Statistical inference for the optimal approximating model

In the setting of high-dimensional linear models with Gaussian noise, we investigate the possibility of confidence statements connected to model selection. Although there exist numerous procedures for adaptive (point) estimation, the construction of adaptive confidence regions is severely limited (cf. Li in Ann Stat 17:1001–1008, 1989). The present paper sheds new light on this gap. We develop exact and adaptive confidence regions for the best approximating model in terms of risk. One of our constructions is based on a multiscale procedure and a particular coupling argument. Utilizing exponential inequalities for noncentral χ2-distributions, we show that the risk and quadratic loss of all models within our confidence region are uniformly bounded by the minimal risk times a factor close to one.

When to start antiretroviral therapy in children aged 2-5 years: a collaborative causal modelling analysis of cohort studies from southern Africa

BACKGROUND There is limited evidence on the optimal timing of antiretroviral therapy (ART) initiation in children 2-5 y of age. We conducted a causal modelling analysis using the International Epidemiologic Databases to Evaluate AIDS-Southern Africa (IeDEA-SA) collaborative dataset to determine the difference in mortality when starting ART in children aged 2-5 y immediately (irrespective of CD4 criteria), as recommended in the World Health Organization (WHO) 2013 guidelines, compared to deferring to lower CD4 thresholds, for example, the WHO 2010 recommended threshold of CD4 count <750 cells/mm(3) or CD4 percentage (CD4%) <25%. METHODS AND FINDINGS ART-naïve children enrolling in HIV care at IeDEA-SA sites who were between 24 and 59 mo of age at first visit and with ≥1 visit prior to ART initiation and ≥1 follow-up visit were included. We estimated mortality for ART initiation at different CD4 thresholds for up to 3 y using g-computation, adjusting for measured time-dependent confounding of CD4 percent, CD4 count, and weight-for-age z-score. Confidence intervals were constructed using bootstrapping. The median (first; third quartile) age at first visit of 2,934 children (51% male) included in the analysis was 3.3 y (2.6; 4.1), with a median (first; third quartile) CD4 count of 592 cells/mm(3) (356; 895) and median (first; third quartile) CD4% of 16% (10%; 23%). The estimated cumulative mortality after 3 y for ART initiation at different CD4 thresholds ranged from 3.4% (95% CI: 2.1-6.5) (no ART) to 2.1% (95% CI: 1.3%-3.5%) (ART irrespective of CD4 value). Estimated mortality was overall higher when initiating ART at lower CD4 values or not at all. There was no mortality difference between starting ART immediately, irrespective of CD4 value, and ART initiation at the WHO 2010 recommended threshold of CD4 count <750 cells/mm(3) or CD4% <25%, with mortality estimates of 2.1% (95% CI: 1.3%-3.5%) and 2.2% (95% CI: 1.4%-3.5%) after 3 y, respectively. The analysis was limited by loss to follow-up and the unavailability of WHO staging data. CONCLUSIONS The results indicate no mortality difference for up to 3 y between ART initiation irrespective of CD4 value and ART initiation at a threshold of CD4 count <750 cells/mm(3) or CD4% <25%, but there are overall higher point estimates for mortality when ART is initiated at lower CD4 values. Please see later in the article for the Editors' Summary.

How do indirect measures of evaluation work? Evaluating the inference of prejudice in the Implicit Association Test

There has been significant interest in indirect measures of attitudes like the Implicit Association Test (IAT), presumably because of the possibility of uncovering implicit prejudices. The authors derived a set of qualitative predictions for people's performance in the IAT on the basis of random walk models. These were supported in 3 experiments comparing clearly positive or negative categories to nonwords. They also provided evidence that participants shift their response criterion when doing the IAT. Because of these criterion shifts, a response pattern in the IAT can have multiple causes. Thus, it is not possible to infer a single cause (such as prejudice) from IAT results. A surprising additional result was that nonwords were treated as though they were evaluated more negatively than obviously negative items like insects, suggesting that low familiarity items may generate the pattern of data previously interpreted as evidence for implicit prejudice.

Prognostic relevance of coronary collateral function: confounded or causal relationship?

OBJECTIVE To expand the limited information on the prognostic impact of quantitatively obtained collateral function in patients with coronary artery disease (CAD) and to estimate causality of such a relation. DESIGN Prospective cohort study with long-term observation of clinical outcome. SETTING University Hospital. PATIENTS One thousand one hundred and eighty-one patients with chronic stable CAD undergoing 1771 quantitative, coronary pressure-derived collateral flow index measurements, as obtained during a 1-min coronary balloon occlusion (CFI is the ratio between mean distal coronary occlusive pressure and mean aortic pressure both subtracted by central venous pressure). Subgroup of 152 patients included in randomised trials on the longitudinal effect of different arteriogenic protocols on CFI. INTERVENTIONS Collection of long-term follow-up information on clinical outcome. MAIN OUTCOME MEASURES All-cause mortality and major adverse cardiac events. RESULTS Cumulative 15-year survival rate was 48% in patients with CFI<0.25 and 65% in the group with CFI≥0.25 (p=0.0057). Cumulative 10-year survival rate was 75% in patients without arteriogenic therapy and 88% (p=0.0482) in the group with arteriogenic therapy and showing a significant increase in CFI at follow-up. By proportional hazard analysis, the following variables predicted increased all-cause mortality: age, low CFI, left ventricular end-diastolic pressure and number of vessels with CAD. CONCLUSIONS A well-functioning coronary collateral circulation independently predicts lowered mortality in patients with chronic CAD. This relation appears to be causal, because augmented collateral function by arteriogenic therapy is associated with prolonged survival.

Status and Causal Pathway Assessments Supporting River Basin Management

The European Water Framework Directive (WFD) requires a status assessment of all water bodies. If that status is deteriorated, the WFD urges the identification of its potential causes in order to be able to suggest appropriate management measures. The instrument of investigative monitoring allows for such identification, provided that appropriate tools are available to link the observed effects to causative stressors, while unravelling confounding factors. In this chapter, the state of the art of status and causal pathway assessment is described for the major stressors responsible for the deterioration of European water bodies, i.e. toxicity, acidification, salinisation, eutrophication and oxygen depletion, parasites and pathogens, invasive alien species, hydromorphological degradation, changing water levels as well as sediments and suspended matter. For each stressor, an extensive description of the potential effects on the ecological status is given. Secondly, stressor-specific abiotic and biotic indicators are described that allow for a first indication of probable causes, based on the assessment of available monitoring data. Subsequently, more advanced tools for site-specific confirmation of stressors at hand are discussed. Finally, the local status assessments are put into the perspective of the risk for downstream stretches in order to be able to prioritise stressors and to be able to select appropriate measures for mitigation of the risks resulting from these stressors.

Unconscious relational inference recruits the hippocampus

Relational inference denotes the capacity to encode, flexibly retrieve, and integrate multiple memories to combine past experiences to update knowledge and improve decision-making in new situations. Although relational inference is thought to depend on the hippocampus and consciousness, we now show in young, healthy men that it may occur outside consciousness but still recruits the hippocampus. In temporally distinct and unique subliminal episodes, we presented word pairs that either overlapped (“winter–red”, “red–computer”) or not. Effects of unconscious relational inference emerged in reaction times recorded during unconscious encoding and in the outcome of decisions made 1 min later at test, when participants judged the semantic relatedness of two supraliminal words. These words were either episodically related through a common word (“winter–computer” related through “red”) or unrelated. Hippocampal activity increased during the unconscious encoding of overlapping versus nonoverlapping word pairs and during the unconscious retrieval of episodically related versus unrelated words. Furthermore, hippocampal activity during unconscious encoding predicted the outcome of decisions made at test. Hence, unconscious inference may influence decision-making in new situations.

Climate refugia: joint inference from fossil records, species distribution models and phylogeography

Climate refugia, locations where taxa survive periods of regionally adverse climate, are thought to be critical for maintaining biodiversity through the glacial–interglacial climate changes of the Quaternary. A critical research need is to better integrate and reconcile the three major lines of evidence used to infer the existence of past refugia – fossil records, species distribution models and phylogeographic surveys – in order to characterize the complex spatiotemporal trajectories of species and populations in and out of refugia. Here we review the complementary strengths, limitations and new advances for these three approaches. We provide case studies to illustrate their combined application, and point the way towards new opportunities for synthesizing these disparate lines of evidence. Case studies with European beech, Qinghai spruce and Douglas-fir illustrate how the combination of these three approaches successfully resolves complex species histories not attainable from any one approach. Promising new statistical techniques can capitalize on the strengths of each method and provide a robust quantitative reconstruction of species history. Studying past refugia can help identify contemporary refugia and clarify their conservation significance, in particular by elucidating the fine-scale processes and the particular geographic locations that buffer species against rapidly changing climate.

Inference of inhomogeneous clouds in an exoplaent atmosphere

We present new visible and infrared observations of the hot Jupiter Kepler-7b to determine its atmospheric properties. Our analysis allows us to (1) refine Kepler-7b's relatively large geometric albedo of Ag = 0.35 ± 0.02, (2) place upper limits on Kepler-7b thermal emission that remains undetected in both Spitzer bandpasses and (3) report a westward shift in the Kepler optical phase curve. We argue that Kepler-7b's visible flux cannot be due to thermal emission or Rayleigh scattering from H2 molecules. We therefore conclude that high altitude, optically reflective clouds located west from the substellar point are present in its atmosphere. We find that a silicate-based cloud composition is a possible candidate. Kepler-7b exhibits several properties that may make it particularly amenable to cloud formation in its upper atmosphere. These include a hot deep atmosphere that avoids a cloud cold trap, very low surface gravity to suppress cloud sedimentation, and a planetary equilibrium temperature in a range that allows for silicate clouds to potentially form in the visible atmosphere probed by Kepler. Our analysis does not only present evidence of optically thick clouds on Kepler-7b but also yields the first map of clouds in an exoplanet atmosphere.

Risk assessment and causal preventive measures.

A prerequisite for preventive measures is to diagnose erosive tooth wear and to evaluate the different etiological factors in order to identify persons at risk. No diagnostic device is available for the assessment of erosive defects. Thus, they can only be detected clinically. Consequently, erosion not diagnosed at an early stage may render timely preventive measures difficult. In order to assess the risk factors, patients should record their dietary intake for a distinct period of time. Then a dentist can determine the erosive potential of the diet. A table with common beverages and foodstuffs is presented for judging the erosive potential. Particularly, patients with more than 4 dietary acid intakes have a higher risk for erosion when other risk factors are present. Regurgitation of gastric acids is a further important risk factor for the development of erosion which has to be taken into account. Based on these analyses, an individually tailored preventive program may be suggested to the patients. It may comprise dietary advice, use of calcium-enriched beverages, optimization of prophylactic regimes, stimulation of salivary flow rate, use of buffering medicaments and particular motivation for nondestructive toothbrushing habits with an erosive-protecting toothpaste as well as rinsing solutions. Since erosion and abrasion often occur simultaneously, all of the causative components must be taken into consideration when planning preventive strategies but only those important and feasible for an individual should be communicated to the patient.

Mining the Ecosystem to Improve Type Inference For Dynamically Typed Languages

Dynamically typed languages lack information about the types of variables in the source code. Developers care about this information as it supports program comprehension. Ba- sic type inference techniques are helpful, but may yield many false positives or negatives. We propose to mine information from the software ecosys- tem on how frequently given types are inferred unambigu- ously to improve the quality of type inference for a single system. This paper presents an approach to augment existing type inference techniques by supplementing the informa- tion available in the source code of a project with data from other projects written in the same language. For all available projects, we track how often messages are sent to instance variables throughout the source code. Predictions for the type of a variable are made based on the messages sent to it. The evaluation of a proof-of-concept prototype shows that this approach works well for types that are sufficiently popular, like those from the standard librarie, and tends to create false positives for unpopular or domain specific types. The false positives are, in most cases, fairly easily identifiable. Also, the evaluation data shows a substantial increase in the number of correctly inferred types when compared to the non-augmented type inference.