Genotypic performance over environmental arrays: A non-linear grouping protocol

A non-linear model for examining genotypic responses across an array of environments is contrasted with the 'joint regression' formulation, and a rigorous approach to hypothesis testing using the conditional error principle is demonstrated. The model is extended to cater for situations where single straight-line response patterns fail to characterize genotypic behaviors over an environmental array: a combination of two straight lines, with slope in below-average and in above-average environments, is offered as the 1 2 simplest representation of convex and concave patterns. A protocol for classifying genotypes according to the results of hypothesis tests, i.e. H( = ) and H( = = = 1), is 1 2 1 2 presented . A doubly desirable response pattern is convex ( < 1< ), while a doubly 1 2 undesirable pattern is concave ( > 1> ). 1 2     

Sample selection in radiocarbon dating

Archaeologists working on the island of O'ahu, Hawai'i, use radiocarbon dating of samples of organic matter found trapped in fish-pond sediments to help them to learn about the chronology of the construction and use of the aquicultural systems created by the Polynesians. At one particular site, Loko Kuwili, 25 organic samples were obtained and funds were available to date an initial nine. However, on calibration to the calendar scale, the radiocarbon determinations provided date estimates that had very large variances. As a result, major issues of chronology remained unresolved and the archaeologists were faced with the prospect of another expensive programme of radiocarbon dating. This paper presents results of research that tackles the problems associated with selecting samples from those which are still available. Building on considerable recent research that utilizes Markov chain Monte Carlo methods to aid archaeologists in their radiocarbon calibration and interpretation, we adopt the standard Bayesian framework of risk functions, which allows us to assess the optimal samples to be sent for dating. Although rather computer intensive, our algorithms are simple to implement within the Bayesian radiocarbon framework that is already in place and produce results that are capable of direct interpretation by the archaeologists. By dating just three more samples from Loko Kuwili the expected variance on the date of greatest interest could be substantially reduced.     

Spatial variation in risk of disease: a nonparametric binary regression approach

A common problem in environmental epidemiology is the estimation and mapping of spatial variation in disease risk. In this paper we analyse data from the Walsall District Health Authority, UK, concerning the spatial distributions of cancer cases compared with controls sampled from the population register. We formulate the risk estimation problem as a nonparametric binary regression problem and consider two different methods of estimation. The first uses a standard kernel method with a cross-validation criterion for choosing the associated bandwidth parameter. The second uses the framework of the generalized additive model (GAM) which has the advantage that it can allow for additional explanatory variables, but is computationally more demanding. For the Walsall data, we obtain similar results using either the kernel method with controls stratified by age and sex to match the age–sex distribution of the cases or the GAM method with random controls but incorporating age and sex as additional explanatory variables. For cancers of the lung or stomach, the analysis shows highly statistically significant spatial variation in risk. For the less common cancers of the pancreas, the spatial variation in risk is not statistically significant.     

Application of Markov chain Monte Carlo methods to modelling birth prevalence of Down syndrome

Data collected before the routine application of prenatal screening are of unique value in estimating the natural live-birth prevalence of Down syndrome. However, much of these data are from births from over 20 years ago and they are of uncertain quality. In particular, they are subject to varying degrees of underascertainment. Published approaches have used ad hoc corrections to deal with this problem or have been restricted to data sets in which ascertainment is assumed to be complete. In this paper we adopt a Bayesian approach to modelling ascertainment and live-birth prevalence. We consider three prior specifications concerning ascertainment and compare predicted maternal-age-specific prevalence under these three different prior specifications. The computations are carried out by using Markov chain Monte Carlo methods in which model parameters and missing data are sampled.     

Efficient Estimation of a Distribution Function under Quadrant Dependence

LetX₁,X₂, ..., be real-valued random variables forming a strictly stationary sequence, and satisfying the basic requirement of being either pairwise positively quadrant dependent or pairwise negatively quadrant dependent. LetF^ be the marginal distribution function of theX_ips, which is estimated by the empirical distribution functionF_n and also by a smooth kernel-type estimateF_n, by means of the segmentX₁, ...,X_n. These estimates are compared on the basis of their mean squared errors (MSE). The main results of this paper are the following. Under certain regularity conditions, the optimal bandwidth (in the MSE sense) is determined, and is found to be the same as that in the independent identically distributed case. It is also shown thatn MSE(F_n(t)) andnMSE (F^_n(t)) tend to the same constant, asn→∞ so that one can not discriminate be tween the two estimates on the basis of the MSE. Next, ifi(n) = min {k∈{1, 2, ...}; MSE (F_k(t)) ≤ MSE (F_n(t))}, then it is proved thati(n)/n tends to 1, asn→∞. Thus, once again, one can not choose one estimate over the other in terms of their asymptotic relative efficiency. If, however, the squared bias ofF^_n(t) tends to 0 sufficiently fast, or equivalently, the bandwidthh_n satisfies the requirement thatnh³_n→ 0, asn→∞, it is shown that, for a suitable choice of the kernel, (i(n) ?n)/(nh_n) tends to a positive number, asn→∞ It follows that the deficiency ofF_n(t) with respect toF^_n(t),i(n) ?n, is substantial, and, actually, tends to ∞, asn→∞. In terms of deficiency, the smooth estimateF^_n(t) is preferable to the empirical distribution functionF_n(t)     

Fit and Skill in Employee Selection: Insights from a Study of Headhunters

We draw upon evidence from a qualitative study of headhunters to provide insights into the character and importance of candidate fit and skill for the selection of a broad range of white-collar employees. Headhunters suggest that the fit of a job candidate is assessed at two levels, one corresponding with a general compatibility with organization-level norms, culture, and strategy, the other corresponding more closely with traits and characteristics of the person or persons with whom the job candidate actually interviews. Skill—a factor which is largely neglected by those who tout the importance of fit—also plays an important and independent role in employee selection. Stalls that influence the selection of employees from a pool of candidates tend to be highly specific if not idiosyncratic, and take the form of what headhunters call hot buttons. We conclude by discussing the conceptualization, causes, and implications of fit; we also consider how the importance of fit and hot buttons challenges the explanatory logic of standard accounts of labor-market success.     

Physician-sponsored networks. Will physicians take back medicine?

Until about the late 1980s, American physicians and their allies, hospitals and the health care manufacturing industries, dominated all facets of the health system--the clinical, the economic, and the political. The bulk of these providers' revenue flowed to them from a highly fragmented insurance system whose governing principle was to provide each insured patient free choice of doctor and hospital. Two distinct, concurrent shifts threaten to erode the medical profession's traditional dominance. The first is a rapid, general shift of control from the supply side of the health sector to its demand side. The second is a shift away from government control, over which organized medicine held much sway in the past, toward private regulators--the executives of the managed care industry. Is the trend towards greater dependence of practicing physicians on non-physician executives inevitable, or can physicians retain--and, in part, regain--their hitherto autonomous position in the health system?     

Will you be ready when the pink slip arrives?

Are you prepared to ride the waves of change? Will you be ready when the pink slip arrives? Health care executives who can jump a little higher and run a little faster will go further in the draft. Those of you who are prepared for change will always be appealing to recruiters and prospective employers. How can you ride these turbulent waves and not capsize? This article explores some suggestions for positioning yourself: Proper positioning with the inevitable changes in mind will help you move your career in a forward direction.     

The medical practice as business organization

Medical practices historically have not been examined in terms of their organizational structures and of the appropriateness of their structures for survival as business entities. In this paper, we propose a model for the typical medical practice and discuss its fit with current organizational theory. It is apparent that the medical practice organization does not fit with the demands of a rapidly changing and complex environment. To survive and grow, the medical practice organization must align itself with others that have an interest and stake in the health care system, develop teamwork among physicians, bridge the gap between physicians and others in the organization, and recognize that the work done in the organization depends on other components of the organization.     

The computerized patient record and confidentiality. The nabobs of negativism are wrong

The handwritten medical record has been the method of choice for documenting health care data since the last millennium. Given this successful tenure, it would be natural to greet any new information system that purports to be an advancement with skepticism. Moreover, physicians as a group are hardly progressive. Yet health care is taking a giant leap and is finally accepting computerization. The advantages and drawbacks of computerized information systems have long been thoroughly tested in such diverse industries as the military, banking, and the airlines. It is difficult to imagine any of these industries in their modern form without an advanced information system.