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Focuses on Donald Campbell's contributions to the concept of validity and the more activist side of his thinking, social experimentation.
Leading social research methodologists and evaluators address the issues of research design in this second of two volumes inspired by the work on Donald Campbell and sponsored by the American Evaluation Association. The book considers issues such as: quasi-experimentation; the proposed conduct of social inquiry; ways to take account of threats to validity; plausible rival hypotheses in measurement and design; subject selection and loss in randomized experiments; the use of evaluation to assess the validity of computer simulations; method variance; and time series experiments. Applied researchers who want to improve their research designs will find this book a compelling and thought-provoking read.
Social Experimentation: A Method for Planning and Evaluating Social Intervention summarizes the available knowledge about how randomized experiments might be used in planning and evaluating ameliorative social programs. The book presents various aspects of social experimentation - design, measurement, execution, sponsorship, and utilization of results. Chapters are devoted to topics on experimentation as a method of program planning and evaluation; experimental design and analysis; institutional and political factors in social experimentation; and aspects of time and institutional capacity. Sociologists will find the book a valuable piece of reference.
Intended to provide a basic understanding not only of how to design and implement social experiments, but also of how to interpret their results once they are completed, author Larry L. Orr's Social Experiments is written in a friendly, how-to manner. Through the use of illustrative examples, how-to exhibits and cases, and boldface key words, Orr provides readers with a grounding in the experimental method, including the rational and ethical issues of random assignment; designs that best address alternative policy questions; maximizing the precision of the estimates; implementing the experiment in the field; data collection; estimating and interpreting program impacts, costs, and benefits; dealing with potential biases; and the use and misuse of experimental results in the policy process. This book will be useful not only to those who plan to conduct experiments, but also to the much larger group who will, at one time or another, want to understand the results of experimental evaluations.
We shall examine the validity of 16 experimental designs against 12 common threats to valid inference. By experiment we refer to that portion of research in which variables are manipulated and their effects upon other variables observed. It is well to distinguish the particular role of this chapter. It is not a chapter on experimental design in the Fisher (1925, 1935) tradition, in which an experimenter having complete mastery can schedule treatments and measurements for optimal statistical efficiency, with complexity of design emerging only from that goal of efficiency. Insofar as the designs discussed in the present chapter become complex, it is because of the intransigency of the environment: because, that is, of the experimenter’s lack of complete control.
"Contains brief summaries of 240 known completed social experiments. Each summary outlines the cost and time frame of the demonstration, the treatments tested, outcomes of interest, sample sizes and target population, research components, major findings, important methodological limitations and design issues encountered, and other relevant topics. In addition, very brief outlines of 21 experiments and one quasi experiment still in progress [as of April 2003] are also provided"--p. 3.
This book provides researchers, evaluators, and graduate students with a user-friendly presentation of Campbell's essential work (including his thoughts on some of his classic works) in social experimentation.
Sections include: experiments and generalised causal inference; statistical conclusion validity and internal validity; construct validity and external validity; quasi-experimental designs that either lack a control group or lack pretest observations on the outcome; quasi-experimental designs that use both control groups and pretests; quasi-experiments: interrupted time-series designs; regresssion discontinuity designs; randomised experiments: rationale, designs, and conditions conducive to doing them; practical problems 1: ethics, participation recruitment and random assignment; practical problems 2: treatment implementation and attrition; generalised causal inference: a grounded theory; generalised causal inference: methods for single studies; generalised causal inference: methods for multiple studies; a critical assessment of our assumptions.
Two social psychologists outline a rigorous and rational approach to social experiments -- programmes designed to test new solutions to social problems. The basic principles of experimental design as applied to the problems of social experiments and the practicalities of measurement, collaboration and choosing the mode of research that is most applicable are discussed -- as is the problem of utilizing the results of social experimentation.
Policy analysis has grown increasingly reliant on the random assignment experiment—a research method whereby participants are sorted by chance into either a program group that is subject to a government policy or program, or a control group that is not. Because the groups are randomly selected, they do not differ from one another systematically. Therefore any differences between the groups at the end of the study can be attributed solely to the influence of the program or policy. But there are many questions that randomized experiments have not been able to address. What component of a social policy made it successful? Did a given program fail because it was designed poorly or because it suffered from low participation rates? In Learning More from Social Experiments, editor Howard Bloom and a team of innovative social researchers profile advancements in the scientific underpinnings of social policy research that can improve randomized experimental studies. Using evaluations of actual social programs as examples, Learning More from Social Experiments makes the case that many of the limitations of random assignment studies can be overcome by combining data from these studies with statistical methods from other research designs. Carolyn Hill, James Riccio, and Bloom profile a new statistical model that allows researchers to pool data from multiple randomized-experiments in order to determine what characteristics of a program made it successful. Lisa Gennetian, Pamela Morris, Johannes Bos, and Bloom discuss how a statistical estimation procedure can be used with experimental data to single out the effects of a program's intermediate outcomes (e.g., how closely patients in a drug study adhere to the prescribed dosage) on its ultimate outcomes (the health effects of the drug). Sometimes, a social policy has its true effect on communities and not individuals, such as in neighborhood watch programs or public health initiatives. In these cases, researchers must randomly assign treatment to groups or clusters of individuals, but this technique raises different issues than do experiments that randomly assign individuals. Bloom evaluates the properties of cluster randomization, its relevance to different kinds of social programs, and the complications that arise from its use. He pays particular attention to the way in which the movement of individuals into and out of clusters over time complicates the design, execution, and interpretation of a study. Learning More from Social Experiments represents a substantial leap forward in the analysis of social policies. By supplementing theory with applied research examples, this important new book makes the case for enhancing the scope and relevance of social research by combining randomized experiments with non-experimental statistical methods, and it serves as a useful guide for researchers who wish to do so.