This monograph is not statistical. It looks instead at pre-statistical assumptions about dependent variables and causal order. Professor Davis spells out the logical principles that underlie our ideas of causality and explains how to discover causal direction, irrespective of the statistical technique used. He stresses throughout that knowledge of the `real world' is important and repeatedly challenges the myth that causal problems can be solved by statistical calculations alone.
The transition from viewing organizations as bureaucracies towards seeing them in metaphoric terms is a contemporary break with past organizational theory. But to investigate the similarities between real organizations and the metaphors describing their functions and context, a shift in both methods of inquiry and organizational theory must take place. This volume explores the paradigm shift at three levels: an overview of historical roots; an explication of terminology, metaphors and constructs; and the practical application of these new organizational inquiry methods, especially for actual research practices and policy analysis applications.
Berry and Feldman provide a systematic treatment of many of the major problems encountered in using regression analysis. The authors discuss: the consequences of violating the assumptions of the regression model; procedures for detecting when such violations occur; and strategies for dealing with these problems when they arise. The monograph was written without the use of matrix algebra, and numerous examples are provided from political science, sociology, and economics.
Social scientists with an interest in theory and research, particularly those involved in educational research, sociologists whose interest are sociology of science, organizational theory, research and methodology (both quantitative and qualitative), and social anthropologists
Ordinary regression analysis is not appropriate for investigating dichotomous or otherwise `limited' dependent variables, but this volume examines three techniques -- linear probability, probit, and logit models -- which are well-suited for such data. It reviews the linear probability model and discusses alternative specifications of non-linear models. Using detailed examples, Aldrich and Nelson point out the differences among linear, logit, and probit models, and explain the assumptions associated with each.
Although clustering -- the classifying of objects into meaningful sets -- is an important procedure, cluster analysis as a multivariate statistical procedure is poorly understood. This volume is an introduction to cluster analysis for professionals, as well as for advanced undergraduate and graduate students with little or no background in the subject. Reaching across disciplines, Aldenderfer and Blashfield pull together the newest information on cluster analysis -- providing the reader with a pragmatic guide to its current uses, statistical techniques, validation methods, and compatible software programmes.
Rape, Child Sexual Abuse, and Workplace Harassment
Diana Russell analyses and compares the prevalence and causes of three forms of sexual exploitation -- rape, child sexual abuse, and sexual harassment in the workplace. Although public awareness of sexual and non-sexual abuse of adults and children has grown steadily over the past few years, the three categories have been analysed and treated as separate issues. Diana Russell uses an original analytical framework to integrate extensive literature on these topics, revealing numerous links between issues that are often considered separate and distinct.
