Estimation of causal effects using instrumental variables with nonignorable missing covariates: Application to effect of type of delivery NICU on premature infants

Understanding how effective high-level NICUs (neonatal intensive care units that have the capacity for sustained mechanical assisted ventilation and high volume) are compared to low-level NICUs is important and valuable for both individual mothers and for public policy decisions. The goal of this paper is to estimate the effect on mortality of premature babies being delivered in a high-level NICU vs. a low-level NICU through an observational study where there are unmeasured confounders as well as nonignorable missing covariates. We consider the use of excess travel time as an instrumental variable (IV) to control for unmeasured confounders. In order for an IV to be valid, we must condition on confounders of the IV---outcome relationship, for example, month prenatal care started must be conditioned on for excess travel time to be a valid IV. However, sometimes month prenatal care started is missing, and the missingness may be nonignorable because it is related to the not fully measured mother's/infant's risk of complications. We develop a method to estimate the causal effect of a treatment using an IV when there are nonignorable missing covariates as in our data, where we allow the missingness to depend on the fully observed outcome as well as the partially observed compliance class, which is a proxy for the unmeasured risk of complications. A simulation study shows that under our nonignorable missingness assumption, the commonly used estimation methods, complete-case analysis and multiple imputation by chained equations assuming missingness at random, provide biased estimates, while our method provides approximately unbiased estimates. We apply our method to the NICU study and find evidence that high-level NICUs significantly reduce deaths for babies of small gestational age, whereas for almost mature babies like 37 weeks, the level of NICUs makes little difference. A sensitivity analysis is conducted to assess the sensitivity of our conclusions to key assumptions about the missing covariates. The method we develop in this paper may be useful for many observational studies facing similar issues of unmeasured confounders and nonignorable missing data as ours.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS699 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Phages and human health: More than idle hitchhikers

Bacteriophages, or phages, are viruses that infect bacteria and archaea. Phages have diverse morphologies and can be coded in DNA or RNA and as single or double strands with a large range of genome sizes. With the increasing use of metagenomic sequencing approaches to analyze complex samples, many studies generate massive amounts of “viral dark matter”, or sequences of viral origin unable to be classified either functionally or taxonomically. Metagenomic analysis of phages is still in its infancy, and uncovering novel phages continues to be a challenge. Work over the past two decades has begun to uncover key roles for phages in different environments, including the human gut. Recent studies in humans have identified expanded phage populations in both healthy infants and in inflammatory bowel disease patients, suggesting distinct phage activity during development and in specific disease states. In this review, we examine our current knowledge of phage biology and discuss recent efforts to improve the analysis and discovery of novel phages. We explore the roles phages may play in human health and disease and discuss the future of phage research

Stronger instruments via integer programming in an observational study of late preterm birth outcomes

In an optimal nonbipartite match, a single population is divided into matched pairs to minimize a total distance within matched pairs. Nonbipartite matching has been used to strengthen instrumental variables in observational studies of treatment effects, essentially by forming pairs that are similar in terms of covariates but very different in the strength of encouragement to accept the treatment. Optimal nonbipartite matching is typically done using network optimization techniques that can be quick, running in polynomial time, but these techniques limit the tools available for matching. Instead, we use integer programming techniques, thereby obtaining a wealth of new tools not previously available for nonbipartite matching, including fine and near-fine balance for several nominal variables, forced near balance on means and optimal subsetting. We illustrate the methods in our on-going study of outcomes of late-preterm births in California, that is, births of 34 to 36 weeks of gestation. Would lengthening the time in the hospital for such births reduce the frequency of rapid readmissions? A straightforward comparison of babies who stay for a shorter or longer time would be severely biased, because the principal reason for a long stay is some serious health problem. We need an instrument, something inconsequential and haphazard that encourages a shorter or a longer stay in the hospital. It turns out that babies born at certain times of day tend to stay overnight once with a shorter length of stay, whereas babies born at other times of day tend to stay overnight twice with a longer length of stay, and there is nothing particularly special about a baby who is born at 11:00 pm.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS582 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Effects of Warm Up Intensity on Factors Related to Subsequent Performance of Submaximal Exercise

Introduction: Athletes often warm up (WU) prior to exercise to improve performance. However, there are no clear directives regarding the intensity of the WU that is most effective in improving physiological responses related to enhanced aerobic performance. Methods: Nine college-aged men (age, ht, mass, 20.6 yr, 1.7 m, 84.8 kg, respectively) performed WU of varying intensities, 60% ventilatory threshold (VT), 100%VT, and 120%VT prior to performing 5 min of steady state exercise at 80%VT on a cycle ergometer. O2 deficit, RPE, steady state heart rate (HRss), and steady state VO2 (VO2ss) were measured during the exercise bout. Results: There was a significant decrease in O2 deficit as WU intensity increased ((2,9)= 9.15, p = .002, 2=0.53) with the deficit being lowest after WU at 120%VT. RPE were significantly lower after WU at 120%VT than both 60% and 100%VT (=(2,9)=6.88, p=.007, 2=0.46). However, WU intensity did not significantly affect either HRss (F(2,9)=0.48, p=0.63) or VO2ss (F(2,9)=1.10, p=0.36) during the exercise bout. Conclusion: The findings suggest that a higher intensity WU improves factors related to improved aerobic performance, i.e. decreased O2 deficit and RPE, without adversely affecting factors that could lead to a decline in performance, i.e. increased HRss and VO2ss

Exploring the Variable Sky with LINEAR. I. Photometric Recalibration with the Sloan Digital Sky Survey

We describe photometric recalibration of data obtained by the asteroid survey LINEAR. Although LINEAR was designed for astrometric discovery of moving objects, the data set described here contains over 5 billion photometric measurements for about 25 million objects, mostly stars. We use Sloan Digital Sky Survey (SDSS) data from the overlapping ~10,000 deg^2 of sky to recalibrate LINEAR photometry and achieve errors of 0.03 mag for sources not limited by photon statistics with errors of 0.2 mag at r ~ 18. With its 200 observations per object on average, LINEAR data provide time domain information for the brightest four magnitudes of the SDSS survey. At the same time, LINEAR extends the deepest similar wide-area variability survey, the Northern Sky Variability Survey, by 3 mag. We briefly discuss the properties of about 7000 visually confirmed periodic variables, dominated by roughly equal fractions of RR Lyrae stars and eclipsing binary stars, and analyze their distribution in optical and infrared color-color diagrams. The LINEAR data set is publicly available from the SkyDOT Web site