The demography of disability and the effects of immigrant history: Older Asians in the United States

Using data from the 2000 U.S. census, we compare the older Asian population with U.S.-born, non-Hispanic whites with respect to three indicators of disability. Insofar as any Asian "advantage" in health vis-a-vis whites exists among the population aged 65 and over, our evidence suggests that it occurs primarily among the U.S.-born segments of this population. We also investigate how differences in disability levels among Asian immigrant groups are influenced by country of birth and by the combined effects of duration of residence in the United States and life cycle stage at entry. These results highlight the diversity of the older Asian population with respect to the ways in which immigration and origin history are linked to disability outcomes. We conclude that in later life, immigrant status confers few disability advantages among the Asian population in the United States.     

A PLURALITY MAXIMIZING APPROACH TO THE ALLOCATION OF CAMPAIGN RESOURCES

An important problem in the planning of political campaigns is the allocation of resources to precincts and other geographical voting units in order to maximize a candidate's plurality. Essentially, parties may increase candidate plurality by engaging in registration drives, midcampaign activities such as canvassing and candidate appearances, and get-out-the-vote drives. Based on previous work which has related voter response to party identification, the authors develop a model for the optimal allocation of campaign resources to these activities. The computational feasibility of the solution procedure is made possible by a decomposition across activities.     

A perspective of composite sampling

Composite samples are formed by physically mixing samples. Usually, composite samples are used to reduce the overall cost associated with analytical procedures that must be performed on each sample, but they can also be used to protect the privacy of individuals.

Composite sampling can reduce the cost of identifying individual cases that have a certain trait, such as those with a rare disease or those exceeding pollution-level standards. Not much is lost by applying this method as long as the trait is relatively rare.

Composite sampling can reduce the cost of estimating the mean of some process. When samples are composited, the ability to estimate the variance is lost. In spite of this, the potential savings are so great that composite samples have been used.

Much of this paper deasl with the variance of estimators based on composite sampling when the porportions of hte original samples comprising the composite sample are actually random. Taking repeated samples and measurements on several composite samples complicates the prodcedure, but allows the estimation of between and within variation as well as measurement error.     

Testing parameter of the power series distribution of a zero inflated power series model

The Zero Inflated Power Series Distribution (ZIPSD) contains two parameters. The first parameter indicates inflation of zero and the other parameter is that of the Power Series distribution. We provide three asymptotic tests for testing the parameter of Power Series distribution, using an unconditional (standard) likelihood approach, a conditional likelihood approach and a test based on sample mean, respectively. The performance of these three tests has been studied for Zero Inflated Poisson Distribution (ZIPD). Asymptotic Confidence Intervals for the parameter are also provided.     

NGO Failure: A Theoretical Synthesis

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - An extensive literature identifies conditions under which markets and states work efficiently and effectively toward their...     

Approximating probability density functions in hybrid Bayesian networks with mixtures of truncated exponentials

Mixtures of truncated exponentials (MTE) potentials are an alternative to discretization and Monte Carlo methods for solving hybrid Bayesian networks. Any probability density function (PDF) can be approximated by an MTE potential, which can always be marginalized in closed form. This allows propagation to be done exactly using the Shenoy-Shafer architecture for computing marginals, with no restrictions on the construction of a join tree. This paper presents MTE potentials that approximate standard PDF’s and applications of these potentials for solving inference problems in hybrid Bayesian networks. These approximations will extend the types of inference problems that can be modelled with Bayesian networks, as demonstrated using three examples.     

On additive and multiplicative damage models and the characterizations of linear and logarithmic exponential families

Rao (1963) has formulated a damage model which we call an additive damage model. A suitable damage model, which we call a multiplicative damage model, has been considered by Krishnaji (1970) for income-related problems. In these models, an original observation is subjected to damage, e.g., death or under-reporting, according to a specified probability law. Within the framework of an additive damage model, with a special form of damage, characterizations of the linear and logarithmic exponential families are formulated using regression properties of the damaged part on the undamaged part. The characterizations of the gamma and Pareto distributions that have been found of some use in the theory of income distributions, are obtained as special cases. Similar results are investigated within the framework of the multiplicative damage model.     

Variable Bandwidths for Nonparametric Hazard Rate Estimation

A smoothing parameter inversely proportional to the square root of the true density is known to produce kernel estimates of the density having faster bias rate of convergence. We show that in the case of kernel-based nonparametric hazard rate estimation, a smoothing parameter inversely proportional to the square root of the true hazard rate leads to a mean square error rate of order n ^?8/9, an improvement over the standard second order kernel. An adaptive version of such a procedure is considered and analyzed.