitative research designs are discussed, and advice is provided regarding best practices of each. The volume then provides an introduction to a variety of important and cutting-edge statistical analyses. In the last section of the volume, nine chapters provide information related to what it takes to have a long and successful research career. Throughout the book, example and real-world research efforts from dozens of different disciplines are discussed.

Scale-Up in Education, Volume 1: Ideas in Principle examines the challenges of 'scaling up' from a multidisciplinary perspective. It brings together contributions from disciplines that routinely take promising innovations to scale, including medicine, business, engineering, computing, and education. Together the contributors explore appropriate methods for estimating the effects of innovations in larger, more diverse settings and provide theories and models to guide the design of innovations most likely to remain viable at large scales. Specially-commissioned commentaries also discuss the analytical requirements and theoretical possibilities of a program of educational research on scale-up built upon these foundations. This volume is ideally suited for researchers, policymakers, and graduate students charged with determining the effectiveness of educational interventions. With its insights into the conceptual and methodological prerequisites for obtaining rigorous, actionable evidence of intervention effects, the volume provides reading for program evaluation courses in schools of education and public policy.

The golden standard evaluation reference text Now in its second edition, Evaluation Theory, Models, and Applications is the vital text on evaluation models, perfect for classroom use as a textbook, and as a professional evaluation reference. The book begins with an overview of the evaluation field and program evaluation standards, and proceeds to cover the most widely used evaluation approaches. With new evaluation designs and the inclusion of the latest literature from the field, this Second Edition is an essential update for professionals and students who want to stay current. Understanding and choosing evaluation approaches is critical to many professions, and Evaluation Theory, Models, and Applications, Second Edition is the benchmark evaluation guide. Authors Daniel L. Stufflebeam and Chris L. S. Coryn, widely considered experts in the evaluation field, introduce and describe 23 program evaluation approaches, including, new to this edition, transformative evaluation, participatory evaluation, consumer feedback, and meta-analysis. Evaluation Theory, Models, and Applications, Second Edition facilitates the process of planning, conducting, and assessing program evaluations. The highlighted evaluation approaches include: Experimental and quasi-experimental design evaluations Daniel L. Stufflebeam's CIPP Model Michael Scriven's Consumer-Oriented Evaluation Michael Patton's Utilization-Focused Evaluation Robert Stake's Responsive/Stakeholder-Centered Evaluation Case Study Evaluation Key readings listed at the end of each chapter direct readers to the most important references for each topic. Learning objectives, review questions, student exercises, and instructor support materials complete the collection of tools. Choosing from evaluation approaches can be an overwhelming process, but Evaluation Theory, Models, and Applications, Second Edition updates the core evaluation concepts with the latest research, making this complex field accessible in just one book.