Comparing the Survival of Two Groups with an Intermediate Clinical Event

Consider a subject entered on a clinicaltrial in which the major endpoint is a time metric such as deathor time to reach a well defined event. During the observationalperiod the subject may experience an intermediate clinical event.The intermediate clinical event may induce a change in the survivaldistribution. We consider models for the one and two sample problem.The model for the one sample problem enables one to test if theoccurrence of the intermediate event changed the survival distribution.This models provides a way of carrying out non-randomized clinicaltrial to determine if a therapy has benefit. The two sample problemconsiders testing if the probability distributions, with andwithout an intermediate event, are the same. Statistical testsare derived using a semi-Markov or a time dependent mixture model.Simulation studies are carried out to compare these new procedureswith the log rank, stratified log rank and landmark tests. Thenew tests appear to have uniformly greater power than these competitortests. The methods are applied to a randomized clinical trialcarried out by the Aids Clinical Trial Group (ACTG) which comparedlow versus high doses of zidovudine (AZT).     

Demographic,organizational and economic determinants of work satisfaction: An assessment of work attitudes of females in academic settings

Using a sample of females employed in nonindustrial settings, a model of work satisfaction was proposed and tested using nonlinear iterative partial least squares (PLS). Included in the final model were three demographic variables (age, hierarchical level, and education); two organizational variables (routinization and size); and two economic variables (objective and perceptual measures of opportunity). Positive relationships were observed between age and work satisfaction and hierarchical level and work satisfaction. An inverse relationship between education and work satisfaction was detected also. Both of the organizational variables were negatively correlated with work attitudes. Objective measures of opportunity (e.g., the unemployment rate) were negatively related to perceived opportunity, and perceived opportunity was inversely related to work satisfaction. The model explained almost 33% of the variance in job satisfaction, although the objective measures of opportunity accounted for less than 2% of the variance in perceived opportunity. The best predictor of work attitudes was routinization. Perceived opportunity and size were the second and third best predictors, respectively. The implications of this research for organizational theorists and managers are discussed.     

An Approximate Bayesian Algorithm for Combining Forecasts*

In this paper we propose a consensus forecasting method based on a convex combination of individual forecast densities. The exact Bayesian updating of the convex combination weights is very complex and practically prohibitive. We propose a simple sequential updating alternative method based on function approximation. Several examples illustrate the method.     

Reactions to interperson distance and topic intimacy: A comparison of strangers and friends

An experiment was conducted to test certain theoretical predictions derived from theories proposed by Hall (1966) and by Sundstrom and Altman (1976). Forty-five opposite-sex pairs discussed either a high, medium, or low intimacy topic while standing facing each other at either an intimate (30 cm), personal (60 cm), or social (165 cm) interperson distance. Following discussion, participants rated their reactions to the interperson distance on several dimensions. The results provided no support for the hypothesis, inferred from Hall's theory, that subjects would prefer an interperson distance that corresponded to topic intimacy. Ratings of feelings about the interpersondistance revealed a nonlinear relationship between rated feelings and interperson distance that is partially in accord with expectations derived from Sundstrom and Altman's theory, although there were some inconsistent findings.     

Decision analysis model: An extension of the states of nature concept

The standard model of decision analysis is modified by showing that, in general, the state of nature concept can be usefully represented in terms of three components that may be called: (1) payoff relevant (2) payoff generating and (3) message generating. This modification allows a richer structure within which decision analysis problems can be formulated and thus allows a richer foundation for developing new concepts, classifying problems and revising existing concepts such as perfect information. It is shown that the unique payoff relevant domain of states and acts must, in any real decision, provide the initial basis for defining any payoff function (or, as appropriate, the loss function and opportunity loss function) that has a domain other than pay-off-relevant states.