Addresses basic aspects of research design which are central and common to many related fields in the social sciences, in the health sciences, in education, and in market research. Presents a unified approach to a common core of problems of statistical design that exists in all these fields, along with basic similarities in practical solutions. Describes many examples and analogies that are 'portable' from field to field of applications. Deals with designs that are the primary basis of research studies, but are neglected in most statistical textbooks (which tend to concentrate on statistical analysis). Takes a broader, more general and philosophical view of the statistics for the more fundamental aspects of design than do the standard treatments of experimental design. Carefully organized into seven chapters and 44 sections, this book can be readily consulted by research workers or graduate students. Extensively illustrated.
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About the author Leslie Kish is Professor Emeritus at the University of Michigan where he was a founder (1947) of the Institute for Social Research and selected as Henry Russel Lecturer for 1981. He is the author of Survey Sampling (Wiley, 1965) and of many articles. Dr. Kish was President of the American Statistical Association (1977), and of the International Association of Survey Statisticians (1983 85). He is an Honorary Fellow of the Royal Statistical Society and a member of the International Statistical Institute.
This title addresses those basic aspects of research design which are common to many related fields in the social sciences, health sciences, education, and market research. The work presents a unified approach to a common core of problems of statistical design that exists in all these fields, along with basic similarities in practical solutions. Describing many examples and analogies that are ′portable′ from application field to application field, Statistical Design for Research deals with designs that are the primary basis of research studies, but are neglected in most statistical textbooks that tend to concentrate on statistical analysis. This text takes a broader, more general and philosophical view of the statistics for the more fundamental aspects of design than do the standard treatments of experimental design. Extensively illustrated and carefully organized into seven chapters and 44 sections, this book can be readily consulted by research workers or graduate students!
Even before statistical data are collected for research, essential decisions of design must be made, decisions which will have significant effects on the validity and efficiency of studies. Yet virtually the entire literature on statistics addresses concerns of analysis and glosses over the crucial issues of collection and selection, issues that go to the heart of the methods and philosophy of the field. Statistical Design for Research delves into the criteria and decisions that underlie accurate, valid methodology. It pursues the uses and ramifications of three distinct design methods: experimental designs, survey sampling, and controlled investigations. Stressing the importance of the basic choice among these design strategies, the treatment explicates the analytical uses of sample surveys; designs for comparisons; controls for disturbing variables; samples and censuses; sample designs over time; and several distinct problems over time. Throughout, coverage is broad enough to encompass the common considerations in many related fields, including the social sciences, health sciences, education, and market research. It can serve as a textbook for university sources and as a source book for research workers. The text is enhanced by 37 tables and figures, over 50 problems, and a comprehensive list of references, notated to indicate the section where each is cited in the text. By claiming for statistics the usually neglected primary aspects of research design, Statistical Design for Research will produce more accurate, practical, and economical designs for future statistical analysis.
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