Plausibility functions and exact frequentist inference

In the frequentist program, inferential methods with exact control on error rates are a primary focus. The standard approach, however, is to rely on asymptotic approximations, which may not be suitable. This paper presents a general framework for the construction of exact frequentist procedures based on plausibility functions. It is shown that the plausibility function-based tests and confidence regions have the desired frequentist properties in finite samples---no large-sample justification needed. An extension of the proposed method is also given for problems involving nuisance parameters. Examples demonstrate that the plausibility function-based method is both exact and efficient in a wide variety of problems.Comment: 21 pages, 5 figures, 3 table

Applying the WHO ICD-MM classification system to maternal deaths in a tertiary hospital in Nigeria: A retrospective analysis from 2014–2018

Background Addressing the problem of maternal mortality in Nigeria requires proper identification of maternal deaths and their underlying causes in order to focus evidence-based interventions to decrease mortality and avert morbidity. Objectives The objective of the study was to classify maternal deaths that occurred at a Nigerian teaching hospital using the WHO International Classification of Diseases Maternal mortality (ICD-MM) tool. Methods This was a retrospective observational study of all maternal deaths that occurred in a tertiary Nigerian hospital from 1st January 2014 to 31st December,2018. The WHO ICD-MM classification system for maternal deaths was used to classify the type, group, and specific underlying cause of identified maternal deaths. Descriptive analysis was performed using Statistical Package for Social Sciences (SPSS). Categorical and continuous variables were summarized respectively as proportions and means (standard deviations). Results The institutional maternal mortality ratio was 831/100,000 live births. Maternal deaths occurred mainly amongst women aged 25–34 years;30(57.7%), without formal education; 22(42.3%), married;47(90.4%), unbooked;24(46.2%) and have delivered at least twice;34(65.4%). The leading causes of maternal death were hypertensive disorders in pregnancy, childbirth, and the puerperium (36.5%), obstetric haemorrhage (30.8%), and pregnancy related infections (17.3%). Application of the WHO ICD-MM resulted in reclassification of underlying cause for 3.8% of maternal deaths. Postpartum renal failure (25.0%), postpartum coagulation defects (17.3%) and puerperal sepsis (15.4%) were the leading final causes of death. Among maternal deaths, type 1, 2, and 3 delays were seen in 30(66.7%), 22(48.9%), and 6(13.3%), respectively. Conclusion Our institutional maternal mortality ratio remains high. Hypertensive disorders during pregnancy, childbirth, and the puerperium and obstetric haemorrhage are the leading causes of maternal deaths. Implementation of evidence-based interventions both at the hospital and community levels may help in tackling the identified underlying causes of maternal mortality in Nigeria

Jet size dependence of single jet suppression in lead-lead collisions at sqrt(s(NN)) = 2.76 TeV with the ATLAS detector at the LHC

Measurements of inclusive jet suppression in heavy ion collisions at the LHC provide direct sensitivity to the physics of jet quenching. In a sample of lead-lead collisions at sqrt(s) = 2.76 TeV corresponding to an integrated luminosity of approximately 7 inverse microbarns, ATLAS has measured jets with a calorimeter over the pseudorapidity interval |eta| < 2.1 and over the transverse momentum range 38 < pT < 210 GeV. Jets were reconstructed using the anti-kt algorithm with values for the distance parameter that determines the nominal jet radius of R = 0.2, 0.3, 0.4 and 0.5. The centrality dependence of the jet yield is characterized by the jet "central-to-peripheral ratio," Rcp. Jet production is found to be suppressed by approximately a factor of two in the 10% most central collisions relative to peripheral collisions. Rcp varies smoothly with centrality as characterized by the number of participating nucleons. The observed suppression is only weakly dependent on jet radius and transverse momentum. These results provide the first direct measurement of inclusive jet suppression in heavy ion collisions and complement previous measurements of dijet transverse energy imbalance at the LHC.Comment: 15 pages plus author list (30 pages total), 8 figures, 2 tables, submitted to Physics Letters B. All figures including auxiliary figures are available at http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/HION-2011-02

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants