Chandra and Far Ultraviolet Spectroscopic Explorer Observations of z~0 Warm-Hot Gas Toward PKS 2155-304

The X-ray bright z=0.116 quasar PKS 2155-304 is frequently observed as a Chandra calibration source, with a total of 483 ksec of Low Energy Transmission Grating (LETG) exposure time accumulated through May 2006. Highly-ionized metal absorption lines, including numerous lines at z=0 and a putative OVIII K-alpha line at z=0.055, have been reported in past Chandra studies of this source. Using all available Chandra LETG spectra and analysis techniques developed for such z=0 X-ray absorption along other sightlines, we revisit these previous detections. We detect 4 absorption lines at >3\sigma significance (OVII K-alpha/beta, OVIII K-alpha, and NeIX K-alpha), with OVII K-alpha being a 7.3\sigma detection. The 1\sigma ranges of z=0 OVII column density and Doppler parameter are consistent with those derived for Mrk 421 and within 2\sigma of the Mrk 279 absorption. Temperatures and densities inferred from the relative OVII and other ionic column densities are found to be consistent with either the local warm-hot intergalactic medium or a Galactic corona. Unlike the local X-ray absorbers seen in other sightlines, a link with the low- or high-velocity far-ultraviolet OVI absorption lines cannot be ruled out. The z=0.055 OVIII absorption reported by Fang et al. is seen with 3.5\sigma confidence in the ACIS/LETG spectrum, but no other absorption lines are found at the same redshift.Comment: 11 pages, 9 figures; minor changes, accepted to Ap

Sensitivity Analysis for Unmeasured Confounding in Meta-Analyses

Random-effects meta-analyses of observational studies can produce biased estimates if the synthesized studies are subject to unmeasured confounding. We propose sensitivity analyses quantifying the extent to which unmeasured confounding of specified magnitude could reduce to below a certain threshold the proportion of true effect sizes that are scientifically meaningful. We also develop converse methods to estimate the strength of confounding capable of reducing the proportion of scientifically meaningful true effects to below a chosen threshold. These methods apply when a "bias factor" is assumed to be normally distributed across studies or is assessed across a range of fixed values. Our estimators are derived using recently proposed sharp bounds on confounding bias within a single study that do not make assumptions regarding the unmeasured confounders themselves or the functional form of their relationships to the exposure and outcome of interest. We provide an R package, ConfoundedMeta, and a freely available online graphical user interface that compute point estimates and inference and produce plots for conducting such sensitivity analyses. These methods facilitate principled use of random-effects meta-analyses of observational studies to assess the strength of causal evidence for a hypothesis