Estimating Marginal Hazard Ratios by Simultaneously Using A Set of Propensity Score Models: A Multiply Robust Approach

The inverse probability weighted Cox model is frequently used to estimate marginal hazard ratios. Its validity requires a crucial condition that the propensity score model is correctly specified. To provide protection against misspecification of the propensity score model, we propose a weighted estimation method rooted in empirical likelihood theory. The proposed estimator is multiply robust in that it is guaranteed to be consistent when a set of postulated propensity score models contains a correctly specified model. Our simulation studies demonstrate satisfactory finite sample performance of the proposed method in terms of consistency and efficiency. We apply the proposed method to compare the risk of postoperative hospitalization between sleeve gastrectomy and Roux-en-Y gastric bypass using data from a large medical claims and billing database.We further extend the development to multi-site studies to enable each site to postulate multiple site-specific propensity score models

Revisiting sample size planning for receiver operating characteristic studies: a confidence interval approach with precision and assurance

Objectives: Estimation of areas under receiver operating characteristic curves (AUCs) and their differences is a key task in diagnostic studies. We aimed to derive, evaluate, and implement simple sample size formulas for such studies with a focus on estimation rather than hypothesis testing. Materials and Methods: Sample size formulas were developed by explicitly incorporating pre-specified precision and assurance, with precision denoted by the lower limit of confidence interval and assurance denoted by the probability of achieving that lower limit. A new variance function was proposed for valid estimation allowing for unequal variances of observations in the disease and non-disease groups. Performance of the proposed formulas was evaluated through simulation. Results: Closed-form sample size formulas were obtained. Simulation results demonstrated that the proposed formulas produced empirical assurance probability close to the pre-specified assurance probability and empirical coverage probability close to the nominal 95%. Real-world worked examples were presented for illustration. Conclusions: Sample size formulas based on estimation of AUCs and their differences were developed. Simulation results suggested good performance in terms of achieving pre-specified precision and assurance probability. An online calculator for implementing the proposed formulas is openly available at https://dishu.page/calculator/.Comment: 28 pages, 3 table

Modeling the magnetic field in the protostellar source NGC 1333 IRAS 4A

Magnetic fields are believed to play a crucial role in the process of star formation. We compare high-angular resolution observations of the submillimeter polarized emission of NGC 1333 IRAS 4A, tracing the magnetic field around a low-mass protostar, with models of the collapse of magnetized molecular cloud cores. Assuming a uniform dust alignment efficiency, we computed the Stokes parameters and synthetic polarization maps from the model density and magnetic field distribution by integrations along the line-of-sight and convolution with the interferometric response. The synthetic maps are in good agreement with the data. The best-fitting models were obtained for a protostellar mass of 0.8 solar masses, of age 9e4 yr, formed in a cloud with an initial mass-to-flux ratio ~2 times the critical value. The magnetic field morphology in NGC 1333 IRAS 4A is consistent with the standard theoretical scenario for the formation of solar-type stars, where well-ordered, large-scale, rather than turbulent, magnetic fields control the evolution and collapse of the molecular cloud cores from which stars form.Comment: 4 pages, 5 figures. Accepted by Astronomy and Astrophysic

From Filamentary Networks to Dense Cores in Molecular Clouds: Toward a New Paradigm for Star Formation

Recent studies of the nearest star-forming clouds of the Galaxy at submillimeter wavelengths with the Herschel Space Observatory have provided us with unprecedented images of the initial and boundary conditions of the star formation process. The Herschel results emphasize the role of interstellar filaments in the star formation process and connect remarkably well with nearly a decade's worth of numerical simulations and theory that have consistently shown that the ISM should be highly filamentary on all scales and star formation is intimately related to self-gravitating filaments. In this review, we trace how the apparent complexity of cloud structure and star formation is governed by relatively simple universal processes - from filamentary clumps to galactic scales. We emphasize two crucial and complementary aspects: (i) the key observational results obtained with Herschel over the past three years, along with relevant new results obtained from the ground on the kinematics of interstellar structures, and (ii) the key existing theoretical models and the many numerical simulations of interstellar cloud structure and star formation. We then synthesize a comprehensive physical picture that arises from the confrontation of these observations and simulations.Comment: 24 pages, 15 figures. Accepted for publication as a review chapter in Protostars and Planets VI, University of Arizona Press (2014), eds. H. Beuther, R. Klessen, C. Dullemond, Th. Hennin