Trends in Premarital Counseling*

Recent developments and current problems in the field of premarital counseling are discussed. Particular attention is given to the need for better training of premarital counselors and for more systematic evaluation of the impact of premarital counseling strategies.     

Estimating means when sampling gives probabilities as well as values or “Looking a gift horse in the mouth”

Consider the random sampling of a discrete population. The observations, as they are collected one by one, are enhanced in that the probability mass associated with each observation is also observed. The goal is to estimate the population mean. Without this extra information about probability mass, the best general purpose estimator is the arithmetic average of the observations, XBAR. The issue is whether or not the extra information can be used to improve on XBAR. This paper examines the issues and offers four new estimators, each with its own strengths and liabilities. Some comparative performances of the four with XBAR are made.The motivating application is a Monte Carlo simulation that proceeds in two stages. The first stage independently samples n characteristics to obtain a configuration of some kind, together with a configuration probability p obtained, if desired, as a product of n individual probabilities. A relatively expensive calculation then determines an output X as a function of the configuration. A random sample of X could simply be averaged to estimate the mean output, but there are possibly more efficient estimators on account of the known configuration probabilities.     

Use of home and community-based services by elderly black and white females

The study purpose was to determine the impact of demographic, social, environmental, and health indicators on utilization of community-based services among black and white female elders. Existing data from a regional Area Agency on Aging was used and the sample (N = 1816) included low income and rural females. Races differed in use and services most frequently used were case management, outreach, congregate meal, and home delivered meals. Multiple linear and logistic regression indicated that age, payment source, income adequacy, residence, health conditions, sensory impairment, and function were associated with the number and types of services used, but these differed by race. Study findings have implications for health care providers, educators, policy makers, and planners.     

Fertility and replacement: Some alternative stochastic models and results for Brazil

The observed joint distribution of births and child deaths for a cohort of women at a given point in time depends on the number of children that would have been born had the family experienced no deaths, the number of child deaths experienced, and the proportion of these deaths that are replaced by a subsequent birth. In this paper we estimate the parameters of the assumed distributions of these three events using a minimum distance estimation model and data from the 1970 Brazilian census. The parameter estimates are shown to be similar to those obtained previously using a maximum likelihood estimation model. When the data are subdivided according to women's years of schooling, estimates of probability of a child death and mean and variance of children born if no deaths decrease while estimates of probability of replacement of a dead child increase as years of schooling increase.     

Canonical correlation between groups of acarine, fungal and environmental variables in bulk grain ecosystems

Summary Interrelations among acarine, fungal, and environmental components of bulk grain ecosystems were determined by canonical correlation analyses. Twenty-seven variables were measured monthly in samples collected from 2 identical grain bulks in a granary in Winnipeg during the years 1959–67. The relationships between 9 kinds of arthropods and 6 environ mental variables, and between the same arthropods and 12 kinds of actinomycetes and fungi were examined. The maximum canonical correlation between arthropods and environmental factors was 0.35, and between arthropods and microorganisms was 0.28; both are highly significant (p<0.001). In the first analysis correlations of the variables with the canonical variates revealed that correlations of the variables with the canonical variates revealed that sampling location, depth, and temperature are the primary environmental antecedents involved, and the criterion is primarily composed of mitesTarsonemus spp.,Tydeus interruptus and the psocid,Lepinotus reticulatus. In the second analysis the fungiNigrospora sphaerica, Aspergillus spp., andCochliobolus sativus are involved with the mitesCheyletus eruditus andAcarus siro. Generally, the results of these analyses complement the findings of factor and regression analyses of the same data reported earlier. Contribution No. 337 from the Research Station, Canada Department of Agriculture, Winnipeg, Manitoba.     

Spatially explicit survival modeling for small area cancer data

In this paper we propose a novel Bayesian statistical methodology for spatial survival data. Our methodology broadens the definition of the survival, density and hazard functions by explicitly modeling the spatial dependency using direct derivations of these functions and their marginals and conditionals. We also derive spatially dependent likelihood functions. Finally we examine the applications of these derivations with geographically augmented survival distributions in the context of the Louisiana Surveillance, Epidemiology, and End Results registry prostate cancer data.     

Trust and Information Sharing in Supply Chains

Drawing on behavioral research, we construct a multi‐period model with which to examine the role of trust and other social characteristics in a supply chain. Specifically, we focus on trust building in the context of a salesperson who acts as a representative of a manufacturer and shares demand forecast information with a retailer. The actions of the salesperson affect both her immediate economic gain and her future credibility as determined by retailer's trust. Our analysis reveals that, in such environments, although salespersons of widely varying types (e.g., honest, self‐serving, benevolent, loyal) lie some extent about their forecast information, they tend to be trusted in long relationships, provided their forecasting accuracy is higher than that of the retailer. Furthermore, while the presence of a salesperson can improve the profits of both the retailer and manufacturer, there are cost structures under which the manufacturer is better off without a salesperson. Finally, we make the general observation that the appropriate salesperson compensation scheme depends on her social characteristics, and the specific observation that when the salesperson cares for the retailer, the linear compensation scheme commonly suggested in the literature as the optimal compensation scheme for the salesperson is no longer optimal.