Using inverse-weighting in cost-effectiveness analysis with censored data

Due to induced dependent censoring, estimating mean costs and quality-adjusted survival in a cost-effectiveness analysis using standard life-table methods leads to biased results. In this paper we propose methods for estimating the difference in mean costs and the difference in effectiveness, together with their respective variances and covariance in the presence of dependent censoring. We consider the situation in which the measure of effectiveness is either the probability of patients surviving a duration of interest, mean survival time over a duration of interest or mean quality-adjusted survival time over a duration of interest. The method of inverse-weighting is used for censored cost and quality of life data. The methods are illustrated in an example using an incremental net benefit analysis.     

Fitting competing risks with an assumed copula

We propose a fully parametric model for the analysis of competing risks data where the types of failure may not be independent. We show how the dependence between the cause-specific survival times can be modelled with a copula function. Features include: identifiability of the problem; accessible understanding of the dependence structures; and flexibility in choosing marginal survival functions. The model is constructed in such a way that it allows us to adjust for concomitant variables and for a dependence parameter to assess the effects of these on each marginal survival model and on the relationship between the causes of death. The methods are applied to a prostate cancer data set. We find that, with the copula model, more accurate inferences are obtained than with the use of a simpler model such as the independent competing risks approach.     

Multi-state models for event history analysis

An introduction to event history analysis via multi-state models in given. Examples include the two-state model for survival analysis, the competing risks and illness-death models, and models for bone marrow transplantation. Statistical model specification via transition intensities and likelihood inference is introduced. Consequences of observational patterns are discussed, and a real example concerning mortality and bleeding episodes in a liver cirrhosis trial is discussed.     

Bivariate random effects models for meta-analysis of comparative studies with binary outcomes: Methods for the absolute risk difference and relative risk

Multivariate meta-analysis is increasingly utilised in biomedical research to combine data of multiple comparative clinical studies for evaluating drug efficacy and safety profile. When the probability of the event of interest is rare, or when the individual study sample sizes are small, a substantial proportion of studies may not have any event of interest. Conventional meta-analysis methods either exclude such studies or include them through ad hoc continuality correction by adding an arbitrary positive value to each cell of the corresponding 2?×?2 tables, which may result in less accurate conclusions. Furthermore, different continuity corrections may result in inconsistent conclusions. In this article, we discuss a bivariate Beta-binomial model derived from Sarmanov family of bivariate distributions and a bivariate generalised linear mixed effects model for binary clustered data to make valid inferences. These bivariate random effects models use all available data without ad hoc continuity corrections, and accounts for the potential correlation between treatment (or exposure) and control groups within studies naturally. We then utilise the bivariate random effects models to reanalyse two recent meta-analysis data sets.     

Competing risks as a multi-state model

This paper deals with the competing risks model as a special case of a multi-state model. The properties of the model are reviewed and contrasted to the so-called latent failure time approach. The relation between the competing risks model and right-censoring is discussed and regression analysis of the cumulative incidence function briefly reviewed. Two real data examples are presented and a guide to the practitioner is given.     

Deciphering the Molecular Nature of Ovarian Cancer Biomarker CA125

The ovarian cancer biomarker CA125 has been extensively investigated over the last 30 years. The knowledge about the exact molecular nature of this protein, however, remains fragmented. This review provides an overview of the structural research regarding CA125, and presents an orthogonal verification method to confirm the identity of this molecule. The need for independent identification of CA125 is exemplified by several reports where mutually exclusive data concerning the existence of isoforms and the glycan moieties is presented. Mass spectrometry can overcome the pitfalls of a single detection/identification method such as antibody probing. Independent verification of CA125 identity in characterization studies will help establish a refined model of its molecular structure that will promote the development of new approaches for diagnosis, prognosis and therapy of ovarian cancer.     

Repeated measures with zeros

Consider repeated measures data with many zeros. For the case with one grouping factor and one repeated measure, we examine several models, assuming that the nonzero data are roughly lognormal. One of the simplest approaches is to model the zeros as left-censored observations from the lognormal distribution. A random effect is assumed for subjects. The censored model makes a strong assumption about the relationship between the zeros and the nonzero values. To check on this, you can instead assume that some of the zeros are 'true' zeros and model them as Bernoulli. Then the other values are modeled with a censored lognormal. A logistic model is used for the Bernoulli p, the probability of a true nonzero. The fit of the pure left-censored lognormal can be assessed by testing the hypothesis that p is 1, as described by Moulton and Halsey. The model can also be simplified by omitting the censoring, leaving a logistic model for the zeros and a lognormal model for the nonzero values. This is approximately equivalent to modeling the zero and nonzero values separately, a two-part model. In contrast to the censored model, this model assumes only a slight relationship (a covariance component) between the occurrence of zeros and the size of the nonzero values. The models are compared in terms of an example with data from children's private speech.     

Log Gaussian Cox processes and spatially aggregated disease incidence data

This article presents a methodology for modeling aggregated disease incidence data with the spatially continuous log-Gaussian Cox process. Statistical models for spatially aggregated disease incidence data usually assign the same relative risk to all individuals in the same reporting region (census areas or postal regions). A further assumption that the relative risks in two regions are independent given their neighbor's risks (the Markov assumption) makes the commonly used Besag-York-Mollié model computationally simple. The continuous model proposed here uses a data augmentation step to sample from the posterior distribution of the exact locations at each step of an Markov chain Monte Carlo algorithm, and models the exact locations with an log-Gaussian Cox process. A simulation study shows the log-Gaussian Cox process model consistently outperforming the Besag-York-Mollié model. The method is illustrated by making inference on the spatial distribution of syphilis risk in North Carolina. The effect of several known social risk factors are estimated, and areas with risk well in excess of that expected given these risk factors are identified.     

Lognormal Simulation of Pore Size Distributions in Cementitious Materials

The pore size distributions in cement pastes and mortars, over the range of pore sizes determined by high-pressure mercury intrusion porosimetry (MIP), can be described in terms of a multimodal distribution by using lognormal simulation. The pore size distribution may be regarded as a mixture of lognormal distributions. Such a mixture is defined by a compound density function: p ( x ) =Σ f_i p ( x , μ _i , σ _i ), Σ f_i = 1, where x is the pore diameter, f_i , is the weighting factor of the i ^th lognormal subdistribution of pore sizes, p ( x , μ _i , σ _i ), and μ _i and σ _i are the location parameter and the shape parameter of the i ^th subdistribution, respectively. It may indicate that different origins and formation mechanisms exist for pores in different size ranges in cementitious materials. A graphical method is proposed to estimate the parameters for the compound distribution. Applications of this model to prediction of permeability are discussed.     

On the potential utility of 2 × 2 contingency tables in electrochemical engineering

2 × 2 contingency tables are widely used in the statistical analysis of categorical data grouped according to certain (mutually exclusive) attributes, characters or quality. The paper describes three specific applications to electrochemical engineering, employing (i) Fisher’s exact test for electrolyzer selection; (ii) the McNemar test to determine improvement in current efficiency, and (iii) the Mantel–Haenszel test to evaluate electrolyzer performance. The subject matter represents a cross-fertilization of two disciplines to facilitate statistically backed design decisions and performance analysis.     

Sera of Neuromyelitis Optica Patients Increase BID-Mediated Apoptosis in Astrocytes

Neuromyelitis optica (NMO) is a rare disease usually presenting with bilateral or unilateral optic neuritis with simultaneous or sequential transverse myelitis. Autoantibodies directed against aquaporin-4 (AQP4-IgG) are found in most patients. They are believed to cross the blood–brain barrier, target astrocytes, activate complement, and eventually lead to astrocyte destruction, demyelination, and axonal damage. However, it is still not clear what the primary pathological event is. We hypothesize that the interaction of AQP4-IgG and astrocytes leads to DNA damage and apoptosis. We studied the effect of sera from seropositive NMO patients and healthy controls (HCs) on astrocytes’ immune gene expression and viability. We found that sera from seropositive NMO patients led to higher expression of apoptosis-related genes, including BH3-interacting domain death agonist (BID), which is the most significant differentiating gene (p < 0.0001), and triggered more apoptosis in astrocytes compared to sera from HCs. Furthermore, NMO sera increased DNA damage and led to a higher expression of immunological genes that interact with BID (TLR4 and NOD-1). Our findings suggest that sera of seropositive NMO patients might cause astrocytic DNA damage and apoptosis. It may be one of the mechanisms implicated in the primary pathological event in NMO and provide new avenues for therapeutic intervention.     

The Possible Role of Neural Cell Apoptosis in Multiple Sclerosis

The etiology of multiple sclerosis (MS), a demyelinating disease affecting the central nervous system (CNS), remains obscure. Although apoptosis of oligodendrocytes and neurons has been observed in MS lesions, the contribution of this cell death process to disease pathogenesis remains controversial. It is usually considered that MS-associated demyelination and axonal degeneration result from neuroinflammation and an autoimmune process targeting myelin proteins. However, experimental data indicate that oligodendrocyte and/or neuronal cell death may indeed precede the development of inflammation and autoimmunity. These findings raise the question as to whether neural cell apoptosis is the key event initiating and/or driving the pathological cascade, leading to clinical functional deficits in MS. Similarly, regarding axonal damage, a key pathological feature of MS lesions, the roles of inflammation-independent and cell autonomous neuronal processes need to be further explored. While oligodendrocyte and neuronal loss in MS may not necessarily be mutually exclusive, particular attention should be given to the role of neuronal apoptosis in the development of axonal loss. If proven, MS could be viewed primarily as a neurodegenerative disease accompanied by a secondary neuroinflammatory and autoimmune process.     

Observational process data analytics using causal inference

Voluminous process data are available with the paradigm shift toward smart manufacturing. However, most historical data are observational, containing noncausal correlations due to confounders and mediators. Estimating causal effects from observational data remains a bottleneck in leveraging them for active applications such as optimization and control. This work aims to introduce a causal modeling framework for analyzing observational process data and extracting quantitative causal information. We demonstrate a real-world application in steel manufacturing where causal inference is used to analyze observational production data and improve the steelmaking process. Additionally, we propose a novel formulation for identifying critical process parameters from observational data, where causal inference is combined with variance-based methods to estimate corresponding risks of interventions to the manufacturing system. The proposed methods are compared with statistical ones to illustrate that causally interpreting statistical correlation leads to problematic results, while the provided workflow generates satisfactory strategies for process improvement.     

A non-Gaussian network model for rubber elasticity

A simple constitutive model based on the non-Gaussian, Kuhn-Grün probability distribution function is derived. It is assumed that the actual macromolecular structure of a rubber-like material can be replaced by idealized equilateral tetrahedra cells that are not mutually exclusive so far as occupancy of the space is concerned. The three chains are assumed to meet at a junction point located at the centroid of the cell with their other ends being fixed at the vertices of the equilateral tetrahedron. The centroid junction point is free to fluctuate, subject to the constraint imposed by the equilibrium of chain forces. Stress-stretch constitutive equations are then derived to study homogeneous deformations of isotropic, incompressible hyperelastic rubber like materials. The accuracy of the derived constitutive equations is demonstrated by using uniaxial, equibiaxial, pure shear, and plane strain experimental data provided in the literature.     

TESTING EQUALITY OF MEANS WHEN THE OBSERVATIONS ARE FROM FUNCTIONAL TIME SERIES

There are numerous examples of functional data in areas ranging from earth science to finance where the problem of interest is to compare several functional populations. In many instances, the observations are obtained consecutively in time, and thus, the classical assumption of independence within each population may not be valid. In this article, we derive a new, asymptotically justified method to test the hypothesis that the mean curves of multiple functional populations are the same. The test statistic is constructed from the coefficient vectors obtained by projecting the functional observations into a finite dimensional space. Asymptotics are established when the observations are considered to be from stationary functional time series. Although the limit results hold for projections into arbitrary finite dimensional spaces, we show that higher power is achieved by projecting onto the principle components of empirical covariance operators that diverge under the alternative. Our method is further illustrated by a simulation study as well as an application to electricity demand data.     

Recent progress in the development of beta-alumina for the sodium-sulphur battery

The development of beta-alumina as the electrolyte and separator for the sodium-sulphur battery is described. The requirements of cell performance and durability determine the mechanical and electrical properties of the electrolyte. Changes in the cell configuration also have an effect in so far as extending the area of the electrodes and electrolyte and reducing their thickness will reduce the overall impedance of a cell. The manner in which this interacts with the manufacturing route is outlined. The methods by which high ionic conductivity are achieved whilst maintaining adequate mechanical strength are described and the extent to which these are mutually exclusive is discussed. Some of the factors responsible for the failure of beta-alumina in sodium-sulphur cells are considered in relation to recent experimental studies.     

油气管道危害风险及预防措施

研究表明:油气管道运行过程中存在的风险问题较多,这也是难以制定有效预防措施的难点所在。管道的风险主要集中在腐蚀和老化、人为损坏以及地质灾害三个方面,这三种风险出现的原因不同,但是都会对管道的运行造成较为严重的后果;管道运营管理公司应从完善相关制度、加强管道监督、控制盗油问题以及做好防范措施四方面入手,采取多项有效措施,防止管道出现风险事故,保障管道安全运行。     

Effect of Hyaluronic Acid on the Self-Assembly of a Dipeptide-Based Supramolecular Gel

The combination of polymers and low molecular weight (LMW) compounds is a powerful approach to prepare new supramolecular materials. Here we prepare two-component hydrogels made by a well-known and biologically active polymer, hyaluronic acid ( HA ), and a dipeptide-based supramolecular gelator. We undertake a detailed study of materials with different compositions including macroscopic (hydrogel formation, rheology) and micro/nanoscopic characterization (electron microscopy, X-ray powder diffraction). We observe that the two components mutually benefit in the new materials: a minimum amount of HA helps to reduce the polymorphism of the LMW network leading to reproducible hydrogels with improved mechanical properties; the LMW component network holds HA without the need for an irreversible covalent crosslinking. These materials have a great potential for biomedical application as, for instance, extracellular matrix mimetics for cell growth. As a proof of concept, we have observed that this material is effective for cell growth in suspension and avoids cell sedimentation even in the presence of competing cell-adhesive surfaces. This may be of interest to advanced cell delivery techniques.     

Particle Image Velocimetry of Human Cough

Cough generated infectious aerosols are of interest while developing strategies for the mitigation of disease risks ranging from the common cold to SARS. In this work, the velocity field of human cough was measured using particle image velocimetry (PIV). The project subjects (total 29) coughed into an enclosure seeded with stage fog. Cough flow velocity profiles, average widths of the cough jet, and maximum cough velocities were measured. Maximum cough velocities ranged from 1.5 m/s to 28.8 m/s. The average width of all coughs ranged between 35 to 45 mm. Wide variability in the data suggests that future cough simulations consider a range of conditions.     

Brände und Explosionen im Rahmen der Risikoermittlung

The procedure of assessing risks is treated by analyzing an event sequence following the puff release of gaseous propylene. The models for fireball, flash fire and explosion required for this purpose are presented. Their uncertainties and sensitivities are discussed and illustrated by numerical examples. Modeling and data uncertainties in assessing the probabilities of event sequences are characterized; their mathematical treatment is shown. Deterministic as well as probabilistic calculations are performed and their results are compared.