The research reported here deals with finding why people make some choices rather than others, why different people make different decisions in objectively similar situations. The book requires that its reader have some basic knowledge of statistical methods, and, since, it cuts across normally separate fields, it requires an adventuresome spirit. But, in return, the reader may expect to gain the use of a powerful tool that can be applied in his own practical projects and social science research.The message is on two levels. On one, the work is a practical handbook for application. On the other, it discusses some fundamental issues in the theory of decision-making and the social sciences.The book presents an application method for measuring assumptions realistic enough for use in management context. In a test-case study, the author uncovered startling diversity in the attributes investors use in picking stocks. More generally, such measures of assumptions are useful in managerial planning and control to aid in decision-making consistence, in learning to revise decision assumptions, and in designing information systems to support decision-making. They are also useful in improving joint decision-making and communication. Still other important applications are possible in consumer market research and in operations research modeling of decision processes. These applications are described with suggestive examples.To the management scientist the author seeks to show the benefits of extending explicitness beyond the traditional bounds of information systems into the realm of subjective decision assumptions. That is, subjective assumptions made explicit in a practical manner are employed as useful inputs to managerial information systems.Such measurement methods as reported here may also have widespread use in building social theory. Individual decision assumptions are key variables in microeconomics, in political science, in organization theory, and in the sociology of knowledge. Their measures play an analogous role in social science to that of thermometers in the development of thermodynamics.The material is developed as follows: First, the problem of discovering the assumptions which underlie decisions is sketched broadly. Alternative possible measurement approaches and theories are then described in logical order. An outline of the method for measuring assumptions is followed by the account of its use in a case study of stock market participants. It is this narrative that provides a practical handbook for the reader's use. A number of prototype applications are shown in some detail. The final chapters propose uses of the method for research in the social sciences and in accounting and the financial markets.

This monograph is intended for an advanced undergraduate or graduate course of engineering and management science. as well as for persons in business. industry. military or in any field. who want an introductory and a capsule look into the methods of group decision making under multiple criteria. This is a sequel to our previous works entitled "Multiple Objective Decision Making--Methods and Applications (No. 164 of the Lecture Notes). and "Multiple Attribute Decision Making--Methods and Applications (No. 186 of the Lecture Notes). Moving from a single decision maker (the consideration of Lecture Notes 164 and 186) to a multiple decision maker setting introduces a great deal of complexity into the analysis. The problem is no longer the selection of the most preferred alternative among the nondominated solutions according to one individual's (single decision maker's) preference structure. The analysis is extended to account for the conflicts among different interest groups who have different objectives. goals. and so forth. Group decision making under multiple criteria includes such diverse and interconnected fields as preference analysis. utility theory. social choice theory. committee decision theory. theory of voting. game theory. expert evaluation analysis. aggregation of qualitative factors. economic equilibrium theory. etc; these are simplified and systematically classified for beginners. This work is to provide readers with a capsule look into the existing methods. their characteristics. and applicability in the complexity of group decision making.

In recent years, much work has been done in formulating and clarifying the concept of sustainable development and related theoretical and research issues. Now, the challenge has shifted to designing and stimulating processes of effective planning and decision-making, at all levels of human activity, in such a way as to achieve local and global sustainable development. Information technology can help a great deal in achieving sustainable development by providing well-designed and useful tools for decision makers. One such tool is the decision support system, or DSS. This book explores the area of DSS in the context of sustainable development. As DSS is a very new technique, especially in the developing world, this book will serve as a reference text, primarily for managers, government officials, and information professionals in developing countries. It covers the concept of sustainable development, defines DSS and how it can be used in the planning and management of sustainable development, and examines the state of the art in DSS use. Other interested readers will include students, teachers, and analysts in information sciences; DSS designers, developers, and implementors; and international development agencies.

"Psychological Testing by Theresa J. B. Kline is an accessible, easy-to-read book that effectively communicates the current concepts, trends, and controversies in the field of psychological testing. Readers are provided with an in-depth analysis of psychometrics in a format that will keep their attention and that they will be able to relate to the significance of psychological testing across numerous areas such as schools, businesses, clinical settings, military, or government." -Todd L. Chmielewski, PsycCRITIQUES, December 7, 2005 VOL. 50, NO. 49, ARTICLE 12 Psychological Testing: A Practical Approach to Design and Evaluation offers a fresh and innovative approach to students and faculty in the fields of testing, measurement, psychometrics, research design, and related areas of study. Author Theresa J.B. Kline guides readers through the process of designing and evaluating a test, while ensuring that the test meets the highest professional standards. The author uses simple, clear examples throughout and fully details the required statistical analyses. Topics include—but are not limited to—design of item stems and responses; sampling strategies; classical and modern test theory; IRT program examples; reliability of tests and raters; validation using content, criterion-related, and factor analytic approaches; test and item bias; and professional and ethical issues in testing. With the student in mind, Kline has created features that ease them into more difficult ideas, always stressing the practical use of theoretical concepts. Features include A step-by-step approach to designing a test, including construct identification, construct operationalization, collecting data, item assessment, and reliability and validity techniques Examples of data analyses with printouts and interpretation Up-to-date coverage of psychometric topics, such as difference scores, change scores, translation, computer adaptive testing, reliability and validity generalization, professional and ethical guidelines, and references IRT program outputs (dichotomous and multiple response) Coverage of traditional topics in the context of how they would be used, such as standard errors and confidence intervals Sampling approaches and their strengths and weaknesses, as well as response rates and missing data management Psychological Testing is perfectly suited as a main text for upper-level undergraduate and graduate Testing or Psychometrics courses in departments of Psychology, Education, Sociology, Management, and in the Human Services disciplines. Professional researchers, educators, and consultants will also want to add this to their libraries for up-to-date coverage of test design and evaluation techniques. "Professor Kline′s attempts to de-mystify complex measurement concepts are beautifully simplified and illustrated in her countless illustrations of practical and relevant problems for the mathematically-challenged student. This book is also a must-have for those who simply do not have the desire for the theoretical jargon used in similar textbooks but are interested in the important conceptual and practical aspects of measurement as they apply in their disciplines." —Arturo Olivarez, Jr., Texas Tech University "Kline′s Psychological Testing provides a well-written treatment of the critical issues in designing and evaluating psychometric instruments. This book will be very useful to advanced undergraduate students, graduate students, and researchers." —Richard Block, Montana State University

Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.