We search for beyond the standard model physics by combining COHERENT Collaboration energy and timing data. Focusing on light, ≲GeV mediators, we find data favor a ∼10-1000 MeV mediator, as compared to best fit at ≲2σ level. The best-fit coupling range is g∼10^{-5}-10^{-3}. provide statistical information neutrino flavor distributions that not attainable from nuclear recoil energies alone. This result accounts uncertainty in effective size of neutron distribution, highlights power including...

Neutrino non-standard interactions (NSI) with the first generation of standard model fermions can span a parameter space large dimension and exhibit degeneracies that cannot be broken by single class experiment. Oscillation experiments, together neutrino scattering merge their observations into highly informational dataset to combat this problem. We consider combining neutrino-electron neutrino-nucleus data from Borexino COHERENT including projection for upcoming coherent measurement at...

Abstract 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) dose-dependently induces the development of hepatic fat accumulation and inflammation with fibrosis in mice initially portal region. Conversely, differential gene protein expression is first detected central To further investigate cell-specific spatially resolved dose-dependent changes elicited by TCDD, single-nuclei RNA sequencing spatial transcriptomics were used for livers male gavaged TCDD every 4 days 28 days. The proportion 11 cell...

The application of single-cell RNA sequencing (scRNAseq) for the evaluation chemicals, drugs, and food contaminants presents opportunity to consider cellular heterogeneity in pharmacological toxicological responses. Current differential gene expression analysis (DGEA) methods focus primarily on two group comparisons, not multi-group dose-response study designs used safety assessments. To benchmark DGEA scRNAseq experiments, we proposed a multiplicity corrected Bayesian testing approach...

ABSTRACT The article considers a new approach for small area estimation based on joint modelling of mean and variances. Model parameters are estimated via expectation–maximization algorithm. conditional squared error is used to evaluate the prediction error. Analytical expressions obtained its estimator. Our approximations second‐order correct, an unwritten standardization in literature. Simulation studies indicate that proposed method outperforms existing methods terms errors their values.

We study the prospects for detection of solar, atmospheric neutrino, and diffuse supernova neutrino background (DSNB) fluxes at future large-scale dark matter detectors through both electron nuclear recoils. specifically examine how change several prospective detector locations [Sanford Underground Research Facility (SURF), SNOlab, Gran Sasso, China Jinping Laboratory (CJPL), Kamioka] improve upon statistical methodologies used in previous studies. Because its ability to measure lower...

Media-based event data—i.e., data comprised from reporting by media outlets—are widely used in political science research. However, events of interest (e.g., strikes, protests, conflict) are often underreported these primary and secondary sources, producing incomplete that risks inconsistency bias subsequent analysis. While general strategies exist to help ameliorate this bias, methods do not make full use the information available researchers. Specifically, much social sciences is drawn...

Complex diseases like cancers can often be classified into subtypes using various pathological and molecular traits of the disease. In this article, we develop methods for analysis disease incidence in cohort studies incorporating data on multiple a two-stage semiparametric Cox proportional hazards regression model that allows one to examine heterogeneity effect covariates by levels different traits. For inference presence missing traits, propose generalization an estimating equation...

Abstract In an individually matched case–control study, effects of potential risk factors are ascertained through conditional logistic regression (CLR). Extension CLR to situations with multiple disease or reference categories has been made polychotomous and is shown be more efficient than carrying out separate CLRs for each subgroup. this paper, we consider studies where there one control group, but states a natural ordering among themselves. This scenario can observed when the cases...

Summary : We propose a semiparametric Bayesian method for handling measurement error in nutritional epidemiological data. Our goal is to estimate nonparametrically the form of association between disease and exposure variable while true values are never observed. Motivated by data, we consider setting where surrogate covariate recorded primary calibration data set contains information on repeated measurements an unbiased instrumental exposure. develop flexible not only relationship treated...

We employ a general bias preventive approach developed by Firth (Biometrika 1993; 80:27-38) to reduce the of an estimator log-odds ratio parameter in matched case-control study solving modified score equation. also propose method calculate standard error resultant estimator. A closed-form expression for is derived case dichotomous exposure variable. Finite sample properties are investigated via simulation study. Finally, we apply analyze data from low birthweight

Accelerated failure time model is a popular to analyze censored time-to-event data. Analysis of this without assuming any parametric distribution for the error challenging, and complexity enhanced in presence large number covariates. We developed nonparametric Bayesian method regularized estimation regression parameters flexible accelerated model. The novelties our lie modeling nonparametrically, variance as function mean, adopting variable selection technique mean. proposed allowed...

This article considers Bayesian analysis of matched case-control problems when one the covariates is partially missing. Within likelihood context, standard approach to this problem posit a fully parametric model among controls for missing covariate as function in and variables making up strata. Sometimes strata effects are ignored at stage. Our differs not only that it Bayesian, but, far more importantly, manner which treats effects. We assume Dirichlet process prior with normal base measure...

Summary In case–control studies of gene‐environment association with disease, when genetic and environmental exposures can be assumed to independent in the underlying population, one may exploit independence order derive more efficient estimation techniques than traditional logistic regression analysis ( Chatterjee Carroll, 2005 , Biometrika 92, 399–418). However, covariates that stratify such as age, ethnicity alike, could potentially lead nonindependence. this article, we provide a novel...

We study the prospects for measuring time variation of solar and atmospheric neutrino fluxes at future large-scale xenon argon dark matter detectors. For neutrinos, a yearly arises from eccentricity Earth’s orbit and, charged current interactions, smaller energy-dependent day-night due to flavor regeneration as neutrinos travel through Earth. 100-ton detector running ten years with xenon-136 fraction <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"...

Summary. We present a Bayesian approach to analyze matched “case–control” data with multiple disease states. The probability of development is described by multinomial logistic regression model. exposure distribution depends on the state and could vary across strata. In such model, number stratum effect parameters grows in direct proportion sample size leading inconsistent MLEs for interest even when one uses retrospective conditional likelihood. adopt semiparametric framework instead,...

Summary We take a semiparametric approach in fitting linear transformation model to right censored data when predictive variables are subject measurement errors. construct consistent estimating equations repeated measurements of surrogate the unobserved true predictor available. The proposed applies under minimal assumptions on distributions covariate or derive asymptotic properties estimator and illustrate characteristics finite sample performance via simulation studies. apply method...

The skew-probit link function is one of the popular choices for modelling success probability a binary variable with regard to covariates. This deviates from probit in terms flexible skewness parameter. For this link, identifiability parameters investigated. Next, reduce bias maximum likelihood estimator model we propose use penalized approach. We consider three different penalty functions, and compare them via extensive simulation studies. Based on results make some practical...

Summary With advances in modern medicine and clinical diagnosis, case–control data with characterization of finer subtypes cases are often available. In matched studies, missingness exposure values leads to deletion entire stratum, thus entails a significant loss information. When treated as categorical outcomes, the further stratified observations becomes even more expensive terms precision category-specific odds-ratio parameters, especially using multinomial logit model. The stereotype...