Donald T. Campbell - Böcker

This book provides researchers, evaluators, and graduate students with a user-friendly presentation of Campbell's essential work (including his latest thoughts on some of his classic works) in social measurement. The book includes Campbell's arguments as to why qualitative approaches belong with quantitative ones as the assumptive background to relevant quantitative measures, his debate with deconstructionists and social constructionists on measurement validity, and an expansion and further explanation of his multitrait-multimethod matrix. By including overviews for each part and article as well as provide social scientists with useful insights into Campbell's papers in a format accessible to advanced undergraduate and graduate students.

This book provides researchers, evaluators, and graduate students with a user-friendly presentation of Campbell's essential work (including his latest thoughts on some of his classic works) in social measurement. The book includes Campbell's arguments as to why qualitative approaches belong with quantitative ones as the assumptive background to relevant quantitative measures, his debate with deconstructionists and social constructionists on measurement validity, and an expansion and further explanation of his multitrait-multimethod matrix. By including overviews for each part and article as well as provide social scientists with useful insights into Campbell's papers in a format accessible to advanced undergraduate and graduate students.

Thirty-five years ago, the four authors of this book addressed the problems of validity in social science research. They were interested in new and unused methods for obtaining information. The original edition and an expanded version have often been cited as justification for using novel means to supplement, if not replace, conventional techniques, especially survey and archival research. Illustrations abound in this book. While the novelty of the illustrations will keep many a graduate student amused, the more serious purpose is to authorize and motivate ingenuity in obtaining information. Even more fundamental is the strategy of combining very different methods so that research results can, by triangulation, withstand "threats to validity" that so frequently invalidate single-measure, conventional research.

Thirty-five years ago, the four authors of this book addressed the problems of validity in social science research. They were interested in new and unused methods for obtaining information. The original edition and an expanded version have often been cited as justification for using novel means to supplement, if not replace, conventional techniques, especially survey and archival research. Illustrations abound in this book. While the novelty of the illustrations will keep many a graduate student amused, the more serious purpose is to authorize and motivate ingenuity in obtaining information. Even more fundamental is the strategy of combining very different methods so that research results can, by triangulation, withstand "threats to validity" that so frequently invalidate single-measure, conventional research.

Regression toward the mean is a complex statistical principle that plays a crucial role in any research involving the measurement of change. This primer is designed to help researchers more fully understand this phenomenon and avoid common errors in interpretation. The book presents new methods of graphing regression toward the mean, facilitating comprehension with a wealth of figures and diagrams. Special attention is given to applications related to program or treatment evaluation. Numerous concrete examples illustrate the ways researchers all too often attribute effects to an intervention or other causal variable without considering regression artifacts as an alternative explanation for change. Also discussed are instances when problems are actually created, instead of solved, by correction for regression toward the mean. Throughout, the authors strive to use nontechnical language and to keep simulations and formulas as accessible as possible.