The Effects of Malpractice Pressure and Liability Reforms on Physicians’ Perceptions of Medical Care

Considerable evidence suggests that the medical malpractice liability system neither provides compensation to patients who suffer negligent medical injury nor seeks to penalize physicians whose negligence causes patient injury. The relationship between liability reforms, malpractice pressure and physician perceptions of medical care is examined

On the monotonicity of the correction term in Ramanujan's factorial approximation

We present two new proofs of the monotonicity of the correction term $\theta_n$ in Ramanujan's refinement of Stirling's formula.Comment: Latex, 5 page

Patient considerations in the management of ulcerative colitis: role of once-daily MMX mesalamine

Mesalamine and its derivatives are effective and well-tolerated therapies for ulcerative colitis. However, patient adherence to traditional mesalamine-based therapy is poor, and is often limited by heavy pill burdens and frequent dosing intervals. This can lead to ineffective disease control, impaired quality of life, and preventable morbidity and mortality. Previous studies have suggested that a once-daily mesalamine regimen would be strongly adhered to in the outpatient setting, but at that time no such formulation of mesalamine existed. In 2007, clinical trial data showed a novel, once-daily, multi-matrix (MMX) formulation of mesalamine to be effective in both remission induction and remission maintenance. This breakthrough in drug delivery allowed the unification of an effective therapeutic with a formulation that enables outpatients to be increasingly adherent to their medication. In theory, this might result in improved outpatient disease control and a decreased number of flares. As the use of MMX mesalamine increases, studies examining the outpatient community adherence rate need to be performed

Low-frequency 3D synthetic aperture radar for the remote intelligence of building interiors

Low-frequency (LF) synthetic aperture radar (SAR) images offer a viable approach to determining the architecture and contents of buildings and underground bunkers via remote sensing. Often however, standard 2D SAR images can be difficult to interpret due to component signatures from different heights being projected into the scene leading to confused results. In this research, measurement results have shown that the full Nyquist 2D aperture scan approach to 3D through-wall LF SAR provides focussed 3D resolution of a wall and contents behind it in a number of frequency bands. Full-scale radar system upgrades are ongoing in order to investigate numerous other scenarios, however in the meantime, sparse 2D aperture scanning investigations have been undertaken with a prototype radar scanner. Whilst this kind of collection cannot achieve the low sidelobe levels of full Nyquist 2D aperture collections, these prototype scanner measurements are much faster to collect, and have shown encouraging results of sufficient image quality to determine the 3D configuration of prominent features in the target scene, albeit with higher sidelobe or image artefact levels

Covariate Adjustment for the Intention-to-Treat Parameter with Empirical Efficiency Maximization

In randomized experiments, the intention-to-treat parameter is defined as the difference in expected outcomes between groups assigned to treatment and control arms. There is a large literature focusing on how (possibly misspecified) working models can sometimes exploit baseline covariate measurements to gain precision, although covariate adjustment is not strictly necessary. In Rubin and van der Laan (2008), we proposed the technique of empirical efficiency maximization for improving estimation by forming nonstandard fits of such working models. Considering a more realistic randomization scheme than in our original article, we suggest a new class of working models for utilizing covariate information, show our method can be implemented by adding weights to standard regression algorithms, and demonstrate benefits over existing estimators through numerical asymptotic efficiency calculations and simulations

Doubly Robust Ecological Inference

The ecological inference problem is a famous longstanding puzzle that arises in many disciplines. The usual formulation in epidemiology is that we would like to quantify an exposure-disease association by obtaining disease rates among the exposed and unexposed, but only have access to exposure rates and disease rates for several regions. The problem is generally intractable, but can be attacked under the assumptions of King\u27s (1997) extended technique if we can correctly specify a model for a certain conditional distribution. We introduce a procedure that it is a valid approach if either this original model is correct or if we can pose a correct model for a different conditional distribution. The new method is illustrated on data concerning risk factors for diabetes