THE WELFARE IMPLICATIONS OF MORAL HAZARD AND ADVERSE SELECTION IN COMPETITIVE INSURANCE MARKETS

I model a competitive insurance market with both moral hazard and adverse selection, and analyze the effect on welfare when both problems are present simultaneously. An examination of the interaction between these two problems leads to two hypotheses. First, the nature of the equilibrium contracts is such that each problem partially offsets the welfare loss associated with the other. And second, the degree to which this occurs increases as agents become more heterogeneous. Simulation results overwhelmingly support both hypotheses.     

Nonresponse weighting adjustment using estimated response probability

To reduce nonresponse bias in sample surveys, a method of nonresponse weighting adjustment is often used which consists of multiplying the sampling weight of the respondent by the inverse of the estimated response probability. The authors examine the asymptotic properties of this estimator. They prove that it is generally more efficient than an estimator which uses the true response probability, provided that the parameters which govern this probability are estimated by maximum likelihood. The authors discuss variance estimation methods that account for the effect of using the estimated response probability; they compare their performances in a small simulation study. They also discuss extensions to the regression estimator.     

A model for short-term group therapy on a children's inpatient unit

The paper describes the group therapy model which has evolved over the past two years on the Child Psychiatry Inpatient Unit of North Carolina Memorial Hospital. It begins with a brief review of the literature concerning group therapy with latency-aged children. The setting and patient population are described. Vignettes from group sessions are used to illustrate techniques which have evolved to deal with this particular setting and population. These include a leadership style characterized by much clarification, modeling, and limit setting; extensive focus on beginning and terminating; clearly defined behavioral limits; the use of time out; and use of play materials requiring little skill or attention as anxiety binders as well as projective media; and observation and supervisory discussions open to all members of the treatment team. The paper concludes with a discussion of the potentials and limitations of group therapy in such a setting. The thesis is that this model is effective in diagnosing developmental levels, in developing interpersonal skills, in substituting verbalization for action, and in mastering separation anxieties, though the setting limits the extent to which controlled regression, transference, and group pressures can develop and be used to produce change.     

Faster algorithm to find anti-risk path between two nodes of an undirected graph

For a weighted 2-edge connected graph G=(V,E), we are to find a “minimum risk path” from source s to destination t. This is a shortest s?t path under the assumption that at most one edge on the path may be blocked. The fact that the edge is blocked is known only when we reach a site adjacent to the blocked edge. If n and m are the number of nodes and edges of G, then we show that this problem can be solved in O(n ²) time using only simple data structures. This is an improvement over the previous O(mn+n ²logn) time algorithm. Moreover, with use of more complicated data structures like Fibonacci Heaps and transmuters the time can be further reduced to O(m+nlogn).     

Utilizing Bayesian predictive power in clinical trial design

The Bayesian paradigm provides an ideal platform to update uncertainties and carry them over into the future in the presence of data. Bayesian predictive power (BPP) reflects our belief in the eventual success of a clinical trial to meet its goals. In this paper we derive mathematical expressions for the most common types of outcomes, to make the BPP accessible to practitioners, facilitate fast computations in adaptive trial design simulations that use interim futility monitoring, and propose an organized BPP-based phase II-to-phase III design framework.     

Volunteering in Retirement and Its Impact on Seniors Subjective Quality of Life Through Personal Outlook: A Study of Older Australians

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This study examines the subjective quality of life of globally expanding senior citizens post-retirement, from a...     

An update on ‘a comparative study of tests for homogeneity of variance’

Tests for equality of variances using independent samples are widely used in data analysis. Conover et al. [A comparative study of tests for homogeneity of variance, with applications to the outer continental shelf bidding data. Technometrics. 1981;23:351–361], won the Youden Prize by comparing 56 variations of popular tests for variance on the basis of robustness and power in 60 different scenarios. None of the tests they compared were robust and powerful for the skewed distributions they considered. This study looks at 12 variations they did not consider, and shows that 10 are robust for the skewed distributions they considered plus the lognormal distribution, which they did not study. Three of these 12 have clearly superior power for skewed distributions, and are competitive in terms of robustness and power for all of the distributions considered. They are recommended for general use based on robustness, power, and ease of application.     

A Rejection Principle for Sequential Tests of Multiple Hypotheses Controlling Familywise Error Rates

We present a unifying approach to multiple testing procedures for sequential (or streaming) data by giving sufficient conditions for a sequential multiple testing procedure to control the familywise error rate (FWER). Together, we call these conditions a ‘rejection principle for sequential tests’, which we then apply to some existing sequential multiple testing procedures to give simplified understanding of their FWER control. Next, the principle is applied to derive two new sequential multiple testing procedures with provable FWER control, one for testing hypotheses in order and another for closed testing. Examples of these new procedures are given by applying them to a chromosome aberration data set and finding the maximum safe dose of a treatment.