The potential for bias in principal causal effect estimation when treatment received depends on a key covariate

Motivated by a potential-outcomes perspective, the idea of principal stratification has been widely recognized for its relevance in settings susceptible to posttreatment selection bias such as randomized clinical trials where treatment received can differ from treatment assigned. In one such setting, we address subtleties involved in inference for causal effects when using a key covariate to predict membership in latent principal strata. We show that when treatment received can differ from treatment assigned in both study arms, incorporating a stratum-predictive covariate can make estimates of the "complier average causal effect" (CACE) derive from observations in the two treatment arms with different covariate distributions. Adopting a Bayesian perspective and using Markov chain Monte Carlo for computation, we develop posterior checks that characterize the extent to which incorporating the pretreatment covariate endangers estimation of the CACE. We apply the method to analyze a clinical trial comparing two treatments for jaw fractures in which the study protocol allowed surgeons to overrule both possible randomized treatment assignments based on their clinical judgment and the data contained a key covariate (injury severity) predictive of treatment received.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS477 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Causal Impact of the Hospital Readmissions Reduction Program on Hospital Readmissions and Mortality

Estimating causal effects of the Hospital Readmissions Reduction Program (HRRP), part of the Affordable Care Act, has been very controversial. Associational studies have demonstrated decreases in hospital readmissions, consistent with the intent of the program, although analyses with different data sources and methods have differed in estimating effects on patient mortality. To address these issues, we define the estimands of interest in the context of potential outcomes, we formalize a Bayesian structural time-series model for causal inference, and discuss the necessary assumptions for estimation of effects using observed data. The method is used to estimate the effect of the passage of HRRP on both the 30-day readmissions and 30-day mortality. We show that for acute myocardial infarction and congestive heart failure, HRRP caused reduction in readmissions while it had no statistically significant effect on mortality. However, for pneumonia, HRRP had no statistically significant effect on readmissions but caused an increase in mortality.Comment: 10 pages, 1 figure, 2 table

Causal health impacts of power plant emission controls under modeled and uncertain physical process interference

Causal inference with spatial environmental data is often challenging due to the presence of interference: outcomes for observational units depend on some combination of local and non-local treatment. This is especially relevant when estimating the effect of power plant emissions controls on population health, as pollution exposure is dictated by (i) the location of point-source emissions, as well as (ii) the transport of pollutants across space via dynamic physical-chemical processes. In this work, we estimate the effectiveness of air quality interventions at coal-fired power plants in reducing two adverse health outcomes in Texas in 2016: pediatric asthma ED visits and Medicare all-cause mortality. We develop methods for causal inference with interference when the underlying network structure is not known with certainty and instead must be estimated from ancillary data. We offer a Bayesian, spatial mechanistic model for the interference mapping which we combine with a flexible non-parametric outcome model to marginalize estimates of causal effects over uncertainty in the structure of interference. Our analysis finds some evidence that emissions controls at upwind power plants reduce asthma ED visits and all-cause mortality, however accounting for uncertainty in the interference renders the results largely inconclusive.Comment: 22 pages, 5 figures. Associated code and supplementary material can be found at https://github.com/nbwikle/estimating-interferenc

Acceleration Of Protons To Above 6 MeV Using H2O >Snow> Nanowire Targets

A scheme is presented for using H2O >snow> nanowire targets for the generation of fast protons. This novel method may relax the requirements for very high laser intensities, thus reducing the size and cost of laser based ion acceleration system.Physic

Characterization of self-injected electron beams from LWFA experiments at SPARC_LAB

The plasma-based acceleration is an encouraging technique to overcome the limits of the accelerating gradient in the conventional RF acceleration. A plasma accelerator is able to provide accelerating fields up to hundreds of $GeV/m$, paving the way to accelerate particles to several MeV over a short distance (below the millimetre range). Here the characteristics of preliminary electron beams obtained with the self-injection mechanism produced with the FLAME high-power laser at the SPARC_LAB test facility are shown. In detail, with an energy laser on focus of $1.5\ J$ and a pulse temporal length (FWHM) of $40\ fs$, we obtained an electron plasma density due to laser ionization of about $6 \times 10^{18}\ cm^{-3}$, electron energy up to $350\ MeV$ and beam charge in the range $(50 - 100)\ pC$.Comment: 6 pages, 11 figures, conference EAAC201

5.5-7.5 MeV Proton generation by a moderate intensity ultra-short laser interaction with H2O nano-wire targets

We report on the first generation of 5.5-7.5 MeV protons by a moderate intensity short-pulse laser (4.5 \times 1017 W/cm^2, 50 fsec) interacting with H2O nano-wires (snow) deposited on a Sapphire substrate. In this setup, the laser intensity is locally enhanced by the tip of the snow nano-wire, leading to high spatial gradients. Accordingly, the plasma near the tip is subject to enhanced ponderomotive potential, and confined charge separation is obtained. Electrostatic fields of extremely high intensities are produced over the short scale length, and protons are accelerated to MeV-level energies.Comment: submitted to PRL, under press embargo. 6 figure