A bayesian test for a two-way contingency table using independence priors

One method of testing for independence in a two-way table is based on the Bayes factor, the ratio of the likelihoods under the independence hypothesis H and the alternative hypothesis H. The main difficulty in this approach is the specification of prior distributions on the composite hypotheses H and H. A new Bayesian test statistic is constructed by using a prior distribution on H that is concentrated about the “independence surface” H. Approximations are proposed which simplify the computation of the test statistic. The values of the Bayes factor are compared with values of statistics proposed by Gunel and Dickey (1974), Good and Crook (1987), and Spiegelhalter and Smith (1982) for a number of two-way tables. This investigation suggests a strong relationship between the new statistic and the p-value.     

Grenzen der Geschichte?

The article follows Tony Becher’s suggestion, that scientific disciplines metaphorically spoken may be looked at as different tribes of different habits occupying different territories. The articles reviews then some possibilities to determine a border between the field of historical research and sociology by different methods, different theories, different research objects e. g. past vs. present and so on. The academic field of history is described as a field importing theories, methods and objects from other academic fields, many of them from sociology. The last decades’ processes of innovation and redefinition within the field of historical research diminished cognitive differences between history and sociology so significantly that — this is the main argument of the article — more or less only the borders produced by institutions remained. Nevertheless these kind of borders have major effects all of them responsible for maintaining different disciplinary identities.     

International Terrorism and the World‐System

Theories of international terrorism are reviewed. It then is noted that waves of terrorism appear in semiperipheral zones of the world‐system during pulsations of globalization when the dominant state is in decline. Finally, how these and other factors might combine to suggest a model of terrorism's role in the cyclical undulations of the world‐system is suggested .     

Interlakes community health centers: A case study

Interlakes Community Health Centers (ICHC) provides primary health care services to low-income people in a medium-size city. ICHC expanded from three to five service centers and soon ran into problems meeting payroll. Several strategic management dilemmas stem from this crisis.     

THE REDUCED-RANK GROWTH CURVE MODEL FOR DISCRIMINANT ANALYSIS OF LONGITUDINAL DATA

This paper presents a method of discriminant analysis especially suited to longitudinal data. The approach is in the spirit of canonical variate analysis (CVA) and is similarly intended to reduce the dimensionality of multivariate data while retaining information about group differences. A drawback of CVA is that it does not take advantage of special structures that may be anticipated in certain types of data. For longitudinal data, it is often appropriate to specify a growth curve structure (as given, for example, in the model of Potthoff & Roy, 1964). The present paper focuses on this growth curve structure, utilizing it in a model-based approach to discriminant analysis. For this purpose the paper presents an extension of the reduced-rank regression model, referred to as the reduced-rank growth curve (RRGC) model. It estimates discriminant functions via maximum likelihood and gives a procedure for determining dimensionality. This methodology is exploratory only, and is illustrated by a well-known dataset from Grizzle & Allen (1969).     

The Treatment of Sexual Disturbance

The thesis of this paper is that the highly competent marriage and family therapist had better have good understanding of both general disturbance and sexual disturbance. A case illustration of an individual with a sexual disturbance is given. Editor.