Selecting Closest to Control

Consider the usual one-way fixed effect analysis of variance model where the populations Π_i ( I = 0, 1, . . . , k ) have independent normal distributions with unknown means and common unknown variance. Let Π₀ be a control population with which the other (treatment) populations are to be compared. The basic problem is to select the treatment that is closest to the control mean. This situation occurs when one of the Π_i must be chosen, regardless of how many are equivalent to the control in the sense of having means sufficiently close. This paper follows the approach of Hsu (1996) and is based on a set of simultaneous confidence intervals. It provides a table of critical values which allows direct implementation of the new inference procedure. The applications given are of the balanced cross-over design type with negligible carry-over effects, for which the results of this paper may be used. One of the applications refers to the selection of a drug, which may not be bioequivalent to a reference formulation but is the closest of those drugs that are readily available to the group of patients considered.     

Multiple comparisons with ‘best’ for multivariate normal populations

Comparisons of multivariate normal populations are made using a mul-tivariate approach (instead of reducing the problem to a univariate one). A rather negative finding is that, for comparisons with the ‘best’ of each variate, repeated univariate comparisons appear to be almost as efficient as multivariate comparisons, at least for the bivariate case and, under certain circumstances, for higher dimensional cases. Investigations are done on comparisons with the ‘MAX-best’ population (that one having the largest maximum of the marginal means), the ‘MIN-best’ (having the largest minimum) and the ‘O-best’ (being closest to largest in all marginal means). Detailed results are given for the bivariate normal with extensions indicated for the multivariate.     

The two-sample problem with multivariate censored data: a new rank test family

A new rank test family is proposed to test the equality of two multivariate failure times distributions with censored observations. The tests are very simple: they are based on a transformation of the multivariate rank vectors to a univariate rank score and the resulting statistics belong to the familiar class of the weighted logrank test statistics. The new procedure is also applicable to multivariate observations in general, such as repeated measures, some of which may be missing. To investigate the performance of the proposed tests, a simulation study was conducted with bivariate exponential models for various censoring rates. The size and power of these tests against Lehmann alternatives were compared to the size and power of two other tests (Wei and Lachin, 1984 and Wei and Knuiman, 1987). In all simulations the new procedures provide a relatively good power and an accurate control over the size of the test. A real example from the National Cooperative Gallstone Study is given     

Media and the Israeli disability rights legislation: progress or mixed and contradictory images?

This article reviews and analyzes disability rights conceptualization and policy as reflected in the Israeli media after the enactment of the Equal Rights for Persons with Disabilities Law of 1998. Media coverage is examined through review of studies conducted on the subject in Israel. A comprehensive review of the research literature reveals a discrepancy between the purposes of anti‐discrimination legislation and policy and media reflections of disability, in which portrayal is primarily via a deviance lens. The discussion is based on the analysis of universal genesis of negative perceptions of disability, as well as on particularized culture bound meaning of disability within the Israeli symbolic framework.     

THE INTEGRATION OF EMOTION IN SOLUTION- FOCUSED THEAPY

The authors believe that solution-focused therapy can be enhanced by more overtly incorporating emotions into its theoretical framework and therapeutic strategies. They discuss the role of emotions in solution-focused therapy and offer several solution-focused interventions that utlize client affect.     

Examining Associations between Occupation and Health by using Routinely Collected Data

When examining a large number of associations simultaneously, as happens when routinely collected data are used to assess associations between occupation and health, it is not obvious how best to identify associations requiring further investigation since some risks may be high, or low, by chance alone. We have developed an approach to deal with this problem which is relatively easy to apply and appropriate to applications where data are not too sparse. Observed to expected ratios are estimated using an empirical Bayes procedure. Anomalous associations can be seen as outliers in a normal probability plot of the log-ratios. The method is illustrated in the analysis of 252 000 cancers registered in men in England during 1981–87.     

MULTIPLE COMPARISONS AND SELECTION1

The selection of the “best” of k populations and subsequent prediction for this population versus “the rest” is compared with the Newman-Keuls multiple comparison procedure for “separating” populations.