Maximum likelihood and pseudo score approaches for parametric time-to-event analysis with informative entry times

We develop a maximum likelihood estimating approach for time-to-event Weibull regression models with outcome-dependent sampling, where sampling of subjects is dependent on the residual fraction of the time left to developing the event of interest. Additionally, we propose a two-stage approach which proceeds by iteratively estimating, through a pseudo score, the Weibull parameters of interest (i.e., the regression parameters) conditional on the inverse probability of sampling weights; and then re-estimating these weights (given the updated Weibull parameter estimates) through the profiled full likelihood. With these two new methods, both the estimated sampling mechanism parameters and the Weibull parameters are consistently estimated under correct specification of the conditional referral distribution. Standard errors for the regression parameters are obtained directly from inverting the observed information matrix in the full likelihood specification and by either calculating bootstrap or robust standard errors for the hybrid pseudo score/profiled likelihood approach. Loss of efficiency with the latter approach is considered. Robustness of the proposed methods to misspecification of the referral mechanism and the time-to-event distribution is also briefly examined. Further, we show how to extend our methods to the family of parametric time-to-event distributions characterized by the generalized gamma distribution. The motivation for these two approaches came from data on time to cirrhosis from hepatitis C viral infection in patients referred to the Edinburgh liver clinic. We analyze these data here.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS725 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Synthesising evidence to estimate pandemic (2009) A/H1N1 influenza severity in 2009-2011

Knowledge of the severity of an influenza outbreak is crucial for informing and monitoring appropriate public health responses, both during and after an epidemic. However, case-fatality, case-intensive care admission and case-hospitalisation risks are difficult to measure directly. Bayesian evidence synthesis methods have previously been employed to combine fragmented, under-ascertained and biased surveillance data coherently and consistently, to estimate case-severity risks in the first two waves of the 2009 A/H1N1 influenza pandemic experienced in England. We present in detail the complex probabilistic model underlying this evidence synthesis, and extend the analysis to also estimate severity in the third wave of the pandemic strain during the 2010/2011 influenza season. We adapt the model to account for changes in the surveillance data available over the three waves. We consider two approaches: (a) a two-stage approach using posterior distributions from the model for the first two waves to inform priors for the third wave model; and (b) a one-stage approach modelling all three waves simultaneously. Both approaches result in the same key conclusions: (1) that the age-distribution of the case-severity risks is "u"-shaped, with children and older adults having the highest severity; (2) that the age-distribution of the infection attack rate changes over waves, school-age children being most affected in the first two waves and the attack rate in adults over 25 increasing from the second to third waves; and (3) that when averaged over all age groups, case-severity appears to increase over the three waves. The extent to which the final conclusion is driven by the change in age-distribution of those infected over time is subject to discussion.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS775 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The On-Orbit Performance of the Galaxy Evolution Explorer

We report the first year on-orbit performance results for the Galaxy Evolution Explorer (GALEX), a NASA Small Explorer that is performing a survey of the sky in two ultraviolet bands. The instrument comprises a 50 cm diameter modified Ritchey-Chretien telescope with a 1.25 degree field of view, selectable imaging and objective grism spectroscopic modes, and an innovative optical system with a thin-film multilayer dichroic beam splitter that enables simultaneous imaging by a pair of photon counting, microchannel plate, delay line readout detectors. Initial measurements demonstrate that GALEX is performing well, meeting its requirements for resolution, efficiency, astrometry, bandpass definition and survey sensitivity.Comment: This paper will be published as part of the Galaxy Evolution Explorer (GALEX) Astrophysical Journal Letters Special Issu

Disease Modelling of Cognitive Outcomes and Biomarkers in the European Prevention of Alzheimer’s Dementia Longitudinal Cohort

A key challenge for the secondary prevention of Alzheimer’s dementia is the need to identify individuals early on in the disease process through sensitive cognitive tests and biomarkers. The European Prevention of Alzheimer’s Dementia (EPAD) consortium recruited participants into a longitudinal cohort study with the aim of building a readiness cohort for a proof-of-concept clinical trial and also to generate a rich longitudinal data-set for disease modelling. Data have been collected on a wide range of measurements including cognitive outcomes, neuroimaging, cerebrospinal fluid biomarkers, genetics and other clinical and environmental risk factors, and are available for 1,828 eligible participants at baseline, 1,567 at 6 months, 1,188 at one-year follow-up, 383 at 2 years, and 89 participants at three-year follow-up visit. We novelly apply state-of-the-art longitudinal modelling and risk stratification approaches to these data in order to characterise disease progression and biological heterogeneity within the cohort. Specifically, we use longitudinal class-specific mixed effects models to characterise the different clinical disease trajectories and a semi-supervised Bayesian clustering approach to explore whether participants can be stratified into homogeneous subgroups that have different patterns of cognitive functioning evolution, while also having subgroup-specific profiles in terms of baseline biomarkers and longitudinal rate of change in biomarkers

Kepler eclipsing binary stars. VII. the catalogue of eclipsing binaries found in the entire Kepler data set

The primary Kepler Mission provided nearly continuous monitoring of ~200,000 objects with unprecedented photometric precision. We present the final catalog of eclipsing binary systems within the 105 deg2 Kepler field of view. This release incorporates the full extent of the data from the primary mission (Q0-Q17 Data Release). As a result, new systems have been added, additional false positives have been removed, ephemerides and principal parameters have been recomputed, classifications have been revised to rely on analytical models, and eclipse timing variations have been computed for each system. We identify several classes of systems including those that exhibit tertiary eclipse events, systems that show clear evidence of additional bodies, heartbeat systems, systems with changing eclipse depths, and systems exhibiting only one eclipse event over the duration of the mission. We have updated the period and galactic latitude distribution diagrams and included a catalog completeness evaluation. The total number of identified eclipsing and ellipsoidal binary systems in the Kepler field of view has increased to 2878, 1.3% of all observed Kepler targets

Survey of Period Variations of Superhumps in SU UMa-Type Dwarf Novae

We systematically surveyed period variations of superhumps in SU UMa-type dwarf novae based on newly obtained data and past publications. In many systems, the evolution of superhump period are found to be composed of three distinct stages: early evolutionary stage with a longer superhump period, middle stage with systematically varying periods, final stage with a shorter, stable superhump period. During the middle stage, many systems with superhump periods less than 0.08 d show positive period derivatives. Contrary to the earlier claim, we found no clear evidence for variation of period derivatives between superoutburst of the same object. We present an interpretation that the lengthening of the superhump period is a result of outward propagation of the eccentricity wave and is limited by the radius near the tidal truncation. We interpret that late stage superhumps are rejuvenized excitation of 3:1 resonance when the superhumps in the outer disk is effectively quenched. Many of WZ Sge-type dwarf novae showed long-enduring superhumps during the post-superoutburst stage having periods longer than those during the main superoutburst. The period derivatives in WZ Sge-type dwarf novae are found to be strongly correlated with the fractional superhump excess, or consequently, mass ratio. WZ Sge-type dwarf novae with a long-lasting rebrightening or with multiple rebrightenings tend to have smaller period derivatives and are excellent candidate for the systems around or after the period minimum of evolution of cataclysmic variables (abridged).Comment: 239 pages, 225 figures, PASJ accepte

Cognitive Information Processing

Contains goals, background, research activities on one research project and reports on three research projects.Center for Advanced Television StudiesAmerican Broadcasting CompanyAmpex CorporationColumbia Broadcasting SystemsHarris CorporationHome Box OfficePublic Broadcasting ServiceNational Broadcasting CompanyRCA CorporationTektronix3M CompanyProvidence Gravure Co. (Grant)International Business Machines, Inc