Estimating medical costs from a transition model

Nonparametric estimators of the mean total cost have been proposed in a variety of settings. In clinical trials it is generally impractical to follow up patients until all have responded, and therefore censoring of patient outcomes and total cost will occur in practice. We describe a general longitudinal framework in which costs emanate from two streams, during sojourn in health states and in transition from one health state to another. We consider estimation of net present value for expenditures incurred over a finite time horizon from medical cost data that might be incompletely ascertained in some patients. Because patient specific demographic and clinical characteristics would influence total cost, we use a regression model to incorporate covariates. We discuss similarities and differences between our net present value estimator and other widely used estimators of total medical costs. Our model can accommodate heteroscedasticity, skewness and censoring in cost data and provides a flexible approach to analyses of health care cost.Comment: Published in at http://dx.doi.org/10.1214/193940307000000266 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

A superconducting microwave multivibrator produced by coherent feedback

We investigate a coherent nonlinear feedback circuit constructed from pre-existing superconducting microwave devices. The network exhibits emergent bistable and astable states, and we demonstrate its operation as a latch and the frequency locking of its oscillations. While the network is tedious to model by hand, our observations agree quite well with the semiclassical dynamical model produced by a new software package [N. Tezak et al., arXiv:1111.3081v1] that systematically interpreted an idealized schematic of the system as a quantum optic feedback network.Comment: 9 double-spaced pages, 5 figures and supplement. To appear in Phys. Rev. Let

Efficient multiple time scale molecular dynamics: using colored noise thermostats to stabilize resonances

Multiple time scale molecular dynamics enhances computational efficiency by updating slow motions less frequently than fast motions. However, in practice the largest outer time step possible is limited not by the physical forces but by resonances between the fast and slow modes. In this paper we show that this problem can be alleviated by using a simple colored noise thermostatting scheme which selectively targets the high frequency modes in the system. For two sample problems, flexible water and solvated alanine dipeptide, we demonstrate that this allows the use of large outer time steps while still obtaining accurate sampling and minimizing the perturbation of the dynamics. Furthermore, this approach is shown to be comparable to constraining fast motions, thus providing an alternative to molecular dynamics with constraints.Comment: accepted for publication by the Journal of Chemical Physic

Magnet field sensing beyond the standard quantum limit under the effect of decoherence

Entangled states can potentially be used to outperform the standard quantum limit which every classical sensor is bounded by. However, entangled states are very susceptible to decoherence, and so it is not clear whether one can really create a superior sensor to classical technology via a quantum strategy which is subject to the effect of realistic noise. This paper presents an investigation of how a quantum sensor composed of many spins is affected by independent dephasing. We adopt general noise models including non-Markovian effects, and in these noise models the performance of the sensor depends crucially on the exposure time of the sensor to the field. We have found that, by choosing an appropriate exposure time within non-Markovian time region, an entangled sensor does actually beat the standard quantum limit. Since independent dephasing is one of the most typical sources of noise in many systems, our results suggest a practical and scalable approach to beating the standard quantum limit

Intrinsic noise and discrete-time processes

A general formalism is developed to construct a Markov chain model that converges to a one-dimensional map in the infinite population limit. Stochastic fluctuations are therefore internal to the system and not externally specified. For finite populations an approximate Gaussian scheme is devised to describe the stochastic fluctuations in the non-chaotic regime. More generally, the stochastic dynamics can be captured using a stochastic difference equation, derived through an approximation to the Markov chain. The scheme is demonstrated using the logistic map as a case study.Comment: Modified version accepted for publication in Phys. Rev. E Rapid Communications. New figures adde

Efficient growth of complex graph states via imperfect path erasure

Given a suitably large and well connected (complex) graph state, any quantum algorithm can be implemented purely through local measurements on the individual qubits. Measurements can also be used to create the graph state: Path erasure techniques allow one to entangle multiple qubits by determining only global properties of the qubits. Here, this powerful approach is extended by demonstrating that even imperfect path erasure can produce the required graph states with high efficiency. By characterizing the degree of error in each path erasure attempt, one can subsume the resulting imperfect entanglement into an extended graph state formalism. The subsequent growth of the improper graph state can be guided, through a series of strategic decisions, in such a way as to bound the growth of the error and eventually yield a high-fidelity graph state. As an implementation of these techniques, we develop an analytic model for atom (or atom-like) qubits in mismatched cavities, under the double-heralding entanglement procedure of Barrett and Kok [Phys. Rev. A 71, 060310 (2005)]. Compared to straightforward postselection techniques our protocol offers a dramatic improvement in growing complex high-fidelity graph states.Comment: 15 pages, 10 figures (which print to better quality than when viewed as an on screen pdf

A Study of the Persistence of Mycobacterium bovis in the Environment under Natural Weather Conditions in Michigan, USA

Reisolation of Mycobacterium bovis from inoculated substrates was used to follow the persistence of viable M. bovis bacteria exposed to natural weather conditions over a 12-month period. Environmental factors were recorded continuously, and factors affecting M. bovis persistence (i.e., temperature, season, and substrate) were studied using survival analysis and Cox's proportional hazards regression. Persistence of M. bovis in the environment was significantly shorter in the spring/summer season, characterized by the highest average daily temperatures over the 12-month period. M. bovis persisted up to 88 days in soil, 58 days in water and hay, and 43 days on corn. These studies demonstrate that M. bovis bacteria persist long enough to represent a risk of exposure for cattle and/or wildlife and strengthen evidence that suggests cattle farm biosecurity and efforts to eliminate supplemental feeding of white-tailed deer will decrease the risk of bovine TB transmission among and between cattle and deer populations

Longitudinal analysis of censored medical cost data

This paper applies the inverse probability weighted (IPW) least-squares method to estimate the effects of treatment on total medical cost, subject to censoring, in a panel-data setting. IPW pooled ordinary-least squares (POLS) and IPW random effects (RE) models are used. Because total medical cost might not be independent of survival time under administrative censoring, unweighted POLS and RE cannot be used with censored data, to assess the effects of certain explanatory variables. Even under the violation of this independency, IPW estimation gives consistent asymptotic normal coefficients with easily computable standard errors. A traditional and robust form of the Hausman test can be used to compare weighted and unweighted least squares estimators. The methods are applied to a sample of 201 Medicare beneficiaries diagnosed with lung cancer between 1994 and 1997

Thermal Flipping of Interstellar Grains

In interstellar dust grains, internal processes dissipate rotational kinetic energy. The dissipation is accompanied by thermal fluctuations, which transfer energy from the vibrational modes to rotation. Together, these processes are known as internal relaxation. For the past several years, internal relaxation has been thought to give rise to thermal flipping, with profound consequences for grain alignment theory. I show that thermal flipping is not possible in the limit that the inertia tensor does not vary with time.Comment: 5 pages, accepted by Ap