Related Covariates Research Articles

A Simple Stochastic Approach to Debt Sustainability Applied to Lebanon

This paper applies a simple probabilistic approach to debt sustainability analysis to the case of Lebanon. The paper derives fan charts to depict the probability distribution of the government debt to GDP ratio under a medium-term adjustment scenario, as a result of shocks to GDP growth and interest rates. The distribution of shocks is derived from the past shocks to these variables and the related variance covariance. Because we are interested in assessing the sustainability of a particular policy scenario, we do not consider independent fiscal policy shocks or the endogenous policy response to shocks.

A Simple Stochastic Approach to Debt Sustainability Applied to Lebanon

This paper applies a simple probabilistic approach to debt sustainability analysis to the case of Lebanon. The paper derives fan charts to depict the probability distribution of the government debt to GDP ratio under a medium-term adjustment scenario, as a result of shocks to GDP growth and interest rates. The distribution of shocks is derived from the past shocks to these variables and the related variance covariance. Because we are interested in assessing the sustainability of a particular policy scenario, we do not consider independent fiscal policy shocks or the endogenous policy response to shocks.

Retrospective Population Pharmacokinetic Analysis of Levetiracetam in Children and??Adolescents with Epilepsy

To characterize levetiracetam pharmacokinetics, identify significant covariate relationships and identify doses in children that achieve blood concentrations similar to those observed in adults. Nonlinear mixed-effects modelling was used to analyse pooled data collected from 228 children with epilepsy aged 3 months to 18 years in five trials of adjunctive levetiracetam therapy. Simulations were used to identify dosing regimens achieving levetiracetam steady-state peak and trough plasma concentrations similar to those attained in adults receiving the recommended starting dose for adjunctive therapy (500 mg twice daily). The covariates considered for inclusion in the base model were age, bodyweight, gender, race, body surface area (BSA), body mass index (BMI), creatinine clearance (CL(CR)), levetiracetam dose, concomitant antiepileptic drug (AED) by category (neutral, enzyme inducer, inhibitor, combination of inducer and inhibitor), and benzodiazepines. A one-compartment model with first-order absorption and elimination best characterized the data. The following significant covariates were identified: (i) age on the absorption rate constant (k(a)); (ii) bodyweight, dose, CL(CR) and concomitant enzyme-inducing AED on plasma oral clearance (CL/F); and (iii) bodyweight on the apparent volume of distribution after oral administration (V(d)/F). The main explanatory covariates were age on k(a), bodyweight on CL/F and V(d)/F, and enzyme-inducing AED on CL/F, of which bodyweight was the most influential covariate. Dosing can be carried out with either 10 mg/kg of oral solution twice daily in children weighing <50 kg and a 500-mg tablet twice daily in those weighing >50 kg or, when patients favour a solid formulation, 10 mg/kg of oral solution twice daily in children weighing <20 kg, a 250-mg tablet twice daily in those weighing 20-40 kg, and a 500-mg tablet twice daily in those weighing >40 kg. All of these doses achieved steady-state peak and trough plasma concentrations similar to those observed in adults following the recommended starting dose for adjunctive therapy (500 mg twice daily). The most influential covariate of levetiracetam pharmacokinetics in children is bodyweight. A starting dose of levetiracetam 10 mg/kg twice daily ensures the same exposure in children as does 500 mg twice daily in adults.

Association Analysis of Historical Bread Wheat Germplasm Using Additive Genetic Covariance of Relatives and Population Structure

Linkage disequilibrium can be used for identifying associations between traits of interest and genetic markers. This study used mapped diversity array technology (DArT) markers to find associations with resistance to stem rust, leaf rust, yellow rust, and powdery mildew, plus grain yield in five historical wheat international multienvironment trials from the International Maize and Wheat Improvement Center (CIMMYT). Two linear mixed models were used to assess marker-trait associations incorporating information on population structure and covariance between relatives. An integrated map containing 813 DArT markers and 831 other markers was constructed. Several linkage disequilibrium clusters bearing multiple host plant resistance genes were found. Most of the associated markers were found in genomic regions where previous reports had found genes or quantitative trait loci (QTL) influencing the same traits, providing an independent validation of this approach. In addition, many new chromosome regions for disease resistance and grain yield were identified in the wheat genome. Phenotyping across up to 60 environments and years allowed modeling of genotype x environment interaction, thereby making possible the identification of markers contributing to both additive and additive x additive interaction effects of traits.

ON RANK ESTIMATION IN SYMMETRIC MATRICES: THE CASE OF INDEFINITE MATRIX ESTIMATORS

In this paper we consider estimating the rank of an unknown symmetric matrix based on a symmetric, asymptotically normal estimator of the matrix. The related positive definite limit covariance matrix is assumed to be estimated consistently and to have either a Kronecker product or an arbitrary structure. These assumptions are standard although they exclude the case when the matrix estimator is positive or negative semidefinite. We adapt and reexamine here some available rank tests and introduce a new rank test based on the sum of eigenvalues of the matrix estimator. We discuss two applications where rank estimation in symmetric matrices is of interest, and we also provide a small simulation study.The first author acknowledges the support of an Alfred P. Sloan Foundation Research Fellowship and NSF Grant SES-0196372. We thank the co-editor and the two referees for useful comments and suggestions. CEMPRE—Centro de Estudos Macroeconómicos e Previsão—is supported by the Fundação para a Ciência e a Tecnologia, Portugal, through the Programa Operacional Ciência, Tecnologia e Inovação (POCTI) of the Quadro Comunitário de Apoio III, which is financed by FEDER and Portuguese funds.

Socioeconomic Status Predicts Objective and Subjective Sleep Quality in Aging Women

To test the hypothesis that socioeconomic status (SES) would be associated with sleep quality measured objectively, even after controlling for related covariates (health status, psychosocial characteristics). Epidemiological studies linking SES and sleep quality have traditionally relied on self-reported assessments of sleep. Ninety-four women, 61 to 90 years of age, participated in this study. SES was determined by pretax household income and years of education. Objective and subjective assessments of sleep quality were obtained using the NightCap sleep system and the Pittsburgh Sleep Quality Index (PSQI), respectively. Health status was determined by subjective health ratings and objective measures of recent and chronic illnesses. Depressive symptoms and neuroticism were quantified using the Center for Epidemiological Studies Depression Scale and the Neuroticism subscale of the NEO Personality Inventory, respectively. Household income significantly predicted sleep latency and sleep efficiency even after adjusting for demographic factors, health status, and psychosocial characteristics. Income also predicted PSQI scores, although this association was significantly attenuated by inclusion of neuroticism in multivariate analyses. Education predicted both sleep latency and sleep efficiency, but the latter association was partially reduced after health status and psychosocial measures were included in analyses. Education predicted PSQI sleep efficiency component scores, but not global scores. These results suggest that SES is robustly linked to both subjective and objective sleep quality, and that health status and psychosocial characteristics partially explain these associations.

Neurological care and risk of hospital mortality for patients with myasthenia gravis in England

Background:Myasthenia gravis (MG) is a rare neurological disorder, which can be life threatening. Although death is a rare outcome, evidence does not exist as to whether neurological care leads to...

A Framework of Statistical Tests For Comparing Mean and Covariance Structure Models

Although statistical procedures are well-known for comparing hierarchically related (nested) mean and covariance structure models, statistical tests for comparing non-hierarchically related (nonnested) models have proven more elusive. Although isolated attempts at statistical tests of non-hierarchically related models have been made, none exist within the commonly used maximum likelihood estimation framework, thereby compromising these methods' accessibility and general applicability. Building on general theory developed by Vuong (1989) and techniques for establishing the relation between covariance structure models (Raykov & Penev, 1999), this work provides a general paradigm for conducting statistical tests on competing mean and covariance structure models. The proposed framework is appropriate for hierarchically related models as well as non-hierarchically related models. In developing the structure of the framework, key aspects of model equivalence, relation, and comparison are unified. An illustration demonstrates its use.

Intraclass Correlation Values for Planning Group-Randomized Trials in Education

Experiments that assign intact groups to treatment conditions are increasingly common in social research. In educational research, the groups assigned are often schools. The design of group-randomized experiments requires knowledge of the intraclass correlation structure to compute statistical power and sample sizes required to achieve adequate power. This article provides a compilation of intraclass correlation values of academic achievement and related covariate effects that could be used for planning group-randomized experiments in education. It also provides variance component information that is useful in planning experiments involving covariates. The use of these values to compute the statistical power of group-randomized experiments is illustrated.

Low frequency motions and motion sickness on a tilting train

Tilting trains have been developed to reduce rail transport times by allowing greater train speeds without increased discomfort from increased lateral acceleration. It is reported that passengers on tilting trains experience motion sickness, but there have been few published studies of motions of tilting trains and the associated sickness. This paper presents the motion and motion sickness on an experimental tilting train during two trials: the first involved 200 subjects on five return journeys, the second involved 445 subjects and 14 return journeys. For each journey, lateral and vertical translational accelerations and roll velocities were measured in the passenger car-body. Simultaneously, subjects assessed their motion sickness at periodic intervals using an illness rating scale. The characteristics of the translational acceleration and roll velocity were investigated for each journey and the covariant relationships between the low frequency motions were explored. Illness ratings were found to be correlated with the vertical acceleration and roll velocity. A single motion variable is considered insufficient to predict motion sickness on tilting trains.

Testing Genetic Linkage with Relative Pairs and Covariates by Quasi-Likelihood Score Statistics

Background/Aims: Genetic linkage analysis of common diseases is complicated by the heterogeneity of genetic and environmental factors that increase disease risk, and possibly interactions among them. Most linkage methods that account for covariates are restricted to sib pairs, with the exception of the conditional logistic regression model [<citeref rid="ref001">1</citeref>] implemented in LODPAL in the S.A.G.E. software [<citeref rid="ref002">2</citeref>]. Although this model can be applied to arbitrary pedigrees, at times it can be difficult to maximize the likelihood due to model constraints, and it does not account for the dependence among the different types of relative pairs in a pedigree. Methods: To overcome these limitations, we developed a new approach based on score statistics for quasi- likelihoods, implemented as weighted least squares. Our methods can be used to test three different hypotheses: (1) a test for linkage without covariates; (2) a test for linkage with covariates, and (3) a test for effects of covariates on identity by descent sharing (i.e., heterogeneity). Furthermore, our methods are robust because they account for the dependence among different relative pairs within a pedigree. Results and Conclusion: Although application of our methods to a prostate cancer linkage study did not find any critical covariates in our data, the results illustrate the utility and interpretation of our methods, and suggest, nonetheless, that our methods will be useful for a broad range of genetic linkage heterogeneity analyses.

Modeling Additive × Environment and Additive × Additive × Environment Using Genetic Covariances of Relatives of Wheat Genotypes

ABSTRACTIn self‐pollinated species, the variance–covariance matrix of breeding values of the genetic strains evaluated in multienvironment trials (MET) can be partitioned into additive effects, additive × additive effects, and their interaction with environments. The additive relationship matrix A can be used to derive the additive × additive genetic variance–covariance relationships among strains, Ã. This study shows how to separate total genetic effects into additive and additive × additive and how to model the additive × environment interaction and additive × additive × environment interaction by incorporating variance–covariance structures constructed as the Kronecker product of a factor‐analytic model across sites and the additive (A) and additive × additive relationships (Ã), between strains. Two CIMMYT international trials were used for illustration. Results show that partitioning the total genotypic effects into additive and additive × additive and their interactions with environments is useful for identifying wheat (Triticum aestivum L.) lines with high additive effects (to be used in crossing programs) as well as high overall production. Some lines and environments had high positive additive × environment interaction patterns, whereas other lines and environments showed a different additive × additive × environment interaction pattern.

Survival Analysis for Gastric Cancer Using the Japanese Foundation Database Based on a Generalized Hazards Model Incorporating B-spline Functions

The Japanese Foundation for Cancer Research (JFCR) has provided a large database on gastric cancer for open use comprised of data on survival times after surgery and related covariates including prognostic factors. Data analysis based on the generalized hazards model incorporating the B-spline function (GHMBS) was performed using a dataset (JFCR dataset) composed of 9,631 cases within this database. A model selection method was adopted for clarifying the meaning of estimated parameters, because the GHMBS was comprised of the proportional hazards model (PHM) and accelerated failure time model (AFTM) as submodels. A preliminary simulation experiment to examine the performance of the model selection method based on the GHMBS was conducted under the condition that multiple covariates were considered, where one was the target covariate and the other was covariate for adjustment. After validation of the method by this simulation experiment, the method was applied to the JFCR dataset to estimate the period effect for prolonging survival time with an adjustment for the stage effect. The analysis revealed that the PHM was suitable for the period effect, while a mixture of the PHM and AFTM was for the stage effect and treatment for gastric cancer made steady progress from the 1950s through the 1990s.

Detection of Spatial Clusters

In this article, we develop the first detailed illustration of the use of a cluster detection method using a spatial scan statistic based on an exponential survival model. We use this approach to study the spatial patterns of survival of patients with stage III or stage IV colorectal cancer or with stage I/II, stage III, or stage IV lung cancer in the State of California and the County of Los Angeles (LA) diagnosed during 1988 through 2002. We present the location of the detected clusters of short survival or long survival and compute nonparametric estimates of survival inside and outside of those detected clusters confirming the survival pattern detected by the spatial scan statistic in both areas. In LA County, we investigate the possible relationship between the cluster locations and race, sex, and histology using nonparametric methods, and we compare socioeconomic factors such as education, employment, income, and health insurance inside and outside of the detected clusters. Finally, we evaluate the effect of related covariates on statistically significant long and short survival clusters detected in LA County using logistic regression models. This article illustrates a new way to understand survival patterns that may point to health disparities in terms of diagnosis and treatment patterns.

Genetic and environmental contributions to serum ascorbic acid concentrations: the Stanislas Family Study

Although numerous environmental factors are documented to influence serum ascorbic concentrations, little is known about the genetic versus environmental contributions to variation of this trait. The aim of this study was to estimate family correlation and, additive genetic heritability and household effects in a variance component analysis for serum ascorbic acid concentrations. In a sample of ninety French families, information was obtained regarding serum ascorbic acid concentrations, usual dietary intake, lifestyle, and other related covariates. Spouse, parent-offspring and offspring-offspring significant correlation coefficients for serum ascorbic acid concentrations, adjusted for age, cigarette consumption and oral contraceptive use, were 0.432, 0.298 and 0.485, respectively, and for adjusted values for additional diet covariates (vitamin C intake and fruit and vegetable consumption), were 0.362, 0.154 and 0.348, respectively. Variance component analysis for serum ascorbic concentrations showed no significant genetic contribution to variability of this trait. Conversely, household common environment accounted for 27.7 and 42.6% in parents and offspring, respectively, after adjustment for age, cigarette consumption and oral contraceptive use. After adjustment for the two additional diet covariates (vitamin C intake and fruit and vegetable consumption) household common variance decreased to 13.6 and 30.5% in parents and offspring, respectively. These results show that serum ascorbic acid concentrations aggregate within healthy families partly due to diet intake but without a significant genetic component.

DYNAMIC MODELS FOR TESTING BASED ON TIME SERIES ANALYSIS

In this paper, we investigate a dynamic software quality model that incorporates software process and software product measures as covariates. Furthermore, the model is not based on execution time between failures. Instead, the method relies on data commonly available from simple problem tracking and source code control systems. Fault counts, testing effort, and code churn measures are collected from each build during the system test phase of a large telecommunications software system. We use this data to predict the number of faults to expect from one build to the next. The technique we use is called time series analysis and forecasting. The methodology assumes that future predictions are based on the history of past failures and related covariates. We show that the quality model incorporating testing effort as a covariate is better than the quality model derived from fault counts alone.

Existence and uniqueness of solutions of semilinear stochastic infinite-dimensional differential systems with H-regular noise

Existence and uniqueness of approximate strong solutions of stochastic infinite-dimensional systems d u = [ A ( t ) u + B ( t , u ) ] d t + G ( t , u ) d W , u ( 0 , ⋅ ) = u 0 ∈ H , t ⩾ 0 with local Lipschitz-continuous, time-depending nonrandom operators A , B and G acting on a separable Hilbert space H are studied. For this purpose, some monotonicity conditions on those operators and an existing U-series expansion of the space–time Wiener process W ( U-valued, U ⊆ H , U Hilbert space) with ∑ n = 1 + ∞ α n 2 < + ∞ belonging to the trace of related covariance operator Q of W with local noise intensities α n 2 ∈ R 1 as eigenvalues of Q are exploited.

Airborne LaCoste &amp; Romberg gravimetry: a space domain approach

This paper introduces a new approach to reduce the airborne gravity data acquired by a LaCoste & Romberg (L&R) air/sea gravimeter, or other similar gravimeters. The acceleration exerted on the gravimeter is the sum of gravity and the vertical and Eotvos accelerations of the aircraft. The L&R gravimeter outputs are: (1) the beam position, (2) the spring tension and (3) the cross coupling. Vertical and Eotvos accelerations are computed from GPS-derived aircraft positions. However, the vertical perturbing acceleration sensed by the gravimeter is not the same as the one sensed by the aircraft (via GPS). A determination of the aircraft-to-sensor transfer function is necessary. The second-order differential equation of the motion of the gravimeter’s beam mixes all the input and output parameters of the gravimeter. Conventionally, low-pass filtering in the frequency domain is used to extract the gravity signal, the filter being applied to each flight-line individually. By transforming the differential equation into an integral equation and by introducing related covariance matrices, we develop a new filtering method based on a least-squares approach that is able to take into account, in one stage, the data corresponding to all flight-lines. The a posteriori covariance matrix of the estimated gravity signal is an internal criterion of the precision of the method. As an example, we estimate the gravity values along the flight-lines from an airborne gravity survey over the Alps and introduce an a priori covariance matrix of the gravity disturbances from a global geopotential model. This matrix is used to regularize the ill-posed Fredholm integral equation introduced in this paper.

Circumcision Status and Risk of Sexually Transmitted Infection in Young Adult Males: An Analysis of a Longitudinal Birth Cohort

Previous research suggests that male circumcision may be a protective factor against the acquisition of sexually transmitted infections; however, studies examining this question have produced mixed results. The aim of this study was to examine the association between circumcision status and sexually transmitted infection risk using a longitudinal birth cohort study. Data were gathered as part of the Christchurch Health and Development Study, a 25-year longitudinal study of a birth cohort of New Zealand children. Information was obtained on: (1) the circumcision status of males in the cohort before 15 years old, (2) measures of self-reported sexually transmitted infection from ages 18 to 25 years, and (3) childhood, family, and related covariate factors. Being uncircumcised had a statistically significant bivariate association with self-reported sexually transmitted infection. Adjustment for potentially confounding factors, including number of sexual partners and unprotected sex, as well as background and family factors related to circumcision, did not reduce the association between circumcision status and reports of sexually transmitted infection. Estimates of the population-attributable risk suggested that universal neonatal circumcision would have reduced rates of sexually transmitted infection in this cohort by 48.2%. These findings suggest that uncircumcised males are at greater risk of acquiring sexually transmitted infection than circumcised males. Male circumcision may reduce the risk of sexually transmitted infection acquisition and transmission by up to one half, suggesting substantial benefits accruing from routine neonatal circumcision.

214 POSTER Characterization of a recombinant, fully human monoclonal antibody directed against the human insulin-like growth factor-1 receptor

The fault-tolerant integrated navigation methods using strapdown inertial navigation system (SINS) and global navigation satellite system (GNSS) for unmanned aerial vehicles (UAVs) are studied herein to address two types of possible faults, system fault and measurement fault. Two typical approximation-based nonlinear filters, extended Kalman filter (EKF) and divided difference Kalman filters (DDKFs), are modified to be fault-tolerant for accurate navigation even in the presence of these faults. Criteria are presented to detect the faults, and related covariance matrices of the predicted errors are enlarged using fault accommodation factors to make the faulty state or measurement components be normally treated. Navigation simulations using the nonlinear quaternion-based navigation error model are given to demonstrate the effectiveness of the proposed methods.