Statistical analysis and interpretation of prenatal diagnostic imaging studies, Part 2: descriptive and inferential statistical methods.

PubMed

Tuuli, Methodius G; Odibo, Anthony O

2011-08-01

The objective of this article is to discuss the rationale for common statistical tests used for the analysis and interpretation of prenatal diagnostic imaging studies. Examples from the literature are used to illustrate descriptive and inferential statistics. The uses and limitations of linear and logistic regression analyses are discussed in detail.

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery - part II: an illustrative example.

PubMed

Cevenini, Gabriele; Barbini, Emanuela; Scolletta, Sabino; Biagioli, Bonizella; Giomarelli, Pierpaolo; Barbini, Paolo

2007-11-22

Popular predictive models for estimating morbidity probability after heart surgery are compared critically in a unitary framework. The study is divided into two parts. In the first part modelling techniques and intrinsic strengths and weaknesses of different approaches were discussed from a theoretical point of view. In this second part the performances of the same models are evaluated in an illustrative example. Eight models were developed: Bayes linear and quadratic models, k-nearest neighbour model, logistic regression model, Higgins and direct scoring systems and two feed-forward artificial neural networks with one and two layers. Cardiovascular, respiratory, neurological, renal, infectious and hemorrhagic complications were defined as morbidity. Training and testing sets each of 545 cases were used. The optimal set of predictors was chosen among a collection of 78 preoperative, intraoperative and postoperative variables by a stepwise procedure. Discrimination and calibration were evaluated by the area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness-of-fit test, respectively. Scoring systems and the logistic regression model required the largest set of predictors, while Bayesian and k-nearest neighbour models were much more parsimonious. In testing data, all models showed acceptable discrimination capacities, however the Bayes quadratic model, using only three predictors, provided the best performance. All models showed satisfactory generalization ability: again the Bayes quadratic model exhibited the best generalization, while artificial neural networks and scoring systems gave the worst results. Finally, poor calibration was obtained when using scoring systems, k-nearest neighbour model and artificial neural networks, while Bayes (after recalibration) and logistic regression models gave adequate results. Although all the predictive models showed acceptable discrimination performance in the example considered, the Bayes and logistic regression models seemed better than the others, because they also had good generalization and calibration. The Bayes quadratic model seemed to be a convincing alternative to the much more usual Bayes linear and logistic regression models. It showed its capacity to identify a minimum core of predictors generally recognized as essential to pragmatically evaluate the risk of developing morbidity after heart surgery.

A trend analysis of laboratory positive propoxyphene workplace urine drug screens before and after the product recall.

PubMed

Price, James

2015-01-01

Propoxyphene was withdrawn from the US market in November 2010. This drug is still tested for in the workplace as part of expanded panel nonregulated testing. A convenience sample of urine specimens (n = 7838) were provided by workers from various industries. The percentage of positive specimens with 95% confidence intervals was calculated for each year of the study. Logistic regression was used to assess the impact of the year upon the propoxyphene result. The prevalence of positive propoxyphene tests was much higher before the product's withdrawal from the market. Logistic regression provided evidence of a decreasing linear trend (P < 0.000; β = -0.71). The odds ratio signifies that for every additional year the urine specimens were 0.49 times less likely to be positive for propoxyphene. This favors the determination that the change in propoxyphene positive drug test over the years is not by chance. The conclusion supports no longer performing nonregulated workplace propoxyphene urine drug testing for this population.

Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

PubMed

Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

2016-05-01

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Classification of sodium MRI data of cartilage using machine learning.

PubMed

Madelin, Guillaume; Poidevin, Frederick; Makrymallis, Antonios; Regatte, Ravinder R

2015-11-01

To assess the possible utility of machine learning for classifying subjects with and subjects without osteoarthritis using sodium magnetic resonance imaging data. Theory: Support vector machine, k-nearest neighbors, naïve Bayes, discriminant analysis, linear regression, logistic regression, neural networks, decision tree, and tree bagging were tested. Sodium magnetic resonance imaging with and without fluid suppression by inversion recovery was acquired on the knee cartilage of 19 controls and 28 osteoarthritis patients. Sodium concentrations were measured in regions of interests in the knee for both acquisitions. Mean (MEAN) and standard deviation (STD) of these concentrations were measured in each regions of interest, and the minimum, maximum, and mean of these two measurements were calculated over all regions of interests for each subject. The resulting 12 variables per subject were used as predictors for classification. Either Min [STD] alone, or in combination with Mean [MEAN] or Min [MEAN], all from fluid suppressed data, were the best predictors with an accuracy >74%, mainly with linear logistic regression and linear support vector machine. Other good classifiers include discriminant analysis, linear regression, and naïve Bayes. Machine learning is a promising technique for classifying osteoarthritis patients and controls from sodium magnetic resonance imaging data. © 2014 Wiley Periodicals, Inc.

Garment Counting in a Textile Warehouse by Means of a Laser Imaging System

PubMed Central

Martínez-Sala, Alejandro Santos; Sánchez-Aartnoutse, Juan Carlos; Egea-López, Esteban

2013-01-01

Textile logistic warehouses are highly automated mechanized places where control points are needed to count and validate the number of garments in each batch. This paper proposes and describes a low cost and small size automated system designed to count the number of garments by processing an image of the corresponding hanger hooks generated using an array of phototransistors sensors and a linear laser beam. The generated image is processed using computer vision techniques to infer the number of garment units. The system has been tested on two logistic warehouses with a mean error in the estimated number of hangers of 0.13%. PMID:23628760

Garment counting in a textile warehouse by means of a laser imaging system.

PubMed

Martínez-Sala, Alejandro Santos; Sánchez-Aartnoutse, Juan Carlos; Egea-López, Esteban

2013-04-29

Textile logistic warehouses are highly automated mechanized places where control points are needed to count and validate the number of garments in each batch. This paper proposes and describes a low cost and small size automated system designed to count the number of garments by processing an image of the corresponding hanger hooks generated using an array of phototransistors sensors and a linear laser beam. The generated image is processed using computer vision techniques to infer the number of garment units. The system has been tested on two logistic warehouses with a mean error in the estimated number of hangers of 0.13%.

Assessing contaminant sensitivity of endangered and threatened aquatic species: part II. Chronic toxicity of copper and pentachlorophenol to two endangered species and two surrogate species.

PubMed

Besser, J M; Wang, N; Dwyer, F J; Mayer, F L; Ingersoll, C G

2005-02-01

Early life-stage toxicity tests with copper and pentachlorophenol (PCP) were conducted with two species listed under the United States Endangered Species Act (the endangered fountain darter, Etheostoma fonticola, and the threatened spotfin chub, Cyprinella monacha) and two commonly tested species (fathead minnow, Pimephales promelas, and rainbow trout, Oncorhynchus mykiss). Results were compared using lowest-observed effect concentrations (LOECs) based on statistical hypothesis tests and by point estimates derived by linear interpolation and logistic regression. Sublethal end points, growth (mean individual dry weight) and biomass (total dry weight per replicate) were usually more sensitive than survival. The biomass end point was equally sensitive as growth and had less among-test variation. Effect concentrations based on linear interpolation were less variable than LOECs, which corresponded to effects ranging from 9% to 76% relative to controls and were consistent with thresholds based on logistic regression. Fountain darter was the most sensitive species for both chemicals tested, with effect concentrations for biomass at < or = 11 microg/L (LOEC and 25% inhibition concentration [IC25]) for copper and at 21 microg/L (IC25) for PCP, but spotfin chub was no more sensitive than the commonly tested species. Effect concentrations for fountain darter were lower than current chronic water quality criteria for both copper and PCP. Protectiveness of chronic water-quality criteria for threatened and endangered species could be improved by the use of safety factors or by conducting additional chronic toxicity tests with species and chemicals of concern.

Assessing contaminant sensitivity of endangered and threatened aquatic species: Part II. chronic toxicity of copper and pentachlorophenol to two endangered species and two surrogate species

USGS Publications Warehouse

Besser, J.M.; Wang, N.; Dwyer, F.J.; Mayer, F.L.; Ingersoll, C.G.

2005-01-01

Early life-stage toxicity tests with copper and pentachlorophenol (PCP) were conducted with two species listed under the United States Endangered Species Act (the endangered fountain darter, Etheostoma fonticola, and the threatened spotfin chub, Cyprinella monacha) and two commonly tested species (fathead minnow, Pimephales promelas, and rainbow trout, Oncorhynchus mykiss). Results were compared using lowest-observed effect concentrations (LOECs) based on statistical hypothesis tests and by point estimates derived by linear interpolation and logistic regression. Sublethal end points, growth (mean individual dry weight) and biomass (total dry weight per replicate) were usually more sensitive than survival. The biomass end point was equally sensitive as growth and had less among-test variation. Effect concentrations based on linear interpolation were less variable than LOECs, which corresponded to effects ranging from 9% to 76% relative to controls and were consistent with thresholds based on logistic regression. Fountain darter was the most sensitive species for both chemicals tested, with effect concentrations for biomass at ??? 11 ??g/L (LOEC and 25% inhibition concentration [IC25]) for copper and at 21 ??g/L (IC25) for PCP, but spotfin chub was no more sensitive than the commonly tested species. Effect concentrations for fountain darter were lower than current chronic water quality criteria for both copper and PCP. Protectiveness of chronic water-quality criteria for threatened and endangered species could be improved by the use of safety factors or by conducting additional chronic toxicity tests with species and chemicals of concern. ?? 2005 Springer Science+Business Media, Inc.

Comparing Alternative Kernels for the Kernel Method of Test Equating: Gaussian, Logistic, and Uniform Kernels. Research Report. ETS RR-08-12

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; von Davier, Alina A.

2008-01-01

The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…

The Dropout Learning Algorithm

PubMed Central

Baldi, Pierre; Sadowski, Peter

2014-01-01

Dropout is a recently introduced algorithm for training neural network by randomly dropping units during training to prevent their co-adaptation. A mathematical analysis of some of the static and dynamic properties of dropout is provided using Bernoulli gating variables, general enough to accommodate dropout on units or connections, and with variable rates. The framework allows a complete analysis of the ensemble averaging properties of dropout in linear networks, which is useful to understand the non-linear case. The ensemble averaging properties of dropout in non-linear logistic networks result from three fundamental equations: (1) the approximation of the expectations of logistic functions by normalized geometric means, for which bounds and estimates are derived; (2) the algebraic equality between normalized geometric means of logistic functions with the logistic of the means, which mathematically characterizes logistic functions; and (3) the linearity of the means with respect to sums, as well as products of independent variables. The results are also extended to other classes of transfer functions, including rectified linear functions. Approximation errors tend to cancel each other and do not accumulate. Dropout can also be connected to stochastic neurons and used to predict firing rates, and to backpropagation by viewing the backward propagation as ensemble averaging in a dropout linear network. Moreover, the convergence properties of dropout can be understood in terms of stochastic gradient descent. Finally, for the regularization properties of dropout, the expectation of the dropout gradient is the gradient of the corresponding approximation ensemble, regularized by an adaptive weight decay term with a propensity for self-consistent variance minimization and sparse representations. PMID:24771879

Testing for gene-environment interaction under exposure misspecification.

PubMed

Sun, Ryan; Carroll, Raymond J; Christiani, David C; Lin, Xihong

2017-11-09

Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties. © 2017, The International Biometric Society.

Forecasting Air Force Logistics Command Second Destination Transportation: An Application of Multiple Regression Analysis and Neural Networks

DTIC Science & Technology

1990-09-01

without the help from the DSXR staff. William Lyons, Charles Ramsey , and Martin Meeks went above and beyond to help complete this research. Special...develop a valid forecasting model that is significantly more accurate than the one presently used by DSXR and suggested the development and testing of a...method, Strom tested DSXR’s iterative linear regression forecasting technique by examining P1 in the simple regression equation to determine whether

Unitary Response Regression Models

ERIC Educational Resources Information Center

Lipovetsky, S.

2007-01-01

The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies

PubMed Central

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-01-01

Abstract Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. PMID:29106476

Automatic Ammunition Identification Technology Project. Ammunition Logistics Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weil, B.

1993-03-01

The Automatic Ammunition Identification Technology (AAIT) Project is an activity of the Robotics & Process Systems Division at the Oak Ridge National Laboratory (ORNL) for the US Army`s Project Manager-Ammunition Logistics (PM-AMMOLOG) at the Picatinny Arsenal in Picatinny, New Jersey. The project objective is to evaluate new two-dimensional bar code symbologies for potential use in ammunition logistics systems and automated reloading equipment. These new symbologies are a significant improvement over typical linear bar codes since machine-readable alphanumeric messages up to 2000 characters long are achievable. These compressed data symbologies are expected to significantly improve logistics and inventory management tasks andmore » permit automated feeding and handling of ammunition to weapon systems. The results will be increased throughout capability, better inventory control, reduction of human error, lower operation and support costs, and a more timely re-supply of various weapon systems. This paper will describe the capabilities of existing compressed data symbologies and the symbol testing activities being conducted at ORNL for the AAIT Project.« less

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

PubMed Central

2011-01-01

Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5. Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. PMID:21849043

Secure Logistic Regression Based on Homomorphic Encryption: Design and Evaluation

PubMed Central

Song, Yongsoo; Wang, Shuang; Xia, Yuhou; Jiang, Xiaoqian

2018-01-01

Background Learning a model without accessing raw data has been an intriguing idea to security and machine learning researchers for years. In an ideal setting, we want to encrypt sensitive data to store them on a commercial cloud and run certain analyses without ever decrypting the data to preserve privacy. Homomorphic encryption technique is a promising candidate for secure data outsourcing, but it is a very challenging task to support real-world machine learning tasks. Existing frameworks can only handle simplified cases with low-degree polynomials such as linear means classifier and linear discriminative analysis. Objective The goal of this study is to provide a practical support to the mainstream learning models (eg, logistic regression). Methods We adapted a novel homomorphic encryption scheme optimized for real numbers computation. We devised (1) the least squares approximation of the logistic function for accuracy and efficiency (ie, reduce computation cost) and (2) new packing and parallelization techniques. Results Using real-world datasets, we evaluated the performance of our model and demonstrated its feasibility in speed and memory consumption. For example, it took approximately 116 minutes to obtain the training model from the homomorphically encrypted Edinburgh dataset. In addition, it gives fairly accurate predictions on the testing dataset. Conclusions We present the first homomorphically encrypted logistic regression outsourcing model based on the critical observation that the precision loss of classification models is sufficiently small so that the decision plan stays still. PMID:29666041

Higher direct bilirubin levels during mid-pregnancy are associated with lower risk of gestational diabetes mellitus.

PubMed

Liu, Chaoqun; Zhong, Chunrong; Zhou, Xuezhen; Chen, Renjuan; Wu, Jiangyue; Wang, Weiye; Li, Xiating; Ding, Huisi; Guo, Yanfang; Gao, Qin; Hu, Xingwen; Xiong, Guoping; Yang, Xuefeng; Hao, Liping; Xiao, Mei; Yang, Nianhong

2017-01-01

Bilirubin concentrations have been recently reported to be negatively associated with type 2 diabetes mellitus. We examined the association between bilirubin concentrations and gestational diabetes mellitus. In a prospective cohort study, 2969 pregnant women were recruited prior to 16 weeks of gestation and were followed up until delivery. The value of bilirubin was tested and oral glucose tolerance test was conducted to screen gestational diabetes mellitus. The relationship between serum bilirubin concentration and gestational weeks was studied by two-piecewise linear regression. A subsample of 1135 participants with serum bilirubin test during 16-18 weeks gestation was conducted to research the association between serum bilirubin levels and risk of gestational diabetes mellitus by logistic regression. Gestational diabetes mellitus developed in 8.5 % of the participants (223 of 2969). Two-piecewise linear regression analyses demonstrated that the levels of bilirubin decreased with gestational week up to the turning point 23 and after that point, levels of bilirubin were increased slightly. In multiple logistic regression analysis, the relative risk of developing gestational diabetes mellitus was lower in the highest tertile of direct bilirubin than that in the lowest tertile (RR 0.60; 95 % CI, 0.35-0.89). The results suggested that women with higher serum direct bilirubin levels during the second trimester of pregnancy have lower risk for development of gestational diabetes mellitus.

Transport spatial model for the definition of green routes for city logistics centers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pamučar, Dragan, E-mail: dpamucar@gmail.com; Gigović, Ljubomir, E-mail: gigoviclj@gmail.com; Ćirović, Goran, E-mail: cirovic@sezampro.rs

This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas.more » The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.« less

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies.

PubMed

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-11-01

Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

NASA Astrophysics Data System (ADS)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

Standards for Standardized Logistic Regression Coefficients

ERIC Educational Resources Information Center

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

A predictive model for early mortality after surgical treatment of heart valve or prosthesis infective endocarditis. The EndoSCORE.

PubMed

Di Mauro, Michele; Dato, Guglielmo Mario Actis; Barili, Fabio; Gelsomino, Sandro; Santè, Pasquale; Corte, Alessandro Della; Carrozza, Antonio; Ratta, Ester Della; Cugola, Diego; Galletti, Lorenzo; Devotini, Roger; Casabona, Riccardo; Santini, Francesco; Salsano, Antonio; Scrofani, Roberto; Antona, Carlo; Botta, Luca; Russo, Claudio; Mancuso, Samuel; Rinaldi, Mauro; De Vincentiis, Carlo; Biondi, Andrea; Beghi, Cesare; Cappabianca, Giangiuseppe; Tarzia, Vincenzo; Gerosa, Gino; De Bonis, Michele; Pozzoli, Alberto; Nicolini, Francesco; Benassi, Filippo; Rosato, Francesco; Grasso, Elena; Livi, Ugolino; Sponga, Sandro; Pacini, Davide; Di Bartolomeo, Roberto; De Martino, Andrea; Bortolotti, Uberto; Onorati, Francesco; Faggian, Giuseppe; Lorusso, Roberto; Vizzardi, Enrico; Di Giammarco, Gabriele; Marinelli, Daniele; Villa, Emmanuel; Troise, Giovanni; Picichè, Marco; Musumeci, Francesco; Paparella, Domenico; Margari, Vito; Tritto, Francesco; Damiani, Girolamo; Scrascia, Giuseppe; Zaccaria, Salvatore; Renzulli, Attilio; Serraino, Giuseppe; Mariscalco, Giovanni; Maselli, Daniele; Foschi, Massimiliano; Parolari, Alessandro; Nappi, Giannantonio

2017-08-15

The aim of this large retrospective study was to provide a logistic risk model along an additive score to predict early mortality after surgical treatment of patients with heart valve or prosthesis infective endocarditis (IE). From 2000 to 2015, 2715 patients with native valve endocarditis (NVE) or prosthesis valve endocarditis (PVE) were operated on in 26 Italian Cardiac Surgery Centers. The relationship between early mortality and covariates was evaluated with logistic mixed effect models. Fixed effects are parameters associated with the entire population or with certain repeatable levels of experimental factors, while random effects are associated with individual experimental units (centers). Early mortality was 11.0% (298/2715); At mixed effect logistic regression the following variables were found associated with early mortality: age class, female gender, LVEF, preoperative shock, COPD, creatinine value above 2mg/dl, presence of abscess, number of treated valve/prosthesis (with respect to one treated valve/prosthesis) and the isolation of Staphylococcus aureus, Fungus spp., Pseudomonas Aeruginosa and other micro-organisms, while Streptococcus spp., Enterococcus spp. and other Staphylococci did not affect early mortality, as well as no micro-organisms isolation. LVEF was found linearly associated with outcomes while non-linear association between mortality and age was tested and the best model was found with a categorization into four classes (AUC=0.851). The following study provides a logistic risk model to predict early mortality in patients with heart valve or prosthesis infective endocarditis undergoing surgical treatment, called "The EndoSCORE". Copyright © 2017. Published by Elsevier B.V.

Secure Logistic Regression Based on Homomorphic Encryption: Design and Evaluation.

PubMed

Kim, Miran; Song, Yongsoo; Wang, Shuang; Xia, Yuhou; Jiang, Xiaoqian

2018-04-17

Learning a model without accessing raw data has been an intriguing idea to security and machine learning researchers for years. In an ideal setting, we want to encrypt sensitive data to store them on a commercial cloud and run certain analyses without ever decrypting the data to preserve privacy. Homomorphic encryption technique is a promising candidate for secure data outsourcing, but it is a very challenging task to support real-world machine learning tasks. Existing frameworks can only handle simplified cases with low-degree polynomials such as linear means classifier and linear discriminative analysis. The goal of this study is to provide a practical support to the mainstream learning models (eg, logistic regression). We adapted a novel homomorphic encryption scheme optimized for real numbers computation. We devised (1) the least squares approximation of the logistic function for accuracy and efficiency (ie, reduce computation cost) and (2) new packing and parallelization techniques. Using real-world datasets, we evaluated the performance of our model and demonstrated its feasibility in speed and memory consumption. For example, it took approximately 116 minutes to obtain the training model from the homomorphically encrypted Edinburgh dataset. In addition, it gives fairly accurate predictions on the testing dataset. We present the first homomorphically encrypted logistic regression outsourcing model based on the critical observation that the precision loss of classification models is sufficiently small so that the decision plan stays still. ©Miran Kim, Yongsoo Song, Shuang Wang, Yuhou Xia, Xiaoqian Jiang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 17.04.2018.

Assessing risk factors for periodontitis using regression

NASA Astrophysics Data System (ADS)

Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

2013-10-01

Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

Neck-focused panic attacks among Cambodian refugees; a logistic and linear regression analysis.

PubMed

Hinton, Devon E; Chhean, Dara; Pich, Vuth; Um, Khin; Fama, Jeanne M; Pollack, Mark H

2006-01-01

Consecutive Cambodian refugees attending a psychiatric clinic were assessed for the presence and severity of current--i.e., at least one episode in the last month--neck-focused panic. Among the whole sample (N=130), in a logistic regression analysis, the Anxiety Sensitivity Index (ASI; odds ratio=3.70) and the Clinician-Administered PTSD Scale (CAPS; odds ratio=2.61) significantly predicted the presence of current neck panic (NP). Among the neck panic patients (N=60), in the linear regression analysis, NP severity was significantly predicted by NP-associated flashbacks (beta=.42), NP-associated catastrophic cognitions (beta=.22), and CAPS score (beta=.28). Further analysis revealed the effect of the CAPS score to be significantly mediated (Sobel test [Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182]) by both NP-associated flashbacks and catastrophic cognitions. In the care of traumatized Cambodian refugees, NP severity, as well as NP-associated flashbacks and catastrophic cognitions, should be specifically assessed and treated.

Assessing the potential for improving S2S forecast skill through multimodel ensembling

NASA Astrophysics Data System (ADS)

Vigaud, N.; Robertson, A. W.; Tippett, M. K.; Wang, L.; Bell, M. J.

2016-12-01

Non-linear logistic regression is well suited to probability forecasting and has been successfully applied in the past to ensemble weather and climate predictions, providing access to the full probabilities distribution without any Gaussian assumption. However, little work has been done at sub-monthly lead times where relatively small re-forecast ensembles and lengths represent new challenges for which post-processing avenues have yet to be investigated. A promising approach consists in extending the definition of non-linear logistic regression by including the quantile of the forecast distribution as one of the predictors. So-called Extended Logistic Regression (ELR), which enables mutually consistent individual threshold probabilities, is here applied to ECMWF, CFSv2 and CMA re-forecasts from the S2S database in order to produce rainfall probabilities at weekly resolution. The ELR model is trained on seasonally-varying tercile categories computed for lead times of 1 to 4 weeks. It is then tested in a cross-validated manner, i.e. allowing real-time predictability applications, to produce rainfall tercile probabilities from individual weekly hindcasts that are finally combined by equal pooling. Results will be discussed over a broader North American region, where individual and MME forecasts generated out to 4 weeks lead are characterized by good probabilistic reliability but low sharpness, exhibiting systematically more skill in winter than summer.

Varicella infection is not associated with increasing prevalence of eczema: a U.S. population-based study.

PubMed

Li, J C; Silverberg, J I

2015-11-01

Chickenpox infection early in childhood has previously been shown to protect against the development of childhood eczema in line with the hygiene hypothesis. In 1995, the American Academy of Pediatrics recommended routine vaccination against varicella zoster virus in the United States. Subsequently, rates of chickenpox infection have dramatically decreased in childhood. We sought to understand the impact of declining rates of chickenpox infection on the prevalence of eczema. We analysed data from 207 007 children in the 1997-2013 National Health Interview Survey. One-year prevalence of eczema and 'ever had' history of chickenpox were analysed. Associations between chickenpox infection and eczema were tested using survey-weighted logistic regression. The impact of chickenpox on trends of eczema prevalence was tested using survey logistic regression and generalized linear models. Children with a history of chickenpox compared with those without chickenpox had a lower prevalence [survey-weighted logistic regression (95% confidence interval, CI)] of eczema [8·8% (8·5-9·0%) vs. 10·6% (10·4-10·8%)]. In pooled multivariate models controlling for age, sex, race/ethnicity, household income, highest level of household education, insurance coverage, U.S. birthplace and family size, eczema was inversely associated with chickenpox [adjusted odds ratio (95% CI), 0·90 (0·86-0·94), P < 0·001]. The prevalence of eczema significantly increased over time (Tukey post-hoc test, P < 0·001 for comparisons of survey years 2001-13 vs. 1997-2000, 2008-13 vs. 2001-04 and 2008-13 vs. 2005-07). In multivariate generalized linear models, the odds of eczema was not associated with chickenpox in 2001-13 (P ≥ 0·06). These findings suggest that lower rates of chickenpox infection secondary to widespread vaccination against varicella zoster virus are not contributing to higher rates of childhood eczema in the U.S. © 2015 British Association of Dermatologists.

Assessment of Advanced Logistics Delivery System (ALDS) Launch Systems Concepts

DTIC Science & Technology

2004-10-01

highest force vs. rotor weight required, allows much higher magnetic field generation than the linear induction or linear permanent magnet motors , and...provides the highest force vs. rotor weight required, allows much higher magnetic generation than the linear induction or linear permanent magnet motors , and

Interpretation of commonly used statistical regression models.

PubMed

Kasza, Jessica; Wolfe, Rory

2014-01-01

A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

Derivation of the linear-logistic model and Cox's proportional hazard model from a canonical system description.

PubMed

Voit, E O; Knapp, R G

1997-08-15

The linear-logistic regression model and Cox's proportional hazard model are widely used in epidemiology. Their successful application leaves no doubt that they are accurate reflections of observed disease processes and their associated risks or incidence rates. In spite of their prominence, it is not a priori evident why these models work. This article presents a derivation of the two models from the framework of canonical modeling. It begins with a general description of the dynamics between risk sources and disease development, formulates this description in the canonical representation of an S-system, and shows how the linear-logistic model and Cox's proportional hazard model follow naturally from this representation. The article interprets the model parameters in terms of epidemiological concepts as well as in terms of general systems theory and explains the assumptions and limitations generally accepted in the application of these epidemiological models.

Logistic models--an odd(s) kind of regression.

PubMed

Jupiter, Daniel C

2013-01-01

The logistic regression model bears some similarity to the multivariable linear regression with which we are familiar. However, the differences are great enough to warrant a discussion of the need for and interpretation of logistic regression. Copyright © 2013 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

Automatic Ammunition Identification Technology Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weil, B.

1993-01-01

The Automatic Ammunition Identification Technology (AAIT) Project is an activity of the Robotics Process Systems Division at the Oak Ridge National Laboratory (ORNL) for the US Army's Project Manager-Ammunition Logistics (PM-AMMOLOG) at the Picatinny Arsenal in Picatinny, New Jersey. The project objective is to evaluate new two-dimensional bar code symbologies for potential use in ammunition logistics systems and automated reloading equipment. These new symbologies are a significant improvement over typical linear bar codes since machine-readable alphanumeric messages up to 2000 characters long are achievable. These compressed data symbologies are expected to significantly improve logistics and inventory management tasks and permitmore » automated feeding and handling of ammunition to weapon systems. The results will be increased throughout capability, better inventory control, reduction of human error, lower operation and support costs, and a more timely re-supply of various weapon systems. This paper will describe the capabilities of existing compressed data symbologies and the symbol testing activities being conducted at ORNL for the AAIT Project.« less

Naval Research Logistics Quarterly. Volume 28. Number 3,

DTIC Science & Technology

1981-09-01

denotes component-wise maximum. f has antone (isotone) differences on C x D if for cl < c2 and d, < d2, NAVAL RESEARCH LOGISTICS QUARTERLY VOL. 28...or negative correlations and linear or nonlinear regressions. Given are the mo- ments to order two and, for special cases, (he regression function and...data sets. We designate this bnb distribution as G - B - N(a, 0, v). The distribution admits only of positive correlation and linear regressions

Use of logistic regression for modelling risk factors: with application to non-melanoma skin cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vitaliano, P.P.

Logistic regression was used to estimate the relative risk of basal and squamous skin cancer for such factors as cumulative lifetime solar exposure, age, complexion, and tannability. In previous reports, a subject's exposure was estimated indirectly, by latitude, or by the number of sun days in a subject's habitat. In contrast, these results are based on interview data gathered for each subject. A relatively new technique was used to estimate relative risk by controlling for confounding and testing for effect modification. A linear effect for the relative risk of cancer versus exposure was found. Tannability was shown to be amore » more important risk factor than complexion. This result is consistent with the work of Silverstone and Searle.« less

Avoiding overstating the strength of forensic evidence: Shrunk likelihood ratios/Bayes factors.

PubMed

Morrison, Geoffrey Stewart; Poh, Norman

2018-05-01

When strength of forensic evidence is quantified using sample data and statistical models, a concern may be raised as to whether the output of a model overestimates the strength of evidence. This is particularly the case when the amount of sample data is small, and hence sampling variability is high. This concern is related to concern about precision. This paper describes, explores, and tests three procedures which shrink the value of the likelihood ratio or Bayes factor toward the neutral value of one. The procedures are: (1) a Bayesian procedure with uninformative priors, (2) use of empirical lower and upper bounds (ELUB), and (3) a novel form of regularized logistic regression. As a benchmark, they are compared with linear discriminant analysis, and in some instances with non-regularized logistic regression. The behaviours of the procedures are explored using Monte Carlo simulated data, and tested on real data from comparisons of voice recordings, face images, and glass fragments. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Prediction of siRNA potency using sparse logistic regression.

PubMed

Hu, Wei; Hu, John

2014-06-01

RNA interference (RNAi) can modulate gene expression at post-transcriptional as well as transcriptional levels. Short interfering RNA (siRNA) serves as a trigger for the RNAi gene inhibition mechanism, and therefore is a crucial intermediate step in RNAi. There have been extensive studies to identify the sequence characteristics of potent siRNAs. One such study built a linear model using LASSO (Least Absolute Shrinkage and Selection Operator) to measure the contribution of each siRNA sequence feature. This model is simple and interpretable, but it requires a large number of nonzero weights. We have introduced a novel technique, sparse logistic regression, to build a linear model using single-position specific nucleotide compositions which has the same prediction accuracy of the linear model based on LASSO. The weights in our new model share the same general trend as those in the previous model, but have only 25 nonzero weights out of a total 84 weights, a 54% reduction compared to the previous model. Contrary to the linear model based on LASSO, our model suggests that only a few positions are influential on the efficacy of the siRNA, which are the 5' and 3' ends and the seed region of siRNA sequences. We also employed sparse logistic regression to build a linear model using dual-position specific nucleotide compositions, a task LASSO is not able to accomplish well due to its high dimensional nature. Our results demonstrate the superiority of sparse logistic regression as a technique for both feature selection and regression over LASSO in the context of siRNA design.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Extension of the Peters–Belson method to estimate health disparities among multiple groups using logistic regression with survey data

PubMed Central

Li, Y.; Graubard, B. I.; Huang, P.; Gastwirth, J. L.

2015-01-01

Determining the extent of a disparity, if any, between groups of people, for example, race or gender, is of interest in many fields, including public health for medical treatment and prevention of disease. An observed difference in the mean outcome between an advantaged group (AG) and disadvantaged group (DG) can be due to differences in the distribution of relevant covariates. The Peters–Belson (PB) method fits a regression model with covariates to the AG to predict, for each DG member, their outcome measure as if they had been from the AG. The difference between the mean predicted and the mean observed outcomes of DG members is the (unexplained) disparity of interest. We focus on applying the PB method to estimate the disparity based on binary/multinomial/proportional odds logistic regression models using data collected from complex surveys with more than one DG. Estimators of the unexplained disparity, an analytic variance–covariance estimator that is based on the Taylor linearization variance–covariance estimation method, as well as a Wald test for testing a joint null hypothesis of zero for unexplained disparities between two or more minority groups and a majority group, are provided. Simulation studies with data selected from simple random sampling and cluster sampling, as well as the analyses of disparity in body mass index in the National Health and Nutrition Examination Survey 1999–2004, are conducted. Empirical results indicate that the Taylor linearization variance–covariance estimation is accurate and that the proposed Wald test maintains the nominal level. PMID:25382235

Fuzzy Linear Programming and its Application in Home Textile Firm

NASA Astrophysics Data System (ADS)

Vasant, P.; Ganesan, T.; Elamvazuthi, I.

2011-06-01

In this paper, new fuzzy linear programming (FLP) based methodology using a specific membership function, named as modified logistic membership function is proposed. The modified logistic membership function is first formulated and its flexibility in taking up vagueness in parameter is established by an analytical approach. The developed methodology of FLP has provided a confidence in applying to real life industrial production planning problem. This approach of solving industrial production planning problem can have feedback with the decision maker, the implementer and the analyst.

Predicting U.S. Army Reserve Unit Manning Using Market Demographics

DTIC Science & Technology

2015-06-01

develops linear regression , classification tree, and logistic regression models to determine the ability of the location to support manning requirements... logistic regression model delivers predictive results that allow decision-makers to identify locations with a high probability of meeting unit...manning requirements. The recommendation of this thesis is that the USAR implement the logistic regression model. 14. SUBJECT TERMS U.S

Does clinical pretest probability influence image quality and diagnostic accuracy in dual-source coronary CT angiography?

PubMed

Thomas, Christoph; Brodoefel, Harald; Tsiflikas, Ilias; Bruckner, Friederike; Reimann, Anja; Ketelsen, Dominik; Drosch, Tanja; Claussen, Claus D; Kopp, Andreas; Heuschmid, Martin; Burgstahler, Christof

2010-02-01

To prospectively evaluate the influence of the clinical pretest probability assessed by the Morise score onto image quality and diagnostic accuracy in coronary dual-source computed tomography angiography (DSCTA). In 61 patients, DSCTA and invasive coronary angiography were performed. Subjective image quality and accuracy for stenosis detection (>50%) of DSCTA with invasive coronary angiography as gold standard were evaluated. The influence of pretest probability onto image quality and accuracy was assessed by logistic regression and chi-square testing. Correlations of image quality and accuracy with the Morise score were determined using linear regression. Thirty-eight patients were categorized into the high, 21 into the intermediate, and 2 into the low probability group. Accuracies for the detection of significant stenoses were 0.94, 0.97, and 1.00, respectively. Logistic regressions and chi-square tests showed statistically significant correlations between Morise score and image quality (P < .0001 and P < .001) and accuracy (P = .0049 and P = .027). Linear regression revealed a cutoff Morise score for a good image quality of 16 and a cutoff for a barely diagnostic image quality beyond the upper Morise scale. Pretest probability is a weak predictor of image quality and diagnostic accuracy in coronary DSCTA. A sufficient image quality for diagnostic images can be reached with all pretest probabilities. Therefore, coronary DSCTA might be suitable also for patients with a high pretest probability. Copyright 2010 AUR. Published by Elsevier Inc. All rights reserved.

New machine-learning algorithms for prediction of Parkinson's disease

NASA Astrophysics Data System (ADS)

Mandal, Indrajit; Sairam, N.

2014-03-01

This article presents an enhanced prediction accuracy of diagnosis of Parkinson's disease (PD) to prevent the delay and misdiagnosis of patients using the proposed robust inference system. New machine-learning methods are proposed and performance comparisons are based on specificity, sensitivity, accuracy and other measurable parameters. The robust methods of treating Parkinson's disease (PD) includes sparse multinomial logistic regression, rotation forest ensemble with support vector machines and principal components analysis, artificial neural networks, boosting methods. A new ensemble method comprising of the Bayesian network optimised by Tabu search algorithm as classifier and Haar wavelets as projection filter is used for relevant feature selection and ranking. The highest accuracy obtained by linear logistic regression and sparse multinomial logistic regression is 100% and sensitivity, specificity of 0.983 and 0.996, respectively. All the experiments are conducted over 95% and 99% confidence levels and establish the results with corrected t-tests. This work shows a high degree of advancement in software reliability and quality of the computer-aided diagnosis system and experimentally shows best results with supportive statistical inference.

Mapping of the DLQI scores to EQ-5D utility values using ordinal logistic regression.

PubMed

Ali, Faraz Mahmood; Kay, Richard; Finlay, Andrew Y; Piguet, Vincent; Kupfer, Joerg; Dalgard, Florence; Salek, M Sam

2017-11-01

The Dermatology Life Quality Index (DLQI) and the European Quality of Life-5 Dimension (EQ-5D) are separate measures that may be used to gather health-related quality of life (HRQoL) information from patients. The EQ-5D is a generic measure from which health utility estimates can be derived, whereas the DLQI is a specialty-specific measure to assess HRQoL. To reduce the burden of multiple measures being administered and to enable a more disease-specific calculation of health utility estimates, we explored an established mathematical technique known as ordinal logistic regression (OLR) to develop an appropriate model to map DLQI data to EQ-5D-based health utility estimates. Retrospective data from 4010 patients were randomly divided five times into two groups for the derivation and testing of the mapping model. Split-half cross-validation was utilized resulting in a total of ten ordinal logistic regression models for each of the five EQ-5D dimensions against age, sex, and all ten items of the DLQI. Using Monte Carlo simulation, predicted health utility estimates were derived and compared against those observed. This method was repeated for both OLR and a previously tested mapping methodology based on linear regression. The model was shown to be highly predictive and its repeated fitting demonstrated a stable model using OLR as well as linear regression. The mean differences between OLR-predicted health utility estimates and observed health utility estimates ranged from 0.0024 to 0.0239 across the ten modeling exercises, with an average overall difference of 0.0120 (a 1.6% underestimate, not of clinical importance). This modeling framework developed in this study will enable researchers to calculate EQ-5D health utility estimates from a specialty-specific study population, reducing patient and economic burden.

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

On the use and misuse of scalar scores of confounders in design and analysis of observational studies.

PubMed

Pfeiffer, R M; Riedl, R

2015-08-15

We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

Clustering performance comparison using K-means and expectation maximization algorithms.

PubMed

Jung, Yong Gyu; Kang, Min Soo; Heo, Jun

2014-11-14

Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.

The Application of the Cumulative Logistic Regression Model to Automated Essay Scoring

ERIC Educational Resources Information Center

Haberman, Shelby J.; Sinharay, Sandip

2010-01-01

Most automated essay scoring programs use a linear regression model to predict an essay score from several essay features. This article applied a cumulative logit model instead of the linear regression model to automated essay scoring. Comparison of the performances of the linear regression model and the cumulative logit model was performed on a…

Product unit neural network models for predicting the growth limits of Listeria monocytogenes.

PubMed

Valero, A; Hervás, C; García-Gimeno, R M; Zurera, G

2007-08-01

A new approach to predict the growth/no growth interface of Listeria monocytogenes as a function of storage temperature, pH, citric acid (CA) and ascorbic acid (AA) is presented. A linear logistic regression procedure was performed and a non-linear model was obtained by adding new variables by means of a Neural Network model based on Product Units (PUNN). The classification efficiency of the training data set and the generalization data of the new Logistic Regression PUNN model (LRPU) were compared with Linear Logistic Regression (LLR) and Polynomial Logistic Regression (PLR) models. 92% of the total cases from the LRPU model were correctly classified, an improvement on the percentage obtained using the PLR model (90%) and significantly higher than the results obtained with the LLR model, 80%. On the other hand predictions of LRPU were closer to data observed which permits to design proper formulations in minimally processed foods. This novel methodology can be applied to predictive microbiology for describing growth/no growth interface of food-borne microorganisms such as L. monocytogenes. The optimal balance is trying to find models with an acceptable interpretation capacity and with good ability to fit the data on the boundaries of variable range. The results obtained conclude that these kinds of models might well be very a valuable tool for mathematical modeling.

Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

PubMed

Held, Elizabeth; Cape, Joshua; Tintle, Nathan

2016-01-01

Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

Power calculations for likelihood ratio tests for offspring genotype risks, maternal effects, and parent-of-origin (POO) effects in the presence of missing parental genotypes when unaffected siblings are available.

PubMed

Rampersaud, E; Morris, R W; Weinberg, C R; Speer, M C; Martin, E R

2007-01-01

Genotype-based likelihood-ratio tests (LRT) of association that examine maternal and parent-of-origin effects have been previously developed in the framework of log-linear and conditional logistic regression models. In the situation where parental genotypes are missing, the expectation-maximization (EM) algorithm has been incorporated in the log-linear approach to allow incomplete triads to contribute to the LRT. We present an extension to this model which we call the Combined_LRT that incorporates additional information from the genotypes of unaffected siblings to improve assignment of incompletely typed families to mating type categories, thereby improving inference of missing parental data. Using simulations involving a realistic array of family structures, we demonstrate the validity of the Combined_LRT under the null hypothesis of no association and provide power comparisons under varying levels of missing data and using sibling genotype data. We demonstrate the improved power of the Combined_LRT compared with the family-based association test (FBAT), another widely used association test. Lastly, we apply the Combined_LRT to a candidate gene analysis in Autism families, some of which have missing parental genotypes. We conclude that the proposed log-linear model will be an important tool for future candidate gene studies, for many complex diseases where unaffected siblings can often be ascertained and where epigenetic factors such as imprinting may play a role in disease etiology.

Predicting diabetes mellitus using SMOTE and ensemble machine learning approach: The Henry Ford ExercIse Testing (FIT) project.

PubMed

Alghamdi, Manal; Al-Mallah, Mouaz; Keteyian, Steven; Brawner, Clinton; Ehrman, Jonathan; Sakr, Sherif

2017-01-01

Machine learning is becoming a popular and important approach in the field of medical research. In this study, we investigate the relative performance of various machine learning methods such as Decision Tree, Naïve Bayes, Logistic Regression, Logistic Model Tree and Random Forests for predicting incident diabetes using medical records of cardiorespiratory fitness. In addition, we apply different techniques to uncover potential predictors of diabetes. This FIT project study used data of 32,555 patients who are free of any known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems between 1991 and 2009 and had a complete 5-year follow-up. At the completion of the fifth year, 5,099 of those patients have developed diabetes. The dataset contained 62 attributes classified into four categories: demographic characteristics, disease history, medication use history, and stress test vital signs. We developed an Ensembling-based predictive model using 13 attributes that were selected based on their clinical importance, Multiple Linear Regression, and Information Gain Ranking methods. The negative effect of the imbalance class of the constructed model was handled by Synthetic Minority Oversampling Technique (SMOTE). The overall performance of the predictive model classifier was improved by the Ensemble machine learning approach using the Vote method with three Decision Trees (Naïve Bayes Tree, Random Forest, and Logistic Model Tree) and achieved high accuracy of prediction (AUC = 0.92). The study shows the potential of ensembling and SMOTE approaches for predicting incident diabetes using cardiorespiratory fitness data.

Statistical sex determination from craniometrics: Comparison of linear discriminant analysis, logistic regression, and support vector machines.

PubMed

Santos, Frédéric; Guyomarc'h, Pierre; Bruzek, Jaroslav

2014-12-01

Accuracy of identification tools in forensic anthropology primarily rely upon the variations inherent in the data upon which they are built. Sex determination methods based on craniometrics are widely used and known to be specific to several factors (e.g. sample distribution, population, age, secular trends, measurement technique, etc.). The goal of this study is to discuss the potential variations linked to the statistical treatment of the data. Traditional craniometrics of four samples extracted from documented osteological collections (from Portugal, France, the U.S.A., and Thailand) were used to test three different classification methods: linear discriminant analysis (LDA), logistic regression (LR), and support vector machines (SVM). The Portuguese sample was set as a training model on which the other samples were applied in order to assess the validity and reliability of the different models. The tests were performed using different parameters: some included the selection of the best predictors; some included a strict decision threshold (sex assessed only if the related posterior probability was high, including the notion of indeterminate result); and some used an unbalanced sex-ratio. Results indicated that LR tends to perform slightly better than the other techniques and offers a better selection of predictors. Also, the use of a decision threshold (i.e. p>0.95) is essential to ensure an acceptable reliability of sex determination methods based on craniometrics. Although the Portuguese, French, and American samples share a similar sexual dimorphism, application of Western models on the Thai sample (that displayed a lower degree of dimorphism) was unsuccessful. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Role of social support in adolescent suicidal ideation and suicide attempts.

PubMed

Miller, Adam Bryant; Esposito-Smythers, Christianne; Leichtweis, Richard N

2015-03-01

The present study examined the relative contributions of perceptions of social support from parents, close friends, and school on current suicidal ideation (SI) and suicide attempt (SA) history in a clinical sample of adolescents. Participants were 143 adolescents (64% female; 81% white; range, 12-18 years; M = 15.38; standard deviation = 1.43) admitted to a partial hospitalization program. Data were collected with well-validated assessments and a structured clinical interview. Main and interactive effects of perceptions of social support on SI were tested with linear regression. Main and interactive effects of social support on the odds of SA were tested with logistic regression. Results from the linear regression analysis revealed that perceptions of lower school support independently predicted greater severity of SI, accounting for parent and close friend support. Further, the relationship between lower perceived school support and SI was the strongest among those who perceived lower versus higher parental support. Results from the logistic regression analysis revealed that perceptions of lower parental support independently predicted SA history, accounting for school and close friend support. Further, those who perceived lower support from school and close friends reported the greatest odds of an SA history. Results address a significant gap in the social support and suicide literature by demonstrating that perceptions of parent and school support are relatively more important than peer support in understanding suicidal thoughts and history of suicidal behavior. Results suggest that improving social support across these domains may be important in suicide prevention efforts. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Association of comorbid mental health symptoms and physical health conditions with employee productivity.

PubMed

Parker, Kristin M; Wilson, Mark G; Vandenberg, Robert J; DeJoy, David M; Orpinas, Pamela

2009-10-01

This study tests the hypothesis that employees with comorbid physical health conditions and mental health symptoms are less productive than other employees. Self-reported health status and productivity measures were collected from 1723 employees of a national retail organization. chi2, analysis of variance, and linear contrast analyses were conducted to evaluate whether health status groups differed on productivity measures. Multivariate linear regression and multinomial logistic regression analyses were conducted to analyze how predictive health status was of productivity. Those with comorbidities were significantly less productive on all productivity measures compared with all other health status groups and those with only physical health conditions or mental health symptoms. Health status also significantly predicted levels of employee productivity. These findings provide evidence for the relationship between health statuses and productivity, which has potential programmatic implications.

Correlation and simple linear regression.

PubMed

Eberly, Lynn E

2007-01-01

This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression.

Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio.

PubMed

Lloyd-Jones, Luke R; Robinson, Matthew R; Yang, Jian; Visscher, Peter M

2018-04-01

Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure ( e.g. , a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0-1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an effect from an LMM GWAS difficult. In this study, we derived transformations from the genetic effects estimated under the LMM to the OR that only rely on summary statistics. To test the proposed transformations, we used real genotypes from two large, publicly available data sets to simulate all-or-none phenotypes for a set of scenarios that differ in underlying model, disease prevalence, and heritability. Furthermore, we applied these transformations to GWAS summary statistics for type 2 diabetes generated from 108,042 individuals in the UK Biobank. In both simulation and real-data application, we observed very high concordance between the transformed OR from the LMM and either the simulated truth or estimates from logistic regression. The transformations derived and validated in this study improve the comparability of results from prospective and already performed LMM GWAS on complex diseases by providing a reliable transformation to a common comparative scale for the genetic effects. Copyright © 2018 by the Genetics Society of America.

Developing a Capacity Assessment Framework for Marine Logistics Groups

DTIC Science & Technology

2017-02-20

test the framework for assessing logistics capacity on a Marine Expeditionary Unit (MEU) Combat Logistics Battalion (CLB). The study proceeded along...and (5) test the framework for assessing logistics capacity on a Marine Expeditionary Unit (MEU) Combat Logistics Battalion (CLB), time permitting...Marine Logistics Group 21 Impact of New Organization on Logistics Support Under the FSSG structure prior to 2006, the Marine Corps employed a

Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem.

ERIC Educational Resources Information Center

Fan, Xitao; Wang, Lin

The Monte Carlo study compared the performance of predictive discriminant analysis (PDA) and that of logistic regression (LR) for the two-group classification problem. Prior probabilities were used for classification, but the cost of misclassification was assumed to be equal. The study used a fully crossed three-factor experimental design (with…

Molecular markers of neuropsychological functioning and Alzheimer's disease.

PubMed

Edwards, Melissa; Balldin, Valerie Hobson; Hall, James; O'Bryant, Sid

2015-03-01

The current project sought to examine molecular markers of neuropsychological functioning among elders with and without Alzheimer's disease (AD) and determine the predictive ability of combined molecular markers and select neuropsychological tests in detecting disease presence. Data were analyzed from 300 participants (n = 150, AD and n = 150, controls) enrolled in the Texas Alzheimer's Research and Care Consortium. Linear regression models were created to examine the link between the top five molecular markers from our AD blood profile and neuropsychological test scores. Logistical regressions were used to predict AD presence using serum biomarkers in combination with select neuropsychological measures. Using the neuropsychological test with the least amount of variance overlap with the molecular markers, the combined neuropsychological test and molecular markers was highly accurate in detecting AD presence. This work provides the foundation for the generation of a point-of-care device that can be used to screen for AD.

Overview of RICOR's reliability theoretical analysis, accelerated life demonstration test results and verification by field data

NASA Astrophysics Data System (ADS)

Vainshtein, Igor; Baruch, Shlomi; Regev, Itai; Segal, Victor; Filis, Avishai; Riabzev, Sergey

2018-05-01

The growing demand for EO applications that work around the clock 24hr/7days a week, such as in border surveillance systems, emphasizes the need for a highly reliable cryocooler having increased operational availability and optimized system's Integrated Logistic Support (ILS). In order to meet this need, RICOR developed linear and rotary cryocoolers which achieved successfully this goal. Cryocoolers MTTF was analyzed by theoretical reliability evaluation methods, demonstrated by normal and accelerated life tests at Cryocooler level and finally verified by field data analysis derived from Cryocoolers operating at system level. The following paper reviews theoretical reliability analysis methods together with analyzing reliability test results derived from standard and accelerated life demonstration tests performed at Ricor's advanced reliability laboratory. As a summary for the work process, reliability verification data will be presented as a feedback from fielded systems.

Fungible weights in logistic regression.

PubMed

Jones, Jeff A; Waller, Niels G

2016-06-01

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

Comparative analysis on the probability of being a good payer

NASA Astrophysics Data System (ADS)

Mihova, V.; Pavlov, V.

2017-10-01

Credit risk assessment is crucial for the bank industry. The current practice uses various approaches for the calculation of credit risk. The core of these approaches is the use of multiple regression models, applied in order to assess the risk associated with the approval of people applying for certain products (loans, credit cards, etc.). Based on data from the past, these models try to predict what will happen in the future. Different data requires different type of models. This work studies the causal link between the conduct of an applicant upon payment of the loan and the data that he completed at the time of application. A database of 100 borrowers from a commercial bank is used for the purposes of the study. The available data includes information from the time of application and credit history while paying off the loan. Customers are divided into two groups, based on the credit history: Good and Bad payers. Linear and logistic regression are applied in parallel to the data in order to estimate the probability of being good for new borrowers. A variable, which contains value of 1 for Good borrowers and value of 0 for Bad candidates, is modeled as a dependent variable. To decide which of the variables listed in the database should be used in the modelling process (as independent variables), a correlation analysis is made. Due to the results of it, several combinations of independent variables are tested as initial models - both with linear and logistic regression. The best linear and logistic models are obtained after initial transformation of the data and following a set of standard and robust statistical criteria. A comparative analysis between the two final models is made and scorecards are obtained from both models to assess new customers at the time of application. A cut-off level of points, bellow which to reject the applications and above it - to accept them, has been suggested for both the models, applying the strategy to keep the same Accept Rate as in the current data.

Sex differences in the effect of aging on dry eye disease.

PubMed

Ahn, Jong Ho; Choi, Yoon-Hyeong; Paik, Hae Jung; Kim, Mee Kum; Wee, Won Ryang; Kim, Dong Hyun

2017-01-01

Aging is a major risk factor in dry eye disease (DED), and understanding sexual differences is very important in biomedical research. However, there is little information about sex differences in the effect of aging on DED. We investigated sex differences in the effect of aging and other risk factors for DED. This study included data of 16,824 adults from the Korea National Health and Nutrition Examination Survey (2010-2012), which is a population-based cross-sectional survey. DED was defined as the presence of frequent ocular dryness or a previous diagnosis by an ophthalmologist. Basic sociodemographic factors and previously known risk factors for DED were included in the analyses. Linear regression modeling and multivariate logistic regression modeling were used to compare the sex differences in the effect of risk factors for DED; we additionally performed tests for interactions between sex and other risk factors for DED in logistic regression models. In our linear regression models, the prevalence of DED symptoms in men increased with age ( R =0.311, P =0.012); however, there was no association between aging and DED in women ( P >0.05). Multivariate logistic regression analyses showed that aging in men was not associated with DED (DED symptoms/diagnosis: odds ratio [OR] =1.01/1.04, each P >0.05), while aging in women was protectively associated with DED (DED symptoms/diagnosis: OR =0.94/0.91, P =0.011/0.003). Previous ocular surgery was significantly associated with DED in both men and women (men/women: OR =2.45/1.77 [DED symptoms] and 3.17/2.05 [DED diagnosis], each P <0.001). Tests for interactions of sex revealed significantly different aging × sex and previous ocular surgery × sex interactions ( P for interaction of sex: DED symptoms/diagnosis - 0.044/0.011 [age] and 0.012/0.006 [previous ocular surgery]). There were distinct sex differences in the effect of aging on DED in the Korean population. DED following ocular surgery also showed sexually different patterns. Age matching and sex matching are strongly recommended in further studies about DED, especially DED following ocular surgery.

Performance Prediction of a MongoDB-Based Traceability System in Smart Factory Supply Chains

PubMed Central

Kang, Yong-Shin; Park, Il-Ha; Youm, Sekyoung

2016-01-01

In the future, with the advent of the smart factory era, manufacturing and logistics processes will become more complex, and the complexity and criticality of traceability will further increase. This research aims at developing a performance assessment method to verify scalability when implementing traceability systems based on key technologies for smart factories, such as Internet of Things (IoT) and BigData. To this end, based on existing research, we analyzed traceability requirements and an event schema for storing traceability data in MongoDB, a document-based Not Only SQL (NoSQL) database. Next, we analyzed the algorithm of the most representative traceability query and defined a query-level performance model, which is composed of response times for the components of the traceability query algorithm. Next, this performance model was solidified as a linear regression model because the response times increase linearly by a benchmark test. Finally, for a case analysis, we applied the performance model to a virtual automobile parts logistics. As a result of the case study, we verified the scalability of a MongoDB-based traceability system and predicted the point when data node servers should be expanded in this case. The traceability system performance assessment method proposed in this research can be used as a decision-making tool for hardware capacity planning during the initial stage of construction of traceability systems and during their operational phase. PMID:27983654

Performance Prediction of a MongoDB-Based Traceability System in Smart Factory Supply Chains.

PubMed

Kang, Yong-Shin; Park, Il-Ha; Youm, Sekyoung

2016-12-14

In the future, with the advent of the smart factory era, manufacturing and logistics processes will become more complex, and the complexity and criticality of traceability will further increase. This research aims at developing a performance assessment method to verify scalability when implementing traceability systems based on key technologies for smart factories, such as Internet of Things (IoT) and BigData. To this end, based on existing research, we analyzed traceability requirements and an event schema for storing traceability data in MongoDB, a document-based Not Only SQL (NoSQL) database. Next, we analyzed the algorithm of the most representative traceability query and defined a query-level performance model, which is composed of response times for the components of the traceability query algorithm. Next, this performance model was solidified as a linear regression model because the response times increase linearly by a benchmark test. Finally, for a case analysis, we applied the performance model to a virtual automobile parts logistics. As a result of the case study, we verified the scalability of a MongoDB-based traceability system and predicted the point when data node servers should be expanded in this case. The traceability system performance assessment method proposed in this research can be used as a decision-making tool for hardware capacity planning during the initial stage of construction of traceability systems and during their operational phase.

Factors Associated with HIV Testing Among Participants from Substance Use Disorder Treatment Programs in the US: A Machine Learning Approach.

PubMed

Pan, Yue; Liu, Hongmei; Metsch, Lisa R; Feaster, Daniel J

2017-02-01

HIV testing is the foundation for consolidated HIV treatment and prevention. In this study, we aim to discover the most relevant variables for predicting HIV testing uptake among substance users in substance use disorder treatment programs by applying random forest (RF), a robust multivariate statistical learning method. We also provide a descriptive introduction to this method for those who are unfamiliar with it. We used data from the National Institute on Drug Abuse Clinical Trials Network HIV testing and counseling study (CTN-0032). A total of 1281 HIV-negative or status unknown participants from 12 US community-based substance use disorder treatment programs were included and were randomized into three HIV testing and counseling treatment groups. The a priori primary outcome was self-reported receipt of HIV test results. Classification accuracy of RF was compared to logistic regression, a standard statistical approach for binary outcomes. Variable importance measures for the RF model were used to select the most relevant variables. RF based models produced much higher classification accuracy than those based on logistic regression. Treatment group is the most important predictor among all covariates, with a variable importance index of 12.9%. RF variable importance revealed that several types of condomless sex behaviors, condom use self-efficacy and attitudes towards condom use, and level of depression are the most important predictors of receipt of HIV testing results. There is a non-linear negative relationship between count of condomless sex acts and the receipt of HIV testing. In conclusion, RF seems promising in discovering important factors related to HIV testing uptake among large numbers of predictors and should be encouraged in future HIV prevention and treatment research and intervention program evaluations.

Short-term quality of life after subthalamic stimulation depends on non-motor symptoms in Parkinson's disease.

PubMed

Dafsari, Haidar Salimi; Weiß, Luisa; Silverdale, Monty; Rizos, Alexandra; Reddy, Prashanth; Ashkan, Keyoumars; Evans, Julian; Reker, Paul; Petry-Schmelzer, Jan Niklas; Samuel, Michael; Visser-Vandewalle, Veerle; Antonini, Angelo; Martinez-Martin, Pablo; Ray-Chaudhuri, K; Timmermann, Lars

2018-02-24

Subthalamic nucleus (STN) deep brain stimulation (DBS) improves quality of life (QoL), motor, and non-motor symptoms (NMS) in advanced Parkinson's disease (PD). However, considerable inter-individual variability has been observed for QoL outcome. We hypothesized that demographic and preoperative NMS characteristics can predict postoperative QoL outcome. In this ongoing, prospective, multicenter study (Cologne, Manchester, London) including 88 patients, we collected the following scales preoperatively and on follow-up 6 months postoperatively: PDQuestionnaire-8 (PDQ-8), NMSScale (NMSS), NMSQuestionnaire (NMSQ), Scales for Outcomes in PD (SCOPA)-motor examination, -complications, and -activities of daily living, levodopa equivalent daily dose. We dichotomized patients into "QoL responders"/"non-responders" and screened for factors associated with QoL improvement with (1) Spearman-correlations between baseline test scores and QoL improvement, (2) step-wise linear regressions with baseline test scores as independent and QoL improvement as dependent variables, (3) logistic regressions using aforementioned "responders/non-responders" as dependent variable. All outcomes improved significantly on follow-up. However, approximately 44% of patients were categorized as "QoL non-responders". Spearman-correlations, linear and logistic regression analyses were significant for NMSS and NMSQ but not for SCOPA-motor examination. Post-hoc, we identified specific NMS (flat moods, difficulties experiencing pleasure, pain, bladder voiding) as significant contributors to QoL outcome. Our results provide evidence that QoL improvement after STN-DBS depends on preoperative NMS characteristics. These findings are important in the advising and selection of individuals for DBS therapy. Future studies investigating motor and non-motor PD clusters may enable stratifying QoL outcomes and help predict patients' individual prospects of benefiting from DBS. Copyright © 2018. Published by Elsevier Inc.

Protection motivation theory and cigarette smoking among vocational high school students in China: a cusp catastrophe modeling analysis.

PubMed

Xu, Yunan; Chen, Xinguang

2016-01-01

Tobacco use is one of the greatest public health problems worldwide and the hazards of cigarette smoking to public health call for better recognition of cigarette smoking behaviors to guide evidence-based policy. Protection motivation theory (PMT) provides a conceptual framework to investigate tobacco use. Evidence from diverse sources implies that the dynamics of smoking behavior may be quantum in nature, consisting of an intuition and an analytical process, challenging the traditional linear continuous analytical approach. In this study, we used cusp catastrophe, a nonlinear analytical approach to test the dual-process hypothesis of cigarette smoking. Data were collected from a random sample of vocational high school students in China ( n = 528). The multivariate stochastic cusp modeling was used and executed with the Cusp Package in R. The PMT-based Threat Appraisal and Coping Appraisal were used as the two control variables and the frequency of cigarette smoking (daily, weekly, occasional, and never) in the past month was used as the outcome variable. Consistent with PMT, the Threat Appraisal (asymmetry, α 1 = 0.1987, p < 0.001) and Coping Appraisal (bifurcation, β 2 = 0.1760, p < 0.05) significantly predicted the smoking behavior after controlling for covariates. Furthermore, the cusp model performed better than the alternative linear and logistic regression models with regard to higher R 2 (0.82 for cusp, but 0.21 for linear and 0.25 for logistic) and smaller AIC and BIC. Study findings support the conclusion that cigarette smoking in adolescents is a quantum process and PMT is relevant to guide studies to understand smoking behavior for smoking prevention and cessation.

Optimal Facility Location Tool for Logistics Battle Command (LBC)

DTIC Science & Technology

2015-08-01

64 Appendix B. VBA Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Appendix C. Story...should city planners have located emergency service facilities so that all households (the demand) had equal access to coverage?” The critical...programming language called Visual Basic for Applications ( VBA ). CPLEX is a commercial solver for linear, integer, and mixed integer linear programming problems

Kinetic compensation effect in logistic distributed activation energy model for lignocellulosic biomass pyrolysis.

PubMed

Xu, Di; Chai, Meiyun; Dong, Zhujun; Rahman, Md Maksudur; Yu, Xi; Cai, Junmeng

2018-06-04

The kinetic compensation effect in the logistic distributed activation energy model (DAEM) for lignocellulosic biomass pyrolysis was investigated. The sum of square error (SSE) surface tool was used to analyze two theoretically simulated logistic DAEM processes for cellulose and xylan pyrolysis. The logistic DAEM coupled with the pattern search method for parameter estimation was used to analyze the experimental data of cellulose pyrolysis. The results showed that many parameter sets of the logistic DAEM could fit the data at different heating rates very well for both simulated and experimental processes, and a perfect linear relationship between the logarithm of the frequency factor and the mean value of the activation energy distribution was found. The parameters of the logistic DAEM can be estimated by coupling the optimization method and isoconversional kinetic methods. The results would be helpful for chemical kinetic analysis using DAEM. Copyright © 2018 Elsevier Ltd. All rights reserved.

Integrated Logistics Support Analysis of the International Space Station Alpha, Background and Summary of Mathematical Modeling and Failure Density Distributions Pertaining to Maintenance Time Dependent Parameters

NASA Technical Reports Server (NTRS)

Sepehry-Fard, F.; Coulthard, Maurice H.

1995-01-01

The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.

Exposure and impact of a mass media campaign targeting sexual health amongst Scottish men who have sex with men: an outcome evaluation

PubMed Central

2013-01-01

Background This paper explores the exposure and impact of a Scottish mass media campaign: Make Your Position Clear. It ran from October 2009 to July 2010, targeted gay men and other men who have sex with men (MSM), and had two key aims: to promote regular sexual health and HIV testing every 6 months, and to promote the use of appropriate condoms and water-based lubricant with each episode of anal intercourse. Methods A cross-sectional survey (anonymous and self-report) was conducted 10 months after the campaign was launched (July 2010). Men were recruited from commercial venues. Outcome measures included use of lubricant, testing for sexually transmitted infections and HIV, and intentions to seek HIV testing within the following six months. Linear-by-linear chi-square analysis and binary logistic regressions were conducted to explore the associations between the outcome measures and campaign exposure. Results The total sample was 822 men (62.6% response rate). Men self-identifying as HIV positive were excluded from the analysis (n = 38). Binary logistic analysis indicated that those with mid or high campaign exposure were more likely to have been tested for HIV in the previous six months when adjusted for age, area of residence and use of the “gay scene” (AOR = 1.96, 95% CI = 1.26 to 3.06, p = .003), but were not more likely to be tested for STIs (AOR = 1.37, 95% CI = 0.88 to 2.16, p = .167). When adjusted for previous HIV testing, those with mid or high campaign exposure were not more likely to indicate intention to be tested for HIV in the following six months (AOR = 1.30, 95% CI = 0.73 to 2.32, p = .367). Those with no campaign exposure were less likely than those with low exposure to have used appropriate lubricant with anal sex partners in the previous year (AOR = 0.42, 95% CI = 0.23 to 0.77, p = .005). Conclusions The campaign had demonstrable reach. The analysis showed partial support for the role of mass media campaigns in improving sexual health outcomes. This suggests that a role for mass media campaigns remains within combination HIV prevention. PMID:23923977

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Epidemiological characteristics and deaths of premature infants in a referral hospital for high-risk pregnancies

PubMed Central

de Freitas, Brunnella Alcantara Chagas; Sant'Ana, Luciana Ferreira da Rocha; Longo, Giana Zarbato; Siqueira-Batista, Rodrigo; Priore, Silvia Eloiza; Franceschin, Sylvia do Carmo Castro

2012-01-01

Objective To analyze the process of care provided to premature infants in a neonatal intensive care unit and the factors associated with their mortality. Methods Cross-sectional retrospective study of premature infants in an intensive care unit between 2008 and 2010. The characteristics of the mothers and premature infants were described, and a bivariate analysis was performed on the following characteristics: the study period and the "death" outcome (hospital, neonatal and early) using Pearson's chi-square test, Fisher's exact test or a chi-square test for linear trends. Bivariate and multivariable logistic regression analyses were performed using a stepwise backward logistic regression method between the variables with p<0.20 and the "death" outcome. A p value <0.05 was considered to be significant. Results In total, 293 preterm infants were studied. Increased access to complementary tests (transfontanellar ultrasound and Doppler echocardiogram) and breastfeeding rates were indicators of improving care. Mortality was concentrated in the neonatal period, especially in the early neonatal period, and was associated with extreme prematurity, small size for gestational age and an Apgar score <7 at 5 minutes after birth. The late-onset sepsis was also associated with a greater chance of neonatal death, and antenatal corticosteroids were protective against neonatal and early deaths. Conclusions Although these results are comparable to previous findings regarding mortality among premature infants in Brazil, the study emphasizes the need to implement strategies that promote breastfeeding and reduce neonatal mortality and its early component. PMID:23917938

The Mantel-Haenszel procedure revisited: models and generalizations.

PubMed

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented.

The Mantel-Haenszel Procedure Revisited: Models and Generalizations

PubMed Central

Fidler, Vaclav; Nagelkerke, Nico

2013-01-01

Several statistical methods have been developed for adjusting the Odds Ratio of the relation between two dichotomous variables X and Y for some confounders Z. With the exception of the Mantel-Haenszel method, commonly used methods, notably binary logistic regression, are not symmetrical in X and Y. The classical Mantel-Haenszel method however only works for confounders with a limited number of discrete strata, which limits its utility, and appears to have no basis in statistical models. Here we revisit the Mantel-Haenszel method and propose an extension to continuous and vector valued Z. The idea is to replace the observed cell entries in strata of the Mantel-Haenszel procedure by subject specific classification probabilities for the four possible values of (X,Y) predicted by a suitable statistical model. For situations where X and Y can be treated symmetrically we propose and explore the multinomial logistic model. Under the homogeneity hypothesis, which states that the odds ratio does not depend on Z, the logarithm of the odds ratio estimator can be expressed as a simple linear combination of three parameters of this model. Methods for testing the homogeneity hypothesis are proposed. The relationship between this method and binary logistic regression is explored. A numerical example using survey data is presented. PMID:23516463

Surgery for left ventricular aneurysm: early and late survival after simple linear repair and endoventricular patch plasty.

PubMed

Lundblad, Runar; Abdelnoor, Michel; Svennevig, Jan Ludvig

2004-09-01

Simple linear resection and endoventricular patch plasty are alternative techniques to repair postinfarction left ventricular aneurysm. The aim of the study was to compare these 2 methods with regard to early mortality and long-term survival. We retrospectively reviewed 159 patients undergoing operations between 1989 and 2003. The epidemiologic design was of an exposed (simple linear repair, n = 74) versus nonexposed (endoventricular patch plasty, n = 85) cohort with 2 endpoints: early mortality and long-term survival. The crude effect of aneurysm repair technique versus endpoint was estimated by odds ratio, rate ratio, or relative risk and their 95% confidence intervals. Stratification analysis by using the Mantel-Haenszel method was done to quantify confounders and pinpoint effect modifiers. Adjustment for multiconfounders was performed by using logistic regression and Cox regression analysis. Survival curves were analyzed with the Breslow test and the log-rank test. Early mortality was 8.2% for all patients, 13.5% after linear repair and 3.5% after endoventricular patch plasty. When adjusted for multiconfounders, the risk of early mortality was significantly higher after simple linear repair than after endoventricular patch plasty (odds ratio, 4.4; 95% confidence interval, 1.1-17.8). Mean follow-up was 5.8 +/- 3.8 years (range, 0-14.0 years). Overall 5-year cumulative survival was 78%, 70.1% after linear repair and 91.4% after endoventricular patch plasty. The risk of total mortality was significantly higher after linear repair than after endoventricular patch plasty when controlled for multiconfounders (relative risk, 4.5; 95% confidence interval, 2.0-9.7). Linear repair dominated early in the series and patch plasty dominated later, giving a possible learning-curve bias in favor of patch plasty that could not be adjusted for in the regression analysis. Postinfarction left ventricular aneurysm can be repaired with satisfactory early and late results. Surgical risk was lower and long-term survival was higher after endoventricular patch plasty than simple linear repair. Differences in outcome should be interpreted with care because of the retrospective study design and the chronology of the 2 repair methods.

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.

PubMed

Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao

2016-11-30

Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.

Understanding logistic regression analysis.

PubMed

Sperandei, Sandro

2014-01-01

Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

Familial associations with paratuberculosis ELISA results in Texas Longhorn cattle.

PubMed

Osterstock, Jason B; Fosgate, Geoffrey T; Cohen, Noah D; Derr, James N; Manning, Elizabeth J B; Collins, Michael T; Roussel, Allen J

2008-05-25

The objective of this cross-sectional study was to estimate familial associations with paratuberculosis ELISA status in beef cattle. Texas Longhorn cattle (n=715) greater than 2years of age were sampled for paratuberculosis testing using ELISA and fecal culture. Diagnostic test results were indicative of substantial numbers of false-positive serological reactions consistent with environmental exposure to non-MAP Mycobacterium spp. Associations between ancestors and paratuberculosis ELISA status of offspring were assessed using conditional logistic regression. The association between ELISA status of the dam and her offspring was assessed using linear mixed-effect models. Significant associations were identified between some ancestors and offspring ELISA status. The odds of being classified as "suspect" or greater based on ELISA results were 4.6 times greater for offspring of dams with similarly increased S:P ratios. A significant positive linear association was also observed between dam and offspring log-transformed S:P ratios. Results indicate that there is familial aggregation of paratuberculosis ELISA results in beef cattle and suggest that genetic selection based on paratuberculosis ELISA status may decrease seroprevalence. However, genetic selection may have minimal effect on paratuberculosis control in herds with exposure to non-MAP Mycobacterium spp.

Power and Sample Size Calculations for Logistic Regression Tests for Differential Item Functioning

ERIC Educational Resources Information Center

Li, Zhushan

2014-01-01

Logistic regression is a popular method for detecting uniform and nonuniform differential item functioning (DIF) effects. Theoretical formulas for the power and sample size calculations are derived for likelihood ratio tests and Wald tests based on the asymptotic distribution of the maximum likelihood estimators for the logistic regression model.…

Parameter Recovery for the 1-P HGLLM with Non-Normally Distributed Level-3 Residuals

ERIC Educational Resources Information Center

Kara, Yusuf; Kamata, Akihito

2017-01-01

A multilevel Rasch model using a hierarchical generalized linear model is one approach to multilevel item response theory (IRT) modeling and is referred to as a one-parameter hierarchical generalized linear logistic model (1-P HGLLM). Although it has the flexibility to model nested structure of data with covariates, the model assumes the normality…

On spurious detection of linear response and misuse of the fluctuation-dissipation theorem in finite time series

NASA Astrophysics Data System (ADS)

Gottwald, Georg A.; Wormell, J. P.; Wouters, Jeroen

2016-09-01

Using a sensitive statistical test we determine whether or not one can detect the breakdown of linear response given observations of deterministic dynamical systems. A goodness-of-fit statistics is developed for a linear statistical model of the observations, based on results for central limit theorems for deterministic dynamical systems, and used to detect linear response breakdown. We apply the method to discrete maps which do not obey linear response and show that the successful detection of breakdown depends on the length of the time series, the magnitude of the perturbation and on the choice of the observable. We find that in order to reliably reject the assumption of linear response for typical observables sufficiently large data sets are needed. Even for simple systems such as the logistic map, one needs of the order of 106 observations to reliably detect the breakdown with a confidence level of 95 %; if less observations are available one may be falsely led to conclude that linear response theory is valid. The amount of data required is larger the smaller the applied perturbation. For judiciously chosen observables the necessary amount of data can be drastically reduced, but requires detailed a priori knowledge about the invariant measure which is typically not available for complex dynamical systems. Furthermore we explore the use of the fluctuation-dissipation theorem (FDT) in cases with limited data length or coarse-graining of observations. The FDT, if applied naively to a system without linear response, is shown to be very sensitive to the details of the sampling method, resulting in erroneous predictions of the response.

Robust mislabel logistic regression without modeling mislabel probabilities.

PubMed

Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

2018-03-01

Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

Evaluating construct validity of the second version of the Copenhagen Psychosocial Questionnaire through analysis of differential item functioning and differential item effect.

PubMed

Bjorner, Jakob Bue; Pejtersen, Jan Hyld

2010-02-01

To evaluate the construct validity of the Copenhagen Psychosocial Questionnaire II (COPSOQ II) by means of tests for differential item functioning (DIF) and differential item effect (DIE). We used a Danish general population postal survey (n = 4,732 with 3,517 wage earners) with a one-year register based follow up for long-term sickness absence. DIF was evaluated against age, gender, education, social class, public/private sector employment, and job type using ordinal logistic regression. DIE was evaluated against job satisfaction and self-rated health (using ordinal logistic regression), against depressive symptoms, burnout, and stress (using multiple linear regression), and against long-term sick leave (using a proportional hazards model). We used a cross-validation approach to counter the risk of significant results due to multiple testing. Out of 1,052 tests, we found 599 significant instances of DIF/DIE, 69 of which showed both practical and statistical significance across two independent samples. Most DIF occurred for job type (in 20 cases), while we found little DIF for age, gender, education, social class and sector. DIE seemed to pertain to particular items, which showed DIE in the same direction for several outcome variables. The results allowed a preliminary identification of items that have a positive impact on construct validity and items that have negative impact on construct validity. These results can be used to develop better shortform measures and to improve the conceptual framework, items and scales of the COPSOQ II. We conclude that tests of DIF and DIE are useful for evaluating construct validity.

The weighted priors approach for combining expert opinions in logistic regression experiments

DOE PAGES

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

2017-04-24

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

Nurses' decision making in heart failure management based on heart failure certification status.

PubMed

Albert, Nancy M; Bena, James F; Buxbaum, Denise; Martensen, Linda; Morrison, Shannon L; Prasun, Marilyn A; Stamp, Kelly D

Research findings on the value of nurse certification were based on subjective perceptions or biased by correlations of certification status and global clinical factors. In heart failure, the value of certification is unknown. Examine the value of certification based nurses' decision-making. Cross-sectional study of nurses who completed heart failure clinical vignettes that reflected decision-making in clinical heart failure scenarios. Statistical tests included multivariable linear, logistic and proportional odds logistic regression models. Of nurses (N = 605), 29.1% were heart failure certified, 35.0% were certified in another specialty/job role and 35.9% were not certified. In multivariable modeling, nurses certified in heart failure (versus not heart failure certified) had higher clinical vignette scores (p = 0.002), reflecting higher evidence-based decision making; nurses with another specialty/role certification (versus no certification) did not (p = 0.62). Heart failure certification, but not in other specialty/job roles was associated with decisions that reflected delivery of high-quality care. Copyright © 2018 Elsevier Inc. All rights reserved.

The weighted priors approach for combining expert opinions in logistic regression experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

Rainfall induced landslide susceptibility mapping using weight-of-evidence, linear and quadratic discriminant and logistic model tree method

NASA Astrophysics Data System (ADS)

Hong, H.; Zhu, A. X.

2017-12-01

Climate change is a common phenomenon and it is very serious all over the world. The intensification of rainfall extremes with climate change is of key importance to society and then it may induce a large impact through landslides. This paper presents GIS-based new ensemble data mining techniques that weight-of-evidence, logistic model tree, linear and quadratic discriminant for landslide spatial modelling. This research was applied in Anfu County, which is a landslide-prone area in Jiangxi Province, China. According to a literature review and research the study area, we select the landslide influencing factor and their maps were digitized in a GIS environment. These landslide influencing factors are the altitude, plan curvature, profile curvature, slope degree, slope aspect, topographic wetness index (TWI), Stream Power Index (SPI), Topographic Wetness Index (SPI), distance to faults, distance to rivers, distance to roads, soil, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the government of Jiangxi Meteorological Bureau of China, 367 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, Pearson's correlation was used for the evaluation of the relationship between the landslides and influencing factors. In the next step, three data mining techniques combined with the weight-of-evidence, logistic model tree, linear and quadratic discriminant, were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.80. At the same time, the highest AUC value was for the linear and quadratic discriminant model (0.864), followed by logistic model tree (0.832), and weight-of-evidence (0.819). In general, the landslide maps can be applied for land use planning and management in the Anfu area.

An Evaluation of Different Statistical Targets for Assembling Parallel Forms in Item Response Theory

PubMed Central

Ali, Usama S.; van Rijn, Peter W.

2015-01-01

Assembly of parallel forms is an important step in the test development process. Therefore, choosing a suitable theoretical framework to generate well-defined test specifications is critical. The performance of different statistical targets of test specifications using the test characteristic curve (TCC) and the test information function (TIF) was investigated. Test length, the number of test forms, and content specifications are considered as well. The TCC target results in forms that are parallel in difficulty, but not necessarily in terms of precision. Vice versa, test forms created using a TIF target are parallel in terms of precision, but not necessarily in terms of difficulty. As sometimes the focus is either on TIF or TCC, differences in either difficulty or precision can arise. Differences in difficulty can be mitigated by equating, but differences in precision cannot. In a series of simulations using a real item bank, the two-parameter logistic model, and mixed integer linear programming for automated test assembly, these differences were found to be quite substantial. When both TIF and TCC are combined into one target with manipulation to relative importance, these differences can be made to disappear.

ADCYAP1R1 and asthma in Puerto Rican children.

PubMed

Chen, Wei; Boutaoui, Nadia; Brehm, John M; Han, Yueh-Ying; Schmitz, Cassandra; Cressley, Alex; Acosta-Pérez, Edna; Alvarez, María; Colón-Semidey, Angel; Baccarelli, Andrea A; Weeks, Daniel E; Kolls, Jay K; Canino, Glorisa; Celedón, Juan C

2013-03-15

Epigenetic and/or genetic variation in the gene encoding the receptor for adenylate-cyclase activating polypeptide 1 (ADCYAP1R1) has been linked to post-traumatic stress disorder in adults and anxiety in children. Psychosocial stress has been linked to asthma morbidity in Puerto Rican children. To examine whether epigenetic or genetic variation in ADCYAP1R1 is associated with childhood asthma in Puerto Ricans. We conducted a case-control study of 516 children ages 6-14 years living in San Juan, Puerto Rico. We assessed methylation at a CpG site in the promoter of ADCYAP1R1 (cg11218385) using a pyrosequencing assay in DNA from white blood cells. We tested whether cg11218385 methylation (range, 0.4-6.1%) is associated with asthma using logistic regression. We also examined whether exposure to violence (assessed by the Exposure to Violence [ETV] Scale in children 9 yr and older) is associated with cg11218385 methylation (using linear regression) or asthma (using logistic regression). Logistic regression was used to test for association between a single nucleotide polymorphism in ADCYAP1R1 (rs2267735) and asthma under an additive model. All multivariate models were adjusted for age, sex, household income, and principal components. EACH 1% increment in cg11218385 methylation was associated with increased odds of asthma (adjusted odds ratio, 1.3; 95% confidence interval, 1.0-1.6; P = 0.03). Among children 9 years and older, exposure to violence was associated with cg11218385 methylation. The C allele of single nucleotide polymorphism rs2267735 was significantly associated with increased odds of asthma (adjusted odds ratio, 1.3; 95% confidence interval, 1.02-1.67; P = 0.03). Epigenetic and genetic variants in ADCYAP1R1 are associated with asthma in Puerto Rican children.

Logistic regression for circular data

NASA Astrophysics Data System (ADS)

Al-Daffaie, Kadhem; Khan, Shahjahan

2017-05-01

This paper considers the relationship between a binary response and a circular predictor. It develops the logistic regression model by employing the linear-circular regression approach. The maximum likelihood method is used to estimate the parameters. The Newton-Raphson numerical method is used to find the estimated values of the parameters. A data set from weather records of Toowoomba city is analysed by the proposed methods. Moreover, a simulation study is considered. The R software is used for all computations and simulations.

Research on the influencing factors of reverse logistics carbon footprint under sustainable development.

PubMed

Sun, Qiang

2017-10-01

With the concerns of ecological and circular economy along with sustainable development, reverse logistics has attracted the attention of enterprise. How to achieve sustainable development of reverse logistics has important practical significance of enhancing low carbon competitiveness. In this paper, the system boundary of reverse logistics carbon footprint is presented. Following the measurement of reverse logistics carbon footprint and reverse logistics carbon capacity is provided. The influencing factors of reverse logistics carbon footprint are classified into five parts such as intensity of reverse logistics, energy structure, energy efficiency, reverse logistics output, and product remanufacturing rate. The quantitative research methodology using ADF test, Johansen co-integration test, and impulse response is utilized to interpret the relationship between reverse logistics carbon footprint and the influencing factors more accurately. This research finds that energy efficiency, energy structure, and product remanufacturing rate are more capable of inhibiting reverse logistics carbon footprint. The statistical approaches will help practitioners in this field to structure their reverse logistics activities and also help academics in developing better decision models to reduce reverse logistics carbon footprint.

Predicting Madura cattle growth curve using non-linear model

NASA Astrophysics Data System (ADS)

Widyas, N.; Prastowo, S.; Widi, T. S. M.; Baliarti, E.

2018-03-01

Madura cattle is Indonesian native. It is a composite breed that has undergone hundreds of years of selection and domestication to reach nowadays remarkable uniformity. Crossbreeding has reached the isle of Madura and the Madrasin, a cross between Madura cows and Limousine semen emerged. This paper aimed to compare the growth curve between Madrasin and one type of pure Madura cows, the common Madura cattle (Madura) using non-linear models. Madura cattles are kept traditionally thus reliable records are hardly available. Data were collected from small holder farmers in Madura. Cows from different age classes (<6 months, 6-12 months, 1-2years, 2-3years, 3-5years and >5years) were observed, and body measurements (chest girth, body length and wither height) were taken. In total 63 Madura and 120 Madrasin records obtained. Linear model was built with cattle sub-populations and age as explanatory variables. Body weights were estimated based on the chest girth. Growth curves were built using logistic regression. Results showed that within the same age, Madrasin has significantly larger body compared to Madura (p<0.05). The logistic models fit better for Madura and Madrasin cattle data; with the estimated MSE for these models were 39.09 and 759.28 with prediction accuracy of 99 and 92% for Madura and Madrasin, respectively. Prediction of growth curve using logistic regression model performed well in both types of Madura cattle. However, attempts to administer accurate data on Madura cattle are necessary to better characterize and study these cattle.

Association of Brain-Derived Neurotrophic Factor and Vitamin D with Depression and Obesity: A Population-Based Study.

PubMed

Goltz, Annemarie; Janowitz, Deborah; Hannemann, Anke; Nauck, Matthias; Hoffmann, Johanna; Seyfart, Tom; Völzke, Henry; Terock, Jan; Grabe, Hans Jörgen

2018-06-19

Depression and obesity are widespread and closely linked. Brain-derived neurotrophic factor (BDNF) and vitamin D are both assumed to be associated with depression and obesity. Little is known about the interplay between vitamin D and BDNF. We explored the putative associations and interactions between serum BDNF and vitamin D levels with depressive symptoms and abdominal obesity in a large population-based cohort. Data were obtained from the population-based Study of Health in Pomerania (SHIP)-Trend (n = 3,926). The associations of serum BDNF and vitamin D levels with depressive symptoms (measured using the Patient Health Questionnaire) were assessed with binary and multinomial logistic regression models. The associations of serum BDNF and vitamin D levels with obesity (measured by the waist-to-hip ratio [WHR]) were assessed with binary logistic and linear regression models with restricted cubic splines. Logistic regression models revealed inverse associations of vitamin D with depression (OR = 0.966; 95% CI 0.951-0.981) and obesity (OR = 0.976; 95% CI 0.967-0.985). No linear association of serum BDNF with depression or obesity was found. However, linear regression models revealed a U-shaped association of BDNF with WHR (p < 0.001). Vitamin D was inversely associated with depression and obesity. BDNF was associated with abdominal obesity, but not with depression. At the population level, our results support the relevant roles of vitamin D and BDNF in mental and physical health-related outcomes. © 2018 S. Karger AG, Basel.

Prevalence and Correlates of Tobacco and Nicotine Containing Product Use in a Sample of United States Air Force Trainees

PubMed Central

Derefinko, Karen J.; Bursac, Zoran; Ebbert, Jon O.; Colvin, Lauren; Talcott, Gerald W.; Hryshko-Mullen, Ann S.; Richey, Phyllis A.; Klesges, Robert C.

2016-01-01

Introduction: Although there is increasing attention to the prevalence of new and emerging tobacco products in the civilian population, remarkably little is known about the current prevalence of these products in a military population. Methods: The current investigation was designed to determine the prevalence of tobacco and nicotine containing products (TNCP) and correlates of use across multiple cohorts of trainees undergoing Technical Training in the US Air Force between April 2013 and December 2014. Chi-square test, Cochran–Armitage test for linear trend, and logistic regression models were applied to test differences and linear trends across time for TNCP use as well as correlates of use in a cross-sectional sample of 13 685 Airmen (final analytic sample). Results: Over a quarter (26.9%) of Airmen reported regular use of a TNCP. The two most prevalent products were cigarettes (11.2%) and hookah (10.5%). Among correlates of use, Airmen that regularly use TNCPs were more likely to be male, younger, non-Hispanic white, and single with a high school degree or General Education Development. Hookah was the most endorsed for intentions to use, and along with e-cigarettes, had the lowest perception of harm. While prevalence of most products remained constant across entering cohorts, the prevalence of e-cigarettes showed significant linear increase. Conclusions: The prevalence of TNCP use is high across cohorts of Airmen. Remarkably high estimates of future intentions to use and low perceptions of harm for emerging products suggest that intervention efforts should be directed at multiple forms of TNCP use to address this important public health issue. PMID:25895952

Private traits and attributes are predictable from digital records of human behavior.

PubMed

Kosinski, Michal; Stillwell, David; Graepel, Thore

2013-04-09

We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait "Openness," prediction accuracy is close to the test-retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy.

A Comparison of Four Linear Equating Methods for the Common-Item Nonequivalent Groups Design Using Simulation Methods. ACT Research Report Series, 2013 (2)

ERIC Educational Resources Information Center

Topczewski, Anna; Cui, Zhongmin; Woodruff, David; Chen, Hanwei; Fang, Yu

2013-01-01

This paper investigates four methods of linear equating under the common item nonequivalent groups design. Three of the methods are well known: Tucker, Angoff-Levine, and Congeneric-Levine. A fourth method is presented as a variant of the Congeneric-Levine method. Using simulation data generated from the three-parameter logistic IRT model we…

Logistics Solution for Choosing Location of Production of Road Construction Enterprise

NASA Astrophysics Data System (ADS)

Gavrilina, I.; Bondar, A.

2017-11-01

The current state of construction of highways indicates that not all the resources of the construction organization are implemented and supported by the modern approaches in logistics problems solving. This article deals with the solution of these problems and considers the features of basic road linear works organization, their large extent and different locations of enterprises. Analyzing these data, it is proposed to simulate the logistics processes and substantiate the methods of transport operations organizing by linking the technology and the organization road construction materials delivery which allows one to optimize the construction processes, to choose the most economically advantageous options, and also to monitor the quality of work.

Locomotive syndrome is associated not only with physical capacity but also degree of depression.

PubMed

Ikemoto, Tatsunori; Inoue, Masayuki; Nakata, Masatoshi; Miyagawa, Hirofumi; Shimo, Kazuhiro; Wakabayashi, Toshiko; Arai, Young-Chang P; Ushida, Takahiro

2016-05-01

Reports of locomotive syndrome (LS) have recently been increasing. Although physical performance measures for LS have been well investigated to date, studies including psychiatric assessment are still scarce. Hence, the aim of this study was to investigate both physical and mental parameters in relation to presence and severity of LS using a 25-question geriatric locomotive function scale (GLFS-25) questionnaire. 150 elderly people aged over 60 years who were members of our physical-fitness center and displayed well-being were enrolled in this study. Firstly, using the previously determined GLFS-25 cutoff value (=16 points), subjects were divided into two groups accordingly: an LS and non-LS group in order to compare each parameter (age, grip strength, timed-up-and-go test (TUG), one-leg standing with eye open, back muscle and leg muscle strength, degree of depression and cognitive impairment) between the groups using the Mann-Whitney U-test followed by multiple logistic regression analysis. Secondly, a multiple linear regression was conducted to determine which variables showed the strongest correlation with severity of LS. We confirmed 110 people for non-LS (73%) and 40 people for LS using the GLFS-25 cutoff value. Comparative analysis between LS and non-LS revealed significant differences in parameters in age, grip strength, TUG, one-leg standing, back muscle strength and degree of depression (p < 0.006, after Bonferroni correction). Multiple logistic regression revealed that functional decline in grip strength, TUG and one-leg standing and degree of depression were significantly associated with LS. On the other hand, we observed that the significant contributors towards the GLFS-25 score were TUG and degree of depression in multiple linear regression analysis. The results indicate that LS is associated with not only the capacity of physical performance but also the degree of depression although most participants fell under the criteria of LS. Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway Is Associated With Major Depressive Disorder.

PubMed

Zeng, Yanni; Navarro, Pau; Fernandez-Pujals, Ana M; Hall, Lynsey S; Clarke, Toni-Kim; Thomson, Pippa A; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Wray, Naomi R; Deary, Ian J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M

2017-02-15

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk. We integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested. In GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model. These post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Predictors of college-student food security and fruit and vegetable intake differ by housing type.

PubMed

Mirabitur, Erica; Peterson, Karen E; Rathz, Colleen; Matlen, Stacey; Kasper, Nicole

2016-10-01

We assessed whether college-student characteristics associate with food security and fruit and vegetable (FV) intake and whether these associations differ in students in housing with and without food provision. 514 randomly-sampled students from a large, Midwestern, public university in 2012 and 2013 METHODS: Ordered logistic regression tested how student characteristics associate with food security. Linear regression tested how student characteristics associate with FV intake. Analyses were stratified by housing type - that is, housing with food provision (dormitory, fraternity/sorority house, cooperative) vs. housing without food provision. Only among those living in housing without food provision, males (p = 0.04), students without car access (p = 0.005), and those with marginal (p = 0.001) or low (p = 0.001) food security demonstrated lower FV intake. Housing with food provision may buffer the effects of student characteristics on food.

Using the ADAP Learning Algorithm to Forecast the Onset of Diabetes Mellitus

PubMed Central

Smith, Jack W.; Everhart, J.E.; Dickson, W.C.; Knowler, W.C.; Johannes, R.S.

1988-01-01

Neural networks or connectionist models for parallel processing are not new. However, a resurgence of interest in the past half decade has occurred. In part, this is related to a better understanding of what are now referred to as hidden nodes. These algorithms are considered to be of marked value in pattern recognition problems. Because of that, we tested the ability of an early neural network model, ADAP, to forecast the onset of diabetes mellitus in a high risk population of Pima Indians. The algorithm's performance was analyzed using standard measures for clinical tests: sensitivity, specificity, and a receiver operating characteristic curve. The crossover point for sensitivity and specificity is 0.76. We are currently further examining these methods by comparing the ADAP results with those obtained from logistic regression and linear perceptron models using precisely the same training and forecasting sets. A description of the algorithm is included.

Physical Function in Older Men With Hyperkyphosis

PubMed Central

Harrison, Stephanie L.; Fink, Howard A.; Marshall, Lynn M.; Orwoll, Eric; Barrett-Connor, Elizabeth; Cawthon, Peggy M.; Kado, Deborah M.

2015-01-01

Background. Age-related hyperkyphosis has been associated with poor physical function and is a well-established predictor of adverse health outcomes in older women, but its impact on health in older men is less well understood. Methods. We conducted a cross-sectional study to evaluate the association of hyperkyphosis and physical function in 2,363 men, aged 71–98 (M = 79) from the Osteoporotic Fractures in Men Study. Kyphosis was measured using the Rancho Bernardo Study block method. Measurements of grip strength and lower extremity function, including gait speed over 6 m, narrow walk (measure of dynamic balance), repeated chair stands ability and time, and lower extremity power (Nottingham Power Rig) were included separately as primary outcomes. We investigated associations of kyphosis and each outcome in age-adjusted and multivariable linear or logistic regression models, controlling for age, clinic, education, race, bone mineral density, height, weight, diabetes, and physical activity. Results. In multivariate linear regression, we observed a dose-related response of worse scores on each lower extremity physical function test as number of blocks increased, p for trend ≤.001. Using a cutoff of ≥4 blocks, 20% (N = 469) of men were characterized with hyperkyphosis. In multivariate logistic regression, men with hyperkyphosis had increased odds (range 1.5–1.8) of being in the worst quartile of performing lower extremity physical function tasks (p < .001 for each outcome). Kyphosis was not associated with grip strength in any multivariate analysis. Conclusions. Hyperkyphosis is associated with impaired lower extremity physical function in older men. Further studies are needed to determine the direction of causality. PMID:25431353

Holistic morphometric analysis of growth of the sand dollar Echinarachnius parma (Echinodermata:Echinoidea:Clypeasteroida).

PubMed

Zachos, Louis G

2015-12-02

Holistic morphometrics is a term implying complete shape characterization of all of the structural parts of an organism. The skeleton of an echinoid is comprised of hundreds of individual plates arranged in a closed 3-dimensional mosaic forming the test. GIS software and techniques were used to generate topologically correct digital models of an ontogenetic series of specimens of the sand dollar echinoid Echinarachnius parma. Plate growth can be considered in proportion to overall skeleton growth, resulting in a linear model of relative growth. Alternatively, separate logistic equations can be fit to the ontogenetic series of homologous plate areas using nonlinear least squares regression to result in a model for instantaneous growth. The linear and logistic parameters of the models describe the allometric growth of plates from different viewpoints. Growth is shown to fall into characteristic patterns defining distinct plate growth domains associated with development of the imago (larval) skeleton just prior to metamorphosis, early growth associated with expansion of the corona and fold-over (forming the flattened body form), juvenile growth and formation of petals, and adult growth. Functions of growth, plate translocation, plate juxtaposition between aboral and oral surfaces, and relationships with internal buttressing are quantified. Results offer explanations for general skeletal symmetry, distinction between ambulacral and interambulacral growth, the relationship of growth to internal buttressing, existence of a distinct petalodium, and anterior-posterior asymmetry during development. The parametric values of growth functions derived from the results are a basis for computational modeling of growth and development in sand dollars.

Work stress, asthma control and asthma-specific quality of life: Initial evidence from a cross-sectional study.

PubMed

Hartmann, Bettina; Leucht, Verena; Loerbroks, Adrian

2017-03-01

Research has suggested that psychological stress is positively associated with asthma morbidity. One major source of stress in adulthood is one's occupation. However, to date, potential links of work stress with asthma control or asthma-specific quality of life have not been examined. We aimed to address this knowledge gap. In 2014/2015, we conducted a cross-sectional study among adults with asthma in Germany (n = 362). For the current analyses that sample was restricted to participants in employment and reporting to have never been diagnosed with chronic obstructive pulmonary disease (n = 94). Work stress was operationalized by the 16-item effort-reward-imbalance (ERI) questionnaire, which measures the subcomponents "effort", "reward" and "overcommitment." Participants further completed the Asthma Control Test and the Asthma Quality of Life Questionnaire-Sydney. Multivariable associations were quantified by linear regression and logistic regression. Effort, reward and their ratio (i.e. ERI ratio) did not show meaningful associations with asthma morbidity. By contrast, increasing levels of overcommitment were associated with poorer asthma control and worse quality of life in both linear regression (ß = -0.26, p = 0.01 and ß = 0.44, p < 0.01, respectively) and logistic regression (odds ratio [OR] = 1.87, 95% confidence interval [CI] = 1.14-3.07 and OR = 2.34, 95% CI = 1.32-4.15, respectively). The present study provides initial evidence of a positive relationship of work-related overcommitment with asthma control and asthma-specific quality of life. Longitudinal studies with larger samples are needed to confirm our findings and to disentangle the potential causality of associations.

Quality Reporting of Multivariable Regression Models in Observational Studies: Review of a Representative Sample of Articles Published in Biomedical Journals.

PubMed

Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M

2016-05-01

Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE.Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model.The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0-30.3) of the articles and 18.5% (95% CI: 14.8-22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor.A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature.

Attitude and practice of physical activity and social problem-solving ability among university students.

PubMed

Sone, Toshimasa; Kawachi, Yousuke; Abe, Chihiro; Otomo, Yuki; Sung, Yul-Wan; Ogawa, Seiji

2017-04-04

Effective social problem-solving abilities can contribute to decreased risk of poor mental health. In addition, physical activity has a favorable effect on mental health. These previous studies suggest that physical activity and social problem-solving ability can interact by helping to sustain mental health. The present study aimed to determine the association between attitude and practice of physical activity and social problem-solving ability among university students. Information on physical activity and social problem-solving was collected using a self-administered questionnaire. We analyzed data from 185 students who participated in the questionnaire surveys and psychological tests. Social problem-solving as measured by the Social Problem-Solving Inventory-Revised (SPSI-R) (median score 10.85) was the dependent variable. Multiple logistic regression analysis was employed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for higher SPSI-R according to physical activity categories. The multiple logistic regression analysis indicated that the ORs (95% CI) in reference to participants who said they never considered exercising were 2.08 (0.69-6.93), 1.62 (0.55-5.26), 2.78 (0.86-9.77), and 6.23 (1.81-23.97) for participants who did not exercise but intended to start, tried to exercise but did not, exercised but not regularly, and exercised regularly, respectively. This finding suggested that positive linear association between physical activity and social problem-solving ability (p value for linear trend < 0.01). The present findings suggest that regular physical activity or intention to start physical activity may be an effective strategy to improve social problem-solving ability.

Maternal exposures and risk of spontaneous abortion before and after a community oriented health education campaign.

PubMed

Agnesi, Roberto; Valentini, Flavio; Fedeli, Ugo; Rylander, Ragnar; Meneghetti, Maurizia; Fadda, Emanuela; Buja, Alessandra; Mastrangelo, Giuseppe

2011-06-01

In a district of Veneto (North-east Italy) where numerous females of childbearing age were occupationally exposed to organic solvents in nearly 400 shoe factories, a case-control study found significant associations between maternal exposures (from occupation and risky behavior) and spontaneous abortion (SAB). Thereafter, a health education campaign was undertaken to increase awareness of risk factors for pregnancy in the population. To evaluate the effects of this campaign maternal exposures and SAB risks were compared before and after the campaign. Hospital records were collected from a local hospital for SAB cases and age- residence-matched controls with normal deliveries. Information on solvent exposure, coffee and alcohol consumption, smoking and the use of medication was collected using a questionnaire. Before and after differences were tested through a modified Chi-square test and linear and logistic regressions for survey data. Odds ratios (ORs) with 95% confidence interval (CI) were estimated using logistic regression models. The consumption of coffee (P = 0.003) and alcohol (P < 0.001) was lower after than before the campaign, controlling for age at pregnancy and level of education. There were no differences in reported solvent exposure or smoking (smokers were few). The previously detected increased risks of SAB in relation to solvent exposure and coffee consumption were no longer present. The results suggest that health education campaigns might reduce harmful maternal exposures and the risk of SAB.

Non-linear Growth Models in Mplus and SAS

PubMed Central

Grimm, Kevin J.; Ram, Nilam

2013-01-01

Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data collected as part of a study examining the effects of preschool instruction on academic gain we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included. PMID:23882134

Linearized Alternating Direction Method of Multipliers for Constrained Nonconvex Regularized Optimization

DTIC Science & Technology

2016-11-22

structure of the graph, we replace the ℓ1- norm by the nonconvex Capped -ℓ1 norm , and obtain the Generalized Capped -ℓ1 regularized logistic regression...X. M. Yuan. Linearized augmented lagrangian and alternating direction methods for nuclear norm minimization. Mathematics of Computation, 82(281):301...better approximations of ℓ0- norm theoretically and computationally beyond ℓ1- norm , for example, the compressive sensing (Xiao et al., 2011). The

The relationship of reported HIV risk and history of HIV testing among emergency department patients.

PubMed

Merchant, Roland C; Freelove, Sarah M; Langan, Thomas J; Clark, Melissa A; Mayer, Kenneth H; Seage, George R; DeGruttola, Victor G

2010-01-01

Among a random sample of emergency department (ED) patients, we sought to determine the extent to which reported risk for human immunodeficiency virus (HIV) is related to ever having been tested for HIV. A random sample of patients (aged 18-64 years) from an adult, urban, northeastern United States, academic ED were surveyed about their history of ever having been tested for HIV and their reported HIV risk behaviors. A reported HIV risk score was calculated from the survey responses and divided into 4 levels, based on quartiles of the risk scores. Pearson's X(2) testing was used to compare HIV testing history and level of reported HIV risk. Logistic regression models were created to investigate the association between level of reported HIV risk and the outcome of ever having been tested for HIV. Of the 557 participants, 62.1% were female. A larger proportion of females than males (71.4% vs 60.6%; P < 0.01) reported they had been tested for HIV. Among the 211 males, 11.4% reported no HIV risk, and among the 346 females, 10.7% reported no HIV risk. The proportion of those who had been tested for HIV was greater among those reporting any risk compared with those reporting no risk for females (75.4% vs 37.8%; P < 0.001), but not for males (59.9% vs 66.7%; P < 0.52). However, certain high-risk behaviors, such as a history of injection-drug use, were associated with prior HIV testing for both genders. In the logistic regression analyses, there was no relationship between increasing level of reported HIV risk and a history of ever having been tested for HIV for males. For females, a history of ever having been tested was related to increasing level of reported risk, but not in a linear fashion. The relationship between reported HIV risk and history of testing among these ED patients was complex and differed by gender. Among these patients, having greater risk did not necessarily mean a higher likelihood of ever having been tested for HIV.

The use of auxiliary variables in capture-recapture and removal experiments

USGS Publications Warehouse

Pollock, K.H.; Hines, J.E.; Nichols, J.D.

1984-01-01

The dependence of animal capture probabilities on auxiliary variables is an important practical problem which has not been considered in the development of estimation procedures for capture-recapture and removal experiments. In this paper the linear logistic binary regression model is used to relate the probability of capture to continuous auxiliary variables. The auxiliary variables could be environmental quantities such as air or water temperature, or characteristics of individual animals, such as body length or weight. Maximum likelihood estimators of the population parameters are considered for a variety of models which all assume a closed population. Testing between models is also considered. The models can also be used when one auxiliary variable is a measure of the effort expended in obtaining the sample.

Reporting quality of multivariable logistic regression in selected Indian medical journals.

PubMed

Kumar, R; Indrayan, A; Chhabra, P

2012-01-01

Use of multivariable logistic regression (MLR) modeling has steeply increased in the medical literature over the past few years. Testing of model assumptions and adequate reporting of MLR allow the reader to interpret results more accurately. To review the fulfillment of assumptions and reporting quality of MLR in selected Indian medical journals using established criteria. Analysis of published literature. Medknow.com publishes 68 Indian medical journals with open access. Eight of these journals had at least five articles using MLR between the years 1994 to 2008. Articles from each of these journals were evaluated according to the previously established 10-point quality criteria for reporting and to test the MLR model assumptions. SPSS 17 software and non-parametric test (Kruskal-Wallis H, Mann Whitney U, Spearman Correlation). One hundred and nine articles were finally found using MLR for analyzing the data in the selected eight journals. The number of such articles gradually increased after year 2003, but quality score remained almost similar over time. P value, odds ratio, and 95% confidence interval for coefficients in MLR was reported in 75.2% and sufficient cases (>10) per covariate of limiting sample size were reported in the 58.7% of the articles. No article reported the test for conformity of linear gradient for continuous covariates. Total score was not significantly different across the journals. However, involvement of statistician or epidemiologist as a co-author improved the average quality score significantly (P=0.014). Reporting of MLR in many Indian journals is incomplete. Only one article managed to score 8 out of 10 among 109 articles under review. All others scored less. Appropriate guidelines in instructions to authors, and pre-publication review of articles using MLR by a qualified statistician may improve quality of reporting.

Manufacturing Challenges and Benefits when Scaling the HIAD Stacked-Torus Aeroshell to a 15m-Class System

NASA Technical Reports Server (NTRS)

Swanson, Gregory; Cheatwood, Neil; Johnson, Keith; Calomino, Anthony; Gilles, Brian; Anderson, Paul; Bond, Bruce

2016-01-01

Over a decade of work has been conducted in the development of NASAs Hypersonic Inflatable Aerodynamic Decelerator (HIAD) deployable aeroshell technology. This effort has included multiple ground test campaigns and flight tests culminating in the HIAD projects second generation (Gen-2) aeroshell system. The HIAD project team has developed, fabricated, and tested stacked-torus inflatable structures (IS) with flexible thermal protection systems (F-TPS) ranging in diameters from 3-6m, with cone angles of 60 and 70 deg. To meet NASA and commercial near term objectives, the HIAD team must scale the current technology up to 12-15m in diameter. Therefore, the HIAD projects experience in scaling the technology has reached a critical juncture. Growing from a 6m to a 15m-class system will introduce many new structural and logistical challenges to an already complicated manufacturing process.Although the general architecture and key aspects of the HIAD design scale well to larger vehicles, details of the technology will need to be reevaluated and possibly redesigned for use in a 15m-class HIAD system. These include: layout and size of the structural webbing that transfers load throughout the IS, inflatable gas barrier design, torus diameter and braid construction, internal pressure and inflation line routing, adhesives used for coating and bonding, and F-TPS gore design and seam fabrication. The logistics of fabricating and testing the IS and the F-TPS also become more challenging with increased scale. Compared to the 6m aeroshell (the largest HIAD built to date), a 12m aeroshell has four times the cross-sectional area, and a 15m one has over six times the area. This means that fabrication and test procedures will need to be reexamined to ac-count for the sheer size and weight of the aeroshell components. This will affect a variety of steps in the manufacturing process, such as: stacking the tori during assembly, stitching the structural webbing, initial inflation of tori, and stitching of F-TPS gores. Additionally, new approaches and hardware will be required for handling and ground testing of both individual tori and the fully assembled HIADs.There are also noteworthy benefits of scaling up the HIAD aeroshell to a 15m-class system. Two complications in working with handmade textile structures are the non-linearity of the material components and the role of human accuracy during fabrication. Larger, more capable, HIAD structures should see much larger operational loads, potentially bringing the structural response of the material components out of the non-linear regime and into the preferred linear response range. Also, making the reasonable assumption that the magnitude of fabrication accuracy remains constant as the structures grow, the relative effect of fabrication errors should decrease as a percentage of the textile component size. Combined, these two effects improve the predictive capability and the uniformity of the structural response for a 12-15m HIAD.In this presentation, a handful of the challenges and associated mitigation plans will be discussed, as well as an update on current 12m aeroshell manufacturing and testing that is addressing these challenges

Manufacturing Challenges and Benefits When Scaling the HIAD Stacked-Torus Aeroshell to a 15 Meter Class System

NASA Technical Reports Server (NTRS)

Swanson, G. T.; Cheatwood, F. M.; Johnson, R. K.; Hughes, S. J.; Calomino, A. M.

2016-01-01

Over a decade of work has been conducted in the development of NASA's Hypersonic Inflatable Aerodynamic Decelerator (HIAD) deployable aeroshell technology. This effort has included multiple ground test campaigns and flight tests culminating in the HIAD project's second generation (Gen-2) aeroshell system. The HIAD project team has developed, fabricated, and tested stacked-torus inflatable structures (IS) with flexible thermal protection systems (F-TPS) ranging in diameters from 3-6 meters, with cone angles of 60 and 70 degrees. To meet NASA and commercial near-term objectives, the HIAD team must scale the current technology up to 12-15 meters in diameter. Therefore, the HIAD project's experience in scaling the technology has reached a critical juncture. Growing from a 6-meter to a 15-meter class system will introduce many new structural and logistical challenges to an already complicated manufacturing process. Although the general architecture and key aspects of the HIAD design scale well to larger vehicles, details of the technology will need to be reevaluated and possibly redesigned for use in a 15-meter-class HIAD system. These include: layout and size of the structural webbing that transfers load throughout the IS, inflatable gas barrier design, torus diameter and braid construction, internal pressure and inflation line routing, adhesives used for coating and bonding, and F-TPS gore design and seam fabrication. The logistics of fabricating and testing the IS and the F-TPS also become more challenging with increased scale. Compared to the 6-meter aeroshell (the largest HIAD built to date), a 12-meter aeroshell has four times the cross-sectional area, and a 15-meter one has over six times the area. This means that fabrication and test procedures will need to be reexamined to account for the sheer size and weight of the aeroshell components. This will affect a variety of steps in the manufacturing process, such as: stacking the tori during assembly, stitching the structural webbing, initial inflation of tori, and stitching of F-TPS gores. Additionally, new approaches and hardware will be required for handling and ground testing of both individual tori and the fully assembled HIADs. There are also noteworthy benefits of scaling up the HIAD aeroshell to a 15m-class system. Two complications in working with handmade textile structures are the non-linearity of the material components and the role of human accuracy during fabrication. Larger, more capable, HIAD structures should see much larger operational loads, potentially bringing the structural response of the material components out of the non-linear regime and into the preferred linear response range. Also, making the reasonable assumption that the magnitude of fabrication accuracy remains constant as the structures grow, the relative effect of fabrication errors should decrease as a percentage of the textile component size. Combined, these two effects improve the predictive capability and the uniformity of the structural response for a 12-15-meter HIAD. In this presentation, a handful of the challenges and associated mitigation plans will be discussed, as well as an update on current manufacturing and testing that addressing these challenges.

Self-powered monitoring of repeated head impacts using time-dilation energy measurement circuit.

PubMed

Feng, Tao; Aono, Kenji; Covassin, Tracey; Chakrabartty, Shantanu

2015-04-01

Due to the current epidemic levels of sport-related concussions (SRC) in the U.S., there is a pressing need for technologies that can facilitate long-term and continuous monitoring of head impacts. Existing helmet-sensor technology is inconsistent, inaccurate, and is not economically or logistically practical for large-scale human studies. In this paper, we present the design of a miniature, battery-less, self-powered sensor that can be embedded inside sport helmets and can continuously monitor and store different spatial and temporal statistics of the helmet impacts. At the core of the proposed sensor is a novel time-dilation circuit that allows measurement of a wide-range of impact energies. In this paper an array of linear piezo-floating-gate (PFG) injectors has been used for self-powered sensing and storage of linear and rotational head-impact statistics. The stored statistics are then retrieved using a plug-and-play reader and has been used for offline data analysis. We report simulation and measurement results validating the functionality of the time-dilation circuit for different levels of impact energies. Also, using prototypes of linear PFG integrated circuits fabricated in a 0.5 μm CMOS process, we demonstrate the functionality of the proposed helmet-sensors using controlled drop tests.

Open Relationships, Nonconsensual Nonmonogamy, and Monogamy Among U.S. Adults: Findings from the 2012 National Survey of Sexual Health and Behavior.

PubMed

Levine, Ethan Czuy; Herbenick, Debby; Martinez, Omar; Fu, Tsung-Chieh; Dodge, Brian

2018-07-01

People in open and other consensually nonmonogamous partnerships have been historically underserved by researchers and providers. Many studies group such partnerships together with nonconsensual nonmonogamy (NCNM) under the banner of "concurrent sexual partnerships." Discrimination from service providers poses a substantial barrier to care. Responding to such concerns, this investigation explored sociodemographic correlates with open relationships and associations between relationship structure and sexual risk, HIV/STI testing, and relationship satisfaction in a nationally representative probability sample. Data were drawn from the 2012 National Survey of Sexual Health and Behavior (n = 2270). We used multinomial logistic regression to identify correlates with relationship structure, and linear and logistic regression to investigate associations between relationship structure and testing, condom use, and relationship satisfaction. Eighty-nine percent of participants reported monogamy, 4% reported open relationships, and 8% reported NCNM. Males, gay/lesbian individuals, bisexual individuals, and those who identified as "Other, Non-Hispanic" were more likely to report open relationships. Bisexual individuals and Black, Non-Hispanic participants were more likely to report NCNM; older participants were less likely to do so. Participants in open relationships reported more frequent condom use for anal intercourse and lower relationship satisfaction than monogamous participants. NCNM participants reported more HIV testing and lower satisfaction. Identities, experiences, and behaviors within open and other consensually nonmonogamous populations should be regarded as unique and diverse, rather than conflated with those common to other relationship structures. There is a need for greater awareness of diverse relationship structures among researchers and providers, and incorporation of related content into educational programming.

A screening system for smear-negative pulmonary tuberculosis using artificial neural networks.

PubMed

de O Souza Filho, João B; de Seixas, José Manoel; Galliez, Rafael; de Bragança Pereira, Basilio; de Q Mello, Fernanda C; Dos Santos, Alcione Miranda; Kritski, Afranio Lineu

2016-08-01

Molecular tests show low sensitivity for smear-negative pulmonary tuberculosis (PTB). A screening and risk assessment system for smear-negative PTB using artificial neural networks (ANNs) based on patient signs and symptoms is proposed. The prognostic and risk assessment models exploit a multilayer perceptron (MLP) and inspired adaptive resonance theory (iART) network. Model development considered data from 136 patients with suspected smear-negative PTB in a general hospital. MLP showed higher sensitivity (100%, 95% confidence interval (CI) 78-100%) than the other techniques, such as support vector machine (SVM) linear (86%; 95% CI 60-96%), multivariate logistic regression (MLR) (79%; 95% CI 53-93%), and classification and regression tree (CART) (71%; 95% CI 45-88%). MLR showed a slightly higher specificity (85%; 95% CI 59-96%) than MLP (80%; 95% CI 54-93%), SVM linear (75%, 95% CI 49-90%), and CART (65%; 95% CI 39-84%). In terms of the area under the receiver operating characteristic curve (AUC), the MLP model exhibited a higher value (0.918, 95% CI 0.824-1.000) than the SVM linear (0.796, 95% CI 0.651-0.970) and MLR (0.782, 95% CI 0.663-0.960) models. The significant signs and symptoms identified in risk groups are coherent with clinical practice. In settings with a high prevalence of smear-negative PTB, the system can be useful for screening and also to aid clinical practice in expediting complementary tests for higher risk patients. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley

2007-01-01

Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.

Combining biological and psychosocial baseline variables did not improve prediction of outcome of a very-low-energy diet in a clinic referral population.

PubMed

Sumithran, P; Purcell, K; Kuyruk, S; Proietto, J; Prendergast, L A

2018-02-01

Consistent, strong predictors of obesity treatment outcomes have not been identified. It has been suggested that broadening the range of predictor variables examined may be valuable. We explored methods to predict outcomes of a very-low-energy diet (VLED)-based programme in a clinically comparable setting, using a wide array of pre-intervention biological and psychosocial participant data. A total of 61 women and 39 men (mean ± standard deviation [SD] body mass index: 39.8 ± 7.3 kg/m 2 ) underwent an 8-week VLED and 12-month follow-up. At baseline, participants underwent a blood test and assessment of psychological, social and behavioural factors previously associated with treatment outcomes. Logistic regression, linear discriminant analysis, decision trees and random forests were used to model outcomes from baseline variables. Of the 100 participants, 88 completed the VLED and 42 attended the Week 60 visit. Overall prediction rates for weight loss of ≥10% at weeks 8 and 60, and attrition at Week 60, using combined data were between 77.8 and 87.6% for logistic regression, and lower for other methods. When logistic regression analyses included only baseline demographic and anthropometric variables, prediction rates were 76.2-86.1%. In this population, considering a wide range of biological and psychosocial data did not improve outcome prediction compared to simply-obtained baseline characteristics. © 2017 World Obesity Federation.

Bias in logistic regression due to imperfect diagnostic test results and practical correction approaches.

PubMed

Valle, Denis; Lima, Joanna M Tucker; Millar, Justin; Amratia, Punam; Haque, Ubydul

2015-11-04

Logistic regression is a statistical model widely used in cross-sectional and cohort studies to identify and quantify the effects of potential disease risk factors. However, the impact of imperfect tests on adjusted odds ratios (and thus on the identification of risk factors) is under-appreciated. The purpose of this article is to draw attention to the problem associated with modelling imperfect diagnostic tests, and propose simple Bayesian models to adequately address this issue. A systematic literature review was conducted to determine the proportion of malaria studies that appropriately accounted for false-negatives/false-positives in a logistic regression setting. Inference from the standard logistic regression was also compared with that from three proposed Bayesian models using simulations and malaria data from the western Brazilian Amazon. A systematic literature review suggests that malaria epidemiologists are largely unaware of the problem of using logistic regression to model imperfect diagnostic test results. Simulation results reveal that statistical inference can be substantially improved when using the proposed Bayesian models versus the standard logistic regression. Finally, analysis of original malaria data with one of the proposed Bayesian models reveals that microscopy sensitivity is strongly influenced by how long people have lived in the study region, and an important risk factor (i.e., participation in forest extractivism) is identified that would have been missed by standard logistic regression. Given the numerous diagnostic methods employed by malaria researchers and the ubiquitous use of logistic regression to model the results of these diagnostic tests, this paper provides critical guidelines to improve data analysis practice in the presence of misclassification error. Easy-to-use code that can be readily adapted to WinBUGS is provided, enabling straightforward implementation of the proposed Bayesian models.

Education level as a predictor of condom use in jail-incarcerated women, with fundamental cause analysis.

PubMed

Emerson, Amanda M; Carroll, Hsiang-Feng; Ramaswamy, Megha

2018-05-27

To model condom usage by jail-incarcerated women incarcerated in US local jails and understand results in terms of fundamental cause theory. We surveyed 102 women in an urban jail in the Midwest United States. Chi-square tests and generalized linear modeling were used to identify factors of significance for women who used condoms during last sex compared with women who did not. Stepwise multiple logistic regression was conducted to estimate the relation between the outcome variable and variables linked to condom use in the literature. Logistic regression showed that for women who completed high school odds of reporting condom use during last sex were 2.78 times higher (p = .043) than the odds for women with less than a high school education. Among women who responded no to ever having had a sexually transmitted infection, odds of using a condom during last sex were 2.597 times (p = .03) higher than odds for women who responded that they had had a sexually transmitted infection. Education is a fundamental cause of reproductive health risk among incarcerated women. We recommend interventions that creatively target distal over proximal factors. © 2018 Wiley Periodicals, Inc.

Analysis of the single-vehicle cyclic inventory routing problem

NASA Astrophysics Data System (ADS)

Aghezzaf, El-Houssaine; Zhong, Yiqing; Raa, Birger; Mateo, Manel

2012-11-01

The single-vehicle cyclic inventory routing problem (SV-CIRP) consists of a repetitive distribution of a product from a single depot to a selected subset of customers. For each customer, selected for replenishments, the supplier collects a corresponding fixed reward. The objective is to determine the subset of customers to replenish, the quantity of the product to be delivered to each and to design the vehicle route so that the resulting profit (difference between the total reward and the total logistical cost) is maximised while preventing stockouts at each of the selected customers. This problem appears often as a sub-problem in many logistical problems. In this article, the SV-CIRP is formulated as a mixed-integer program with a nonlinear objective function. After a thorough analysis of the structure of the problem and its features, an exact algorithm for its solution is proposed. This exact algorithm requires only solutions of linear mixed-integer programs. Values of a savings-based heuristic for this problem are compared to the optimal values obtained for a set of some test problems. In general, the gap may get as large as 25%, which justifies the effort to continue exploring and developing exact and approximation algorithms for the SV-CIRP.

Innovative hyperchaotic encryption algorithm for compressed video

NASA Astrophysics Data System (ADS)

Yuan, Chun; Zhong, Yuzhuo; Yang, Shiqiang

2002-12-01

It is accepted that stream cryptosystem can achieve good real-time performance and flexibility which implements encryption by selecting few parts of the block data and header information of the compressed video stream. Chaotic random number generator, for example Logistics Map, is a comparatively promising substitute, but it is easily attacked by nonlinear dynamic forecasting and geometric information extracting. In this paper, we present a hyperchaotic cryptography scheme to encrypt the compressed video, which integrates Logistics Map with Z(232 - 1) field linear congruential algorithm to strengthen the security of the mono-chaotic cryptography, meanwhile, the real-time performance and flexibility of the chaotic sequence cryptography are maintained. It also integrates with the dissymmetrical public-key cryptography and implements encryption and identity authentification on control parameters at initialization phase. In accord with the importance of data in compressed video stream, encryption is performed in layered scheme. In the innovative hyperchaotic cryptography, the value and the updating frequency of control parameters can be changed online to satisfy the requirement of the network quality, processor capability and security requirement. The innovative hyperchaotic cryprography proves robust security by cryptoanalysis, shows good real-time performance and flexible implement capability through the arithmetic evaluating and test.

Majorization Minimization by Coordinate Descent for Concave Penalized Generalized Linear Models

PubMed Central

Jiang, Dingfeng; Huang, Jian

2013-01-01

Recent studies have demonstrated theoretical attractiveness of a class of concave penalties in variable selection, including the smoothly clipped absolute deviation and minimax concave penalties. The computation of the concave penalized solutions in high-dimensional models, however, is a difficult task. We propose a majorization minimization by coordinate descent (MMCD) algorithm for computing the concave penalized solutions in generalized linear models. In contrast to the existing algorithms that use local quadratic or local linear approximation to the penalty function, the MMCD seeks to majorize the negative log-likelihood by a quadratic loss, but does not use any approximation to the penalty. This strategy makes it possible to avoid the computation of a scaling factor in each update of the solutions, which improves the efficiency of coordinate descent. Under certain regularity conditions, we establish theoretical convergence property of the MMCD. We implement this algorithm for a penalized logistic regression model using the SCAD and MCP penalties. Simulation studies and a data example demonstrate that the MMCD works sufficiently fast for the penalized logistic regression in high-dimensional settings where the number of covariates is much larger than the sample size. PMID:25309048

General equations for optimal selection of diagnostic image acquisition parameters in clinical X-ray imaging.

PubMed

Zheng, Xiaoming

2017-12-01

The purpose of this work was to examine the effects of relationship functions between diagnostic image quality and radiation dose on the governing equations for image acquisition parameter variations in X-ray imaging. Various equations were derived for the optimal selection of peak kilovoltage (kVp) and exposure parameter (milliAmpere second, mAs) in computed tomography (CT), computed radiography (CR), and direct digital radiography. Logistic, logarithmic, and linear functions were employed to establish the relationship between radiation dose and diagnostic image quality. The radiation dose to the patient, as a function of image acquisition parameters (kVp, mAs) and patient size (d), was used in radiation dose and image quality optimization. Both logistic and logarithmic functions resulted in the same governing equation for optimal selection of image acquisition parameters using a dose efficiency index. For image quality as a linear function of radiation dose, the same governing equation was derived from the linear relationship. The general equations should be used in guiding clinical X-ray imaging through optimal selection of image acquisition parameters. The radiation dose to the patient could be reduced from current levels in medical X-ray imaging.

Text mining approach to predict hospital admissions using early medical records from the emergency department.

PubMed

Lucini, Filipe R; S Fogliatto, Flavio; C da Silveira, Giovani J; L Neyeloff, Jeruza; Anzanello, Michel J; de S Kuchenbecker, Ricardo; D Schaan, Beatriz

2017-04-01

Emergency department (ED) overcrowding is a serious issue for hospitals. Early information on short-term inward bed demand from patients receiving care at the ED may reduce the overcrowding problem, and optimize the use of hospital resources. In this study, we use text mining methods to process data from early ED patient records using the SOAP framework, and predict future hospitalizations and discharges. We try different approaches for pre-processing of text records and to predict hospitalization. Sets-of-words are obtained via binary representation, term frequency, and term frequency-inverse document frequency. Unigrams, bigrams and trigrams are tested for feature formation. Feature selection is based on χ 2 and F-score metrics. In the prediction module, eight text mining methods are tested: Decision Tree, Random Forest, Extremely Randomized Tree, AdaBoost, Logistic Regression, Multinomial Naïve Bayes, Support Vector Machine (Kernel linear) and Nu-Support Vector Machine (Kernel linear). Prediction performance is evaluated by F1-scores. Precision and Recall values are also informed for all text mining methods tested. Nu-Support Vector Machine was the text mining method with the best overall performance. Its average F1-score in predicting hospitalization was 77.70%, with a standard deviation (SD) of 0.66%. The method could be used to manage daily routines in EDs such as capacity planning and resource allocation. Text mining could provide valuable information and facilitate decision-making by inward bed management teams. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

A practical guide to environmental association analysis in landscape genomics.

PubMed

Rellstab, Christian; Gugerli, Felix; Eckert, Andrew J; Hancock, Angela M; Holderegger, Rolf

2015-09-01

Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced-representation sequencing, candidate-gene approaches, linearity of allele-environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies. © 2015 John Wiley & Sons Ltd.

CUSUM-Logistic Regression analysis for the rapid detection of errors in clinical laboratory test results.

PubMed

Sampson, Maureen L; Gounden, Verena; van Deventer, Hendrik E; Remaley, Alan T

2016-02-01

The main drawback of the periodic analysis of quality control (QC) material is that test performance is not monitored in time periods between QC analyses, potentially leading to the reporting of faulty test results. The objective of this study was to develop a patient based QC procedure for the more timely detection of test errors. Results from a Chem-14 panel measured on the Beckman LX20 analyzer were used to develop the model. Each test result was predicted from the other 13 members of the panel by multiple regression, which resulted in correlation coefficients between the predicted and measured result of >0.7 for 8 of the 14 tests. A logistic regression model, which utilized the measured test result, the predicted test result, the day of the week and time of day, was then developed for predicting test errors. The output of the logistic regression was tallied by a daily CUSUM approach and used to predict test errors, with a fixed specificity of 90%. The mean average run length (ARL) before error detection by CUSUM-Logistic Regression (CSLR) was 20 with a mean sensitivity of 97%, which was considerably shorter than the mean ARL of 53 (sensitivity 87.5%) for a simple prediction model that only used the measured result for error detection. A CUSUM-Logistic Regression analysis of patient laboratory data can be an effective approach for the rapid and sensitive detection of clinical laboratory errors. Published by Elsevier Inc.

Estimating Contraceptive Prevalence Using Logistics Data for Short-Acting Methods: Analysis Across 30 Countries.

PubMed

Cunningham, Marc; Bock, Ariella; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana

2015-09-01

Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed. © Cunningham et al.

Estimating Contraceptive Prevalence Using Logistics Data for Short-Acting Methods: Analysis Across 30 Countries

PubMed Central

Cunningham, Marc; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana

2015-01-01

Background: Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Methods: Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. Results: For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (P<.05) with the referent DHS values for both bivariate and multivariate models. For condoms, however, that association was only significant for the bivariate model. With the exception of the CYP-based model for condoms, models were able to estimate public-sector prevalence rates for each short-acting method to within 2 percentage points in at least 85% of countries. Conclusions: Public-sector contraceptive logistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The models provide a starting point for generating interim estimates of contraceptive use when timely survey data are unavailable. All models except the condoms CYP model performed well; the regression models were most accurate but the CYP model offers the simplest calculation method. Future work extending the research to other modern methods, relating subnational logistics data with prevalence rates, and tracking that relationship over time is needed. PMID:26374805

An Evaluation of One- and Three-Parameter Logistic Tailored Testing Procedures for Use with Small Item Pools.

ERIC Educational Resources Information Center

McKinley, Robert L.; Reckase, Mark D.

A two-stage study was conducted to compare the ability estimates yielded by tailored testing procedures based on the one-parameter logistic (1PL) and three-parameter logistic (3PL) models. The first stage of the study employed real data, while the second stage employed simulated data. In the first stage, response data for 3,000 examinees were…

LOGMIS Programmed Texts, Tests and Answers.

DTIC Science & Technology

1979-04-01

This publication contains the programmed text and related test and answer booklets produced to teach field users correct procedures for utilization of the Army’s Logistics Management Information System (LOGMIS). It was prepared by ARINC Research Corporation under Contract DAEA18-77-C-0184 for the Logistics Evaluation Branch, Plans and Programs Division of the Assistant Chief of Staff for Logistics, U.S. Army Communications Command. (Author)

The Trend Odds Model for Ordinal Data‡

PubMed Central

Capuano, Ana W.; Dawson, Jeffrey D.

2013-01-01

Ordinal data appear in a wide variety of scientific fields. These data are often analyzed using ordinal logistic regression models that assume proportional odds. When this assumption is not met, it may be possible to capture the lack of proportionality using a constrained structural relationship between the odds and the cut-points of the ordinal values (Peterson and Harrell, 1990). We consider a trend odds version of this constrained model, where the odds parameter increases or decreases in a monotonic manner across the cut-points. We demonstrate algebraically and graphically how this model is related to latent logistic, normal, and exponential distributions. In particular, we find that scale changes in these potential latent distributions are consistent with the trend odds assumption, with the logistic and exponential distributions having odds that increase in a linear or nearly linear fashion. We show how to fit this model using SAS Proc Nlmixed, and perform simulations under proportional odds and trend odds processes. We find that the added complexity of the trend odds model gives improved power over the proportional odds model when there are moderate to severe departures from proportionality. A hypothetical dataset is used to illustrate the interpretation of the trend odds model, and we apply this model to a Swine Influenza example where the proportional odds assumption appears to be violated. PMID:23225520

The trend odds model for ordinal data.

PubMed

Capuano, Ana W; Dawson, Jeffrey D

2013-06-15

Ordinal data appear in a wide variety of scientific fields. These data are often analyzed using ordinal logistic regression models that assume proportional odds. When this assumption is not met, it may be possible to capture the lack of proportionality using a constrained structural relationship between the odds and the cut-points of the ordinal values. We consider a trend odds version of this constrained model, wherein the odds parameter increases or decreases in a monotonic manner across the cut-points. We demonstrate algebraically and graphically how this model is related to latent logistic, normal, and exponential distributions. In particular, we find that scale changes in these potential latent distributions are consistent with the trend odds assumption, with the logistic and exponential distributions having odds that increase in a linear or nearly linear fashion. We show how to fit this model using SAS Proc NLMIXED and perform simulations under proportional odds and trend odds processes. We find that the added complexity of the trend odds model gives improved power over the proportional odds model when there are moderate to severe departures from proportionality. A hypothetical data set is used to illustrate the interpretation of the trend odds model, and we apply this model to a swine influenza example wherein the proportional odds assumption appears to be violated. Copyright © 2012 John Wiley & Sons, Ltd.

Manufacturing Challenges and Benefits when Scaling the HIAD Stacked-Torus Aeroshell to a 15m Class System

NASA Technical Reports Server (NTRS)

Cheatwood, F. McNeil; Swanson, Gregory T.; Johnson, R. Keith; Hughes, Stephen; Calomino, Anthony; Gilles, Brian; Anderson, Paul; Bond, Bruce

2016-01-01

Over a decade of work has been conducted in the development of NASA's Hypersonic Inflatable Aerodynamic Decelerator (HIAD) deployable aeroshell technology. This effort has included multiple ground test campaigns and flight tests culminating in the HIAD project's second generation (Gen-2) aeroshell system. The HIAD project team has developed, fabricated, and tested stacked-torus inflatable structures (IS) with flexible thermal protection systems (F-TPS) ranging in diameters from 3-6m, with cone angles of 60 and 70 deg. To meet NASA and commercial near term objectives, the HIAD team must scale the current technology up to 12-15m in diameter. The HIAD project's experience in scaling the technology has reached a critical juncture. Growing from a 6m to a 15m class system will introduce many new structural and logistical challenges to an already complicated manufacturing process. Although the general architecture and key aspects of the HIAD design scale well to larger vehicles, details of the technology will need to be reevaluated and possibly redesigned for use in a 15m-class HIAD system. These include: layout and size of the structural webbing that transfers load throughout the IS, inflatable gas barrier design, torus diameter and braid construction, internal pressure and inflation line routing, adhesives used for coating and bonding, and F-TPS gore design and seam fabrication. The logistics of fabricating and testing the IS and the F-TPS also become more challenging with increased scale. Compared to the 6m aeroshell (the largest HIAD built to date), a 12m aeroshell has four times the cross-sectional area, and a 15m one has over six times the area. This means that fabrication and test procedures will need to be reexamined to account for the sheer size and weight of the aeroshell components. This will affect a variety of steps in the manufacturing process, such as: stacking the tori during assembly, stitching the structural webbing, initial inflation of tori, and stitching of F-TPS gores. Additionally, new approaches and hardware will be required for handling and ground testing of both individual tori and the fully assembled HIADs. There are also noteworthy benefits of scaling up the HIAD aeroshell to 15m-class system. Two complications in working with handmade textiles structures are the non-linearity of the materials and the role of human accuracy during fabrication. Larger, more capable, HIAD structures should see much larger operational loads, potentially bringing the structural response of the materials out of the non-linear regime and into the preferred linear response range. Also, making the reasonable assumption that the magnitude of fabrication accuracy remains constant as the structures grow, the relative effect of fabrication errors should decrease as a percentage of the textile component size. Combined, these two effects improve the predictive capability and the uniformity of the structural response for a 12-15m class HIAD. In this paper, the challenges and associated mitigation plans related to scaling up the HIAD stacked-torus aeroshell to a 15m class system will be discussed. In addition, the benefits of enlarging the structure will be further explored.

Coping Styles in Heart Failure Patients with Depressive Symptoms

PubMed Central

Trivedi, Ranak B.; Blumenthal, James A.; O'Connor, Christopher; Adams, Kirkwood; Hinderliter, Alan; Sueta-Dupree, Carla; Johnson, Kristy; Sherwood, Andrew

2009-01-01

Objective Elevated depressive symptoms have been linked to poorer prognosis in heart failure (HF) patients. Our objective was to identify coping styles associated with depressive symptoms in HF patients. Methods 222 stable HF patients (32.75% female, 45.4% non-Hispanic Black) completed multiple questionnaires. Beck Depression Inventory (BDI) assessed depressive symptoms, Life Orientation Test (LOT-R) assessed optimism, ENRICHD Social Support Inventory (ESSI) and Perceived Social Support Scale (PSSS) assessed social support, and COPE assessed coping styles. Linear regression analyses were employed to assess the association of coping styles with continuous BDI scores. Logistic regression analyses were performed using BDI scores dichotomized into BDI<10 versus BDI≥10, to identify coping styles accompanying clinically significant depressive symptoms. Results In linear regression models, higher BDI scores were associated with lower scores on the acceptance (β=-.14), humor (β=-.15), planning (β=-.15), and emotional support (β=-.14) subscales of the COPE, and higher scores on the behavioral disengagement (β=.41), denial (β=.33), venting (β=.25), and mental disengagement (β=.22) subscales. Higher PSSS and ESSI scores were associated with lower BDI scores (β=-.32 and -.25, respectively). Higher LOT-R scores were associated with higher BDI scores (β=.39, p<.001). In logistical regression models, BDI≥10 was associated with greater likelihood of behavioral disengagement (OR=1.3), denial (OR=1.2), mental disengagement (OR=1.3), venting (OR=1.2), and pessimism (OR=1.2), and lower perceived social support measured by PSSS (OR=.92) and ESSI (OR=.92). Conclusion Depressive symptoms in HF patients are associated with avoidant coping, lower perceived social support, and pessimism. Results raise the possibility that interventions designed to improve coping may reduce depressive symptoms. PMID:19773027

Only One Third of Tehran's Physicians are Familiar with 'Evidence-Based Clinical Guidelines'.

PubMed

Mounesan, Leila; Nedjat, Saharnaz; Majdzadeh, Reza; Rashidian, Arash; Gholami, Jaleh

2013-03-01

Clinical guidelines have increasingly been used as tools for applying new knowledge and research findings. Although, efforts have been made to produce clinical guidelines in Iran, it is not clear whether they have been used by physicians and what factors are associated with them?. Four hundred and forty three practicing physicians in Tehran were selected from private clinics through weighted random sampling. The data collection tool was a questionnaire on familiarity and attitude toward clinical guidelines. The descriptive and analytical findings were analyzed with t-tests, Chi(2), logistic and linear multivariate regression by SPSS, version 16. 31.8% of physicians were familiar with clinical guidelines. Based on the logistic regression model physicians' familiarity with clinical guidelines was positively and significantly associated with 'working experience in a health service delivery point' OR = 2.13 (95% CI, 1.17-3.90), 'familiarity with therapeutic protocols' OR = 2.09 (95% CI, 1.22-3.57) and 'holding a specialty degree' OR = 2.51 (95% CI, 1.24-5.07). The mean overall attitude scores in the 'usefulness', 'reliability', and 'problems and barriers' domains were, respectively, 78.9 (SD = 16.5), 78.9 (SD = 19.7) and 50.4 (SD = 15.9) out of a total of 100 scores in each domain. No significant association was observed between attitude domains and other independent variables using multivariate linear regression. Little familiarity with clinical guidelines may represent weakness in of production and distribution of domestic evidence. Although, physicians considered guidelines as useful and reliable tools, but problems such as difficult access to guidelines and lack of facilities to apply them were stated as well.

A Multiomics Approach to Identify Genes Associated with Childhood Asthma Risk and Morbidity.

PubMed

Forno, Erick; Wang, Ting; Yan, Qi; Brehm, John; Acosta-Perez, Edna; Colon-Semidey, Angel; Alvarez, Maria; Boutaoui, Nadia; Cloutier, Michelle M; Alcorn, John F; Canino, Glorisa; Chen, Wei; Celedón, Juan C

2017-10-01

Childhood asthma is a complex disease. In this study, we aim to identify genes associated with childhood asthma through a multiomics "vertical" approach that integrates multiple analytical steps using linear and logistic regression models. In a case-control study of childhood asthma in Puerto Ricans (n = 1,127), we used adjusted linear or logistic regression models to evaluate associations between several analytical steps of omics data, including genome-wide (GW) genotype data, GW methylation, GW expression profiling, cytokine levels, asthma-intermediate phenotypes, and asthma status. At each point, only the top genes/single-nucleotide polymorphisms/probes/cytokines were carried forward for subsequent analysis. In step 1, asthma modified the gene expression-protein level association for 1,645 genes; pathway analysis showed an enrichment of these genes in the cytokine signaling system (n = 269 genes). In steps 2-3, expression levels of 40 genes were associated with intermediate phenotypes (asthma onset age, forced expiratory volume in 1 second, exacerbations, eosinophil counts, and skin test reactivity); of those, methylation of seven genes was also associated with asthma. Of these seven candidate genes, IL5RA was also significant in analytical steps 4-8. We then measured plasma IL-5 receptor α levels, which were associated with asthma age of onset and moderate-severe exacerbations. In addition, in silico database analysis showed that several of our identified IL5RA single-nucleotide polymorphisms are associated with transcription factors related to asthma and atopy. This approach integrates several analytical steps and is able to identify biologically relevant asthma-related genes, such as IL5RA. It differs from other methods that rely on complex statistical models with various assumptions.

Excess adiposity, inflammation, and iron-deficiency in female adolescents.

PubMed

Tussing-Humphreys, Lisa M; Liang, Huifang; Nemeth, Elizabeta; Freels, Sally; Braunschweig, Carol A

2009-02-01

Iron deficiency is more prevalent in overweight children and adolescents but the mechanisms that underlie this condition remain unclear. The purpose of this cross-sectional study was to assess the relationship between iron status and excess adiposity, inflammation, menarche, diet, physical activity, and poverty status in female adolescents included in the National Health and Nutrition Examination Survey 2003-2004 dataset. Descriptive and simple comparative statistics (t test, chi(2)) were used to assess differences between normal-weight (5th < or = body mass index [BMI] percentile <85th) and heavier-weight girls (< or = 85th percentile for BMI) for demographic, biochemical, dietary, and physical activity variables. In addition, logistic regression analyses predicting iron deficiency and linear regression predicting serum iron levels were performed. Heavier-weight girls had an increased prevalence of iron deficiency compared to those with normal weight. Dietary iron, age of and time since first menarche, poverty status, and physical activity were similar between the two groups and were not independent predictors of iron deficiency or log serum iron levels. Logistic modeling predicting iron deficiency revealed having a BMI > or = 85th percentile and for each 1 mg/dL increase in C-reactive protein the odds ratio for iron deficiency more than doubled. The best-fit linear model to predict serum iron levels included both serum transferrin receptor and C-reactive protein following log-transformation for normalization of these variables. Findings indicate that heavier-weight female adolescents are at greater risk for iron deficiency and that inflammation stemming from excess adipose tissue contributes to this phenomenon. Food and nutrition professionals should consider elevated BMI as an additional risk factor for iron deficiency in female adolescents.

Speech prosody impairment predicts cognitive decline in Parkinson's disease.

PubMed

Rektorova, Irena; Mekyska, Jiri; Janousova, Eva; Kostalova, Milena; Eliasova, Ilona; Mrackova, Martina; Berankova, Dagmar; Necasova, Tereza; Smekal, Zdenek; Marecek, Radek

2016-08-01

Impairment of speech prosody is characteristic for Parkinson's disease (PD) and does not respond well to dopaminergic treatment. We assessed whether baseline acoustic parameters, alone or in combination with other predominantly non-dopaminergic symptoms may predict global cognitive decline as measured by the Addenbrooke's cognitive examination (ACE-R) and/or worsening of cognitive status as assessed by a detailed neuropsychological examination. Forty-four consecutive non-depressed PD patients underwent clinical and cognitive testing, and acoustic voice analysis at baseline and at the two-year follow-up. Influence of speech and other clinical parameters on worsening of the ACE-R and of the cognitive status was analyzed using linear and logistic regression. The cognitive status (classified as normal cognition, mild cognitive impairment and dementia) deteriorated in 25% of patients during the follow-up. The multivariate linear regression model consisted of the variation in range of the fundamental voice frequency (F0VR) and the REM Sleep Behavioral Disorder Screening Questionnaire (RBDSQ). These parameters explained 37.2% of the variability of the change in ACE-R. The most significant predictors in the univariate logistic regression were the speech index of rhythmicity (SPIR; p = 0.012), disease duration (p = 0.019), and the RBDSQ (p = 0.032). The multivariate regression analysis revealed that SPIR alone led to 73.2% accuracy in predicting a change in cognitive status. Combining SPIR with RBDSQ improved the prediction accuracy of SPIR alone by 7.3%. Impairment of speech prosody together with symptoms of RBD predicted rapid cognitive decline and worsening of PD cognitive status during a two-year period. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coping styles in heart failure patients with depressive symptoms.

PubMed

Trivedi, Ranak B; Blumenthal, James A; O'Connor, Christopher; Adams, Kirkwood; Hinderliter, Alan; Dupree, Carla; Johnson, Kristy; Sherwood, Andrew

2009-10-01

Elevated depressive symptoms have been linked to poorer prognosis in heart failure (HF) patients. Our objective was to identify coping styles associated with depressive symptoms in HF patients. A total of 222 stable HF patients (32.75% female, 45.4% non-Hispanic black) completed multiple questionnaires. Beck Depression Inventory (BDI) assessed depressive symptoms, Life Orientation Test (LOT-R) assessed optimism, ENRICHD Social Support Inventory (ESSI) and Perceived Social Support Scale (PSSS) assessed social support, and COPE assessed coping styles. Linear regression analyses were employed to assess the association of coping styles with continuous BDI scores. Logistic regression analyses were performed using BDI scores dichotomized into BDI<10 vs. BDI> or =10, to identify coping styles accompanying clinically significant depressive symptoms. In linear regression models, higher BDI scores were associated with lower scores on the acceptance (beta=-.14), humor (beta=-.15), planning (beta=-.15), and emotional support (beta=-.14) subscales of the COPE, and higher scores on the behavioral disengagement (beta=.41), denial (beta=.33), venting (beta=.25), and mental disengagement (beta=.22) subscales. Higher PSSS and ESSI scores were associated with lower BDI scores (beta=-.32 and -.25, respectively). Higher LOT-R scores were associated with higher BDI scores (beta=.39, P<.001). In logistical regression models, BDI> or =10 was associated with greater likelihood of behavioral disengagement (OR=1.3), denial (OR=1.2), mental disengagement (OR=1.3), venting (OR=1.2), and pessimism (OR=1.2), and lower perceived social support measured by PSSS (OR=.92) and ESSI (OR=.92). Depressive symptoms in HF patients are associated with avoidant coping, lower perceived social support, and pessimism. Results raise the possibility that interventions designed to improve coping may reduce depressive symptoms.

Physical function in older men with hyperkyphosis.

PubMed

Katzman, Wendy B; Harrison, Stephanie L; Fink, Howard A; Marshall, Lynn M; Orwoll, Eric; Barrett-Connor, Elizabeth; Cawthon, Peggy M; Kado, Deborah M

2015-05-01

Age-related hyperkyphosis has been associated with poor physical function and is a well-established predictor of adverse health outcomes in older women, but its impact on health in older men is less well understood. We conducted a cross-sectional study to evaluate the association of hyperkyphosis and physical function in 2,363 men, aged 71-98 (M = 79) from the Osteoporotic Fractures in Men Study. Kyphosis was measured using the Rancho Bernardo Study block method. Measurements of grip strength and lower extremity function, including gait speed over 6 m, narrow walk (measure of dynamic balance), repeated chair stands ability and time, and lower extremity power (Nottingham Power Rig) were included separately as primary outcomes. We investigated associations of kyphosis and each outcome in age-adjusted and multivariable linear or logistic regression models, controlling for age, clinic, education, race, bone mineral density, height, weight, diabetes, and physical activity. In multivariate linear regression, we observed a dose-related response of worse scores on each lower extremity physical function test as number of blocks increased, p for trend ≤.001. Using a cutoff of ≥4 blocks, 20% (N = 469) of men were characterized with hyperkyphosis. In multivariate logistic regression, men with hyperkyphosis had increased odds (range 1.5-1.8) of being in the worst quartile of performing lower extremity physical function tasks (p < .001 for each outcome). Kyphosis was not associated with grip strength in any multivariate analysis. Hyperkyphosis is associated with impaired lower extremity physical function in older men. Further studies are needed to determine the direction of causality. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Effect of feeding heat-treated colostrum on risk for infection with Mycobacterium avium ssp. paratuberculosis, milk production, and longevity in Holstein dairy cows.

PubMed

Godden, S M; Wells, S; Donahue, M; Stabel, J; Oakes, J M; Sreevatsan, S; Fetrow, J

2015-08-01

In summer 2007, a randomized controlled field trial was initiated on 6 large Midwest commercial dairy farms to investigate the effect of feeding heat-treated (HT) colostrum on transmission of Mycobacterium avium ssp. paratuberculosis (MAP) and on future milk production and longevity within the herd. On each farm, colostrum was collected daily from fresh cows, pooled, divided into 2 aliquots, and then 1 aliquot was heat-treated in a commercial batch pasteurizer at 60°C for 60min. A sample from each batch of colostrum was collected for PCR testing (MAP-positive vs. MAP-negative). Newborn heifer calves were removed from the dam within 30 to 60min of birth and systematically assigned to be fed 3.8 L of either fresh (FR; n=434) or heat-treated (HT; n=490) colostrum within 2h of birth. After reaching adulthood (>2 yr old), study animals were tested once annually for 3 yr (2010, 2011, 2012) for infection with MAP using serum ELISA and fecal culture. Lactation records describing milk production data and death or culling events were collected during the 3-yr testing period. Multivariable model logistic and linear regression was used to investigate the effect of feeding HT colostrum on risk for testing positive to MAP during the 3-yr testing period (positive/negative; logistic regression) and on first and second lactation milk yield (kg/cow; linear regression), respectively. Cox proportional hazards regression was used to investigate the effect of feeding HT colostrum on risk and time to removal from the herd. Fifteen percent of all study animals were fed PCR-positive colostrum. By the end of the 3-yr testing period, no difference was noted in the proportion of animals testing positive for MAP, with either serum ELISA or fecal culture, when comparing the HT group (10.5%) versus the FR group (8.1%). There was no effect of treatment on first- (HT=11.797kg; FR=11,671kg) or second-lactation (HT=11,013kg; FR=11,235kg) milk production. The proportion of cows leaving the herd by study conclusion was not different for animals originally fed HT (68.0%) versus FR (71.7%) colostrum. Although a previous study showed that feeding HT colostrum (60°C for 60min) produces short-term benefits, including improved passive transfer of IgG and reduced morbidity in the preweaning period, the current study found no benefit of feeding HT colostrum on long-term outcomes including risk for transmission of Mycobacterium avium ssp. paratuberculosis, milk production in the first and second lactation, and longevity within the herd. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Applications of statistics to medical science, III. Correlation and regression.

PubMed

Watanabe, Hiroshi

2012-01-01

In this third part of a series surveying medical statistics, the concepts of correlation and regression are reviewed. In particular, methods of linear regression and logistic regression are discussed. Arguments related to survival analysis will be made in a subsequent paper.

Prevalence of dry eye syndrome after a three-year exposure to a clean room.

PubMed

Cho, Hyun A; Cheon, Jae Jung; Lee, Jong Seok; Kim, Soo Young; Chang, Seong Sil

2014-01-01

To measure the prevalence of dry eye syndrome (DES) among clean room (relative humidity ≤1%) workers from 2011 to 2013. Three annual DES examinations were performed completely in 352 clean room workers aged 20-40 years who were working at a secondary battery factory. Each examination comprised the tear-film break-up test (TFBUT), Schirmer's test I, slit-lamp microscopic examination, and McMonnies questionnaire. DES grades were measured using the Delphi approach. The annual examination results were analyzed using a general linear model and post-hoc analysis with repeated-ANOVA (Tukey). Multiple logistic regression was performed using the examination results from 2013 (dependent variable) to analyze the effect of years spent working in the clean room (independent variable). The prevalence of DES among these workers was 14.8% in 2011, 27.1% in 2012, and 32.8% in 2013. The TFBUT and McMonnies questionnaire showed that DES grades worsened over time. Multiple logistic regression analysis indicated that the odds ratio for having dry eyes was 1.130 (95% CI 1.012-1.262) according to the findings of the McMonnies questionnaire. This 3-year trend suggests that the increased prevalence of DES was associated with longer working hours. To decrease the prevalence of DES, employees should be assigned reasonable working hours with shift assignments that include appropriate break times. Workers should also wear protective eyewear, subdivide their working process to minimize exposure, and utilize preservative-free eye drops.

A Comparison of the One-and Three-Parameter Logistic Models on Measures of Test Efficiency.

ERIC Educational Resources Information Center

Benson, Jeri

Two methods of item selection were used to select sets of 40 items from a 50-item verbal analogies test, and the resulting item sets were compared for relative efficiency. The BICAL program was used to select the 40 items having the best mean square fit to the one parameter logistic (Rasch) model. The LOGIST program was used to select the 40 items…

The South African English Smartphone Digits-in-Noise Hearing Test: Effect of Age, Hearing Loss, and Speaking Competence.

PubMed

Potgieter, Jenni-Marí; Swanepoel, De Wet; Myburgh, Hermanus Carel; Smits, Cas

2017-11-20

This study determined the effect of hearing loss and English-speaking competency on the South African English digits-in-noise hearing test to evaluate its suitability for use across native (N) and non-native (NN) speakers. A prospective cross-sectional cohort study of N and NN English adults with and without sensorineural hearing loss compared pure-tone air conduction thresholds to the speech reception threshold (SRT) recorded with the smartphone digits-in-noise hearing test. A rating scale was used for NN English listeners' self-reported competence in speaking English. This study consisted of 454 adult listeners (164 male, 290 female; range 16 to 90 years), of whom 337 listeners had a best ear four-frequency pure-tone average (4FPTA; 0.5, 1, 2, and 4 kHz) of ≤25 dB HL. A linear regression model identified three predictors of the digits-in-noise SRT, namely, 4FPTA, age, and self-reported English-speaking competence. The NN group with poor self-reported English-speaking competence (≤5/10) performed significantly (p < 0.01) poorer than the N and NN (≥6/10) groups on the digits-in-noise test. Screening characteristics of the test improved with separate cutoff values depending on English-speaking competence for the N and NN groups (≥6/10) and NN group alone (≤5/10). Logistic regression models, which include age in the analysis, showed a further improvement in sensitivity and specificity for both groups (area under the receiver operating characteristic curve, 0.962 and 0.903, respectively). Self-reported English-speaking competence had a significant influence on the SRT obtained with the smartphone digits-in-noise test. A logistic regression approach considering SRT, self-reported English-speaking competence, and age as predictors of best ear 4FPTA >25 dB HL showed that the test can be used as an accurate hearing screening tool for N and NN English speakers. The smartphone digits-in-noise test, therefore, allows testing in a multilingual population familiar with English digits using dynamic cutoff values that can be chosen according to self-reported English-speaking competence and age.

On the assessment of the added value of new predictive biomarkers.

PubMed

Chen, Weijie; Samuelson, Frank W; Gallas, Brandon D; Kang, Le; Sahiner, Berkman; Petrick, Nicholas

2013-07-29

The surge in biomarker development calls for research on statistical evaluation methodology to rigorously assess emerging biomarkers and classification models. Recently, several authors reported the puzzling observation that, in assessing the added value of new biomarkers to existing ones in a logistic regression model, statistical significance of new predictor variables does not necessarily translate into a statistically significant increase in the area under the ROC curve (AUC). Vickers et al. concluded that this inconsistency is because AUC "has vastly inferior statistical properties," i.e., it is extremely conservative. This statement is based on simulations that misuse the DeLong et al. method. Our purpose is to provide a fair comparison of the likelihood ratio (LR) test and the Wald test versus diagnostic accuracy (AUC) tests. We present a test to compare ideal AUCs of nested linear discriminant functions via an F test. We compare it with the LR test and the Wald test for the logistic regression model. The null hypotheses of these three tests are equivalent; however, the F test is an exact test whereas the LR test and the Wald test are asymptotic tests. Our simulation shows that the F test has the nominal type I error even with a small sample size. Our results also indicate that the LR test and the Wald test have inflated type I errors when the sample size is small, while the type I error converges to the nominal value asymptotically with increasing sample size as expected. We further show that the DeLong et al. method tests a different hypothesis and has the nominal type I error when it is used within its designed scope. Finally, we summarize the pros and cons of all four methods we consider in this paper. We show that there is nothing inherently less powerful or disagreeable about ROC analysis for showing the usefulness of new biomarkers or characterizing the performance of classification models. Each statistical method for assessing biomarkers and classification models has its own strengths and weaknesses. Investigators need to choose methods based on the assessment purpose, the biomarker development phase at which the assessment is being performed, the available patient data, and the validity of assumptions behind the methodologies.

Acculturation dimensions and 12-month mood and anxiety disorders across US Latino subgroups in the National Epidemiologic Survey of Alcohol and Related Conditions.

PubMed

Fernández, R Lewis; Morcillo, C; Wang, S; Duarte, C S; Aggarwal, N K; Sánchez-Lacay, J A; Blanco, C

2016-07-01

Individual-level measures of acculturation (e.g. age of immigration) have a complex relationship with psychiatric disorders. Fine-grained analyses that tap various acculturation dimensions and population subgroups are needed to generate hypotheses regarding the mechanisms of action for the association between acculturation and mental health. Study participants were US Latinos (N = 6359) from Wave 2 of the 2004-2005 National Epidemiologic Survey of Alcohol and Related Conditions (N = 34 653). We used linear χ2 tests and logistic regression models to analyze the association between five acculturation dimensions and presence of 12-month DSM-IV mood/anxiety disorders across Latino subgroups (Mexican, Puerto Rican, Cuban, 'Other Latinos'). Acculturation dimensions associated linearly with past-year presence of mood/anxiety disorders among Mexicans were: (1) younger age of immigration (linear χ2 1 = 11.04, p < 0.001), (2) longer time in the United States (linear χ2 1 = 10.52, p < 0.01), (3) greater English-language orientation (linear χ2 1 = 14.57, p < 0.001), (4) lower Latino composition of social network (linear χ2 1 = 15.03, p < 0.001), and (5) lower Latino ethnic identification (linear χ2 1 = 7.29, p < 0.01). However, the associations were less consistent among Cubans and Other Latinos, and no associations with acculturation were found among Puerto Ricans. The relationship between different acculturation dimensions and 12-month mood/anxiety disorder varies across ethnic subgroups characterized by cultural and historical differences. The association between acculturation measures and disorder may depend on the extent to which they index protective or pathogenic adaptation pathways (e.g. loss of family support) across population subgroups preceding and/or following immigration. Future research should incorporate direct measures of maladaptive pathways and their relationship to various acculturation dimensions.

Acculturation dimensions and 12-month mood and anxiety disorders across US Latino subgroups in the National Epidemiologic Survey of Alcohol and Related Conditions

PubMed Central

Wang, S.; Duarte, C. S.; Aggarwal, N. K.; Sánchez-Lacay, J. A.; Blanco, C.

2016-01-01

Background Individual-level measures of acculturation (e.g. age of immigration) have a complex relationship with psychiatric disorders. Fine-grained analyses that tap various acculturation dimensions and population subgroups are needed to generate hypotheses regarding the mechanisms of action for the association between acculturation and mental health. Method Study participants were US Latinos (N = 6359) from Wave 2 of the 2004–2005 National Epidemiologic Survey of Alcohol and Related Conditions (N = 34 653). We used linear χ2 tests and logistic regression models to analyze the association between five acculturation dimensions and presence of 12-month DSM-IV mood/anxiety disorders across Latino subgroups (Mexican, Puerto Rican, Cuban, ‘Other Latinos’). Results Acculturation dimensions associated linearly with past-year presence of mood/anxiety disorders among Mexicans were: (1) younger age of immigration (linear χ12=11.04, p < 0.001), (2) longer time in the United States (linear χ12=10.52, p < 0.01), (3) greater English-language orientation (linear χ12=14.57, p < 0.001), (4) lower Latino composition of social network (linear χ12=15.03, p < 0.001), and (5) lower Latino ethnic identification (linear χ12=7.29, p < 0.01). However, the associations were less consistent among Cubans and Other Latinos, and no associations with acculturation were found among Puerto Ricans. Conclusions The relationship between different acculturation dimensions and 12-month mood/anxiety disorder varies across ethnic subgroups characterized by cultural and historical differences. The association between acculturation measures and disorder may depend on the extent to which they index protective or pathogenic adaptation pathways (e.g. loss of family support) across population subgroups preceding and/or following immigration. Future research should incorporate direct measures of maladaptive pathways and their relationship to various acculturation dimensions. PMID:27087570

The association of serum prolactin concentration with inflammatory biomarkers - cross-sectional findings from the population-based Study of Health in Pomerania.

PubMed

Friedrich, Nele; Schneider, Harald J; Spielhagen, Christin; Markus, Marcello Ricardo Paulista; Haring, Robin; Grabe, Hans J; Buchfelder, Michael; Wallaschofski, Henri; Nauck, Matthias

2011-10-01

Prolactin (PRL) is involved in immune regulation and may contribute to an atherogenic phenotype. Previous results on the association of PRL with inflammatory biomarkers have been conflicting and limited by small patient studies. Therefore, we used data from a large population-based sample to assess the cross-sectional associations between serum PRL concentration and high-sensitivity C-reactive protein (hsCRP), fibrinogen, interleukin-6 (IL-6), and white blood cell (WBC) count. From the population-based Study of Health in Pomerania (SHIP), a total of 3744 subjects were available for the present analyses. PRL and inflammatory biomarkers were measured. Linear and logistic regression models adjusted for age, sex, body-mass-index, total cholesterol and glucose were analysed. Multivariable linear regression models revealed a positive association of PRL with WBC. Multivariable logistic regression analyses showed a significant association of PRL with increased IL-6 in non-smokers [highest vs lowest quintile: odds ratio 1·69 (95% confidence interval 1·10-2·58), P = 0·02] and smokers [OR 2·06 (95%-CI 1·10-3·89), P = 0·02]. Similar results were found for WBC in non-smokers [highest vs lowest quintile: OR 2·09 (95%-CI 1·21-3·61), P = 0·01)] but not in smokers. Linear and logistic regression analyses revealed no significant associations of PRL with hsCRP or fibrinogen. Serum PRL concentrations are associated with inflammatory biomarkers including IL-6 and WBC, but not hsCRP or fibrinogen. The suggested role of PRL in inflammation needs further investigation in future prospective studies. © 2011 Blackwell Publishing Ltd.

An integrated conceptual framework for selecting reverse logistics providers in the presence of vagueness

NASA Astrophysics Data System (ADS)

Fırdolaş, Tugba; Önüt, Semih; Kongar, Elif

2005-11-01

In recent years, relating organization's attitude towards sustainable development, environmental management is gaining an increasing interest among researchers in supply chain management. With regard to a long term requirement of a shift from a linear economy towards a cycle economy, businesses should be motivated to embrace change brought about by consumers, government, competition, and ethical responsibility. To achieve business goals and objectives, a company must reply to increasing consumer demand for "green" products and implement environmentally responsible plans. Reverse logistics is an activity within organizations delegated to the customer service function, where customers with warranted or defective products would return them to their supplier. Emergence of reverse logistics enables to provide a competitive advantage and significant return on investment with an indirect effect on profitability. Many organizations are hiring third-party providers to implement reverse logistics programs designed to retain value by getting products back. Reverse logistics vendors play an important role in helping organizations in closing the loop for products offered by the organizations. In this regard, the selection of third-party providers issue is increasingly becoming an area of reverse logistics concept and practice. This study aims to assist managers in determining which third-party logistics provider to collaborate in the reverse logistics process with an alternative approach based on an integrated model using neural networks and fuzzy logic. An illustrative case study is discussed and the best provider is identified through the solution of this model.

An IPSO-SVM algorithm for security state prediction of mine production logistics system

NASA Astrophysics Data System (ADS)

Zhang, Yanliang; Lei, Junhui; Ma, Qiuli; Chen, Xin; Bi, Runfang

2017-06-01

A theoretical basis for the regulation of corporate security warning and resources was provided in order to reveal the laws behind the security state in mine production logistics. Considering complex mine production logistics system and the variable is difficult to acquire, a superior security status predicting model of mine production logistics system based on the improved particle swarm optimization and support vector machine (IPSO-SVM) is proposed in this paper. Firstly, through the linear adjustments of inertia weight and learning weights, the convergence speed and search accuracy are enhanced with the aim to deal with situations associated with the changeable complexity and the data acquisition difficulty. The improved particle swarm optimization (IPSO) is then introduced to resolve the problem of parameter settings in traditional support vector machines (SVM). At the same time, security status index system is built to determine the classification standards of safety status. The feasibility and effectiveness of this method is finally verified using the experimental results.

A Note on Three Statistical Tests in the Logistic Regression DIF Procedure

ERIC Educational Resources Information Center

Paek, Insu

2012-01-01

Although logistic regression became one of the well-known methods in detecting differential item functioning (DIF), its three statistical tests, the Wald, likelihood ratio (LR), and score tests, which are readily available under the maximum likelihood, do not seem to be consistently distinguished in DIF literature. This paper provides a clarifying…

Protocol Analysis as a Tool in Function and Task Analysis

DTIC Science & Technology

1999-10-01

Autocontingency The use of log-linear and logistic regression methods to analyse sequential data seems appealing , and is strongly advocated by...collection and analysis of observational data. Behavior Research Methods, Instruments, and Computers, 23(3), 415-429. Patrick, J. D. (1991). Snob : A

Testing healthy immigrant effects among late life immigrants in the United States: using multiple indicators.

PubMed

Choi, Sunha H

2012-04-01

This study tested a healthy immigrant effect (HIE) and postimmigration health status changes among late life immigrants. Using three waves of the Second Longitudinal Study of Aging (1994-2000) and the linked mortality file through 2006, this study compared (a) chronic health conditions, (b) longitudinal trajectories of self-rated health, (c) longitudinal trajectories of functional impairments, and (d) mortality between three groups (age 70+): (i) late life immigrants with less than 15 years in the United States (n = 133), (ii) longer term immigrants (n = 672), and (iii) U.S.-born individuals (n = 8,642). Logistic and Poisson regression, hierarchical generalized linear modeling, and survival analyses were conducted. Late life immigrants were less likely to suffer from cancer, had lower numbers of chronic conditions at baseline, and displayed lower hazards of mortality during the 12-year follow-up. However, their self-rated health and functional status were worse than those of their counterparts over time. A HIE was only partially supported among older adults.

Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming-Based Approach.

PubMed

Duarte, Belmiro P M; Wong, Weng Kee

2015-08-01

This paper uses semidefinite programming (SDP) to construct Bayesian optimal design for nonlinear regression models. The setup here extends the formulation of the optimal designs problem as an SDP problem from linear to nonlinear models. Gaussian quadrature formulas (GQF) are used to compute the expectation in the Bayesian design criterion, such as D-, A- or E-optimality. As an illustrative example, we demonstrate the approach using the power-logistic model and compare results in the literature. Additionally, we investigate how the optimal design is impacted by different discretising schemes for the design space, different amounts of uncertainty in the parameter values, different choices of GQF and different prior distributions for the vector of model parameters, including normal priors with and without correlated components. Further applications to find Bayesian D-optimal designs with two regressors for a logistic model and a two-variable generalised linear model with a gamma distributed response are discussed, and some limitations of our approach are noted.

Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming-Based Approach

PubMed Central

Duarte, Belmiro P. M.; Wong, Weng Kee

2014-01-01

Summary This paper uses semidefinite programming (SDP) to construct Bayesian optimal design for nonlinear regression models. The setup here extends the formulation of the optimal designs problem as an SDP problem from linear to nonlinear models. Gaussian quadrature formulas (GQF) are used to compute the expectation in the Bayesian design criterion, such as D-, A- or E-optimality. As an illustrative example, we demonstrate the approach using the power-logistic model and compare results in the literature. Additionally, we investigate how the optimal design is impacted by different discretising schemes for the design space, different amounts of uncertainty in the parameter values, different choices of GQF and different prior distributions for the vector of model parameters, including normal priors with and without correlated components. Further applications to find Bayesian D-optimal designs with two regressors for a logistic model and a two-variable generalised linear model with a gamma distributed response are discussed, and some limitations of our approach are noted. PMID:26512159

LOGISTIC FUNCTION PROFILE FIT: A least-squares program for fitting interface profiles to an extended logistic function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirchhoff, William H.

2012-09-15

The extended logistic function provides a physically reasonable description of interfaces such as depth profiles or line scans of surface topological or compositional features. It describes these interfaces with the minimum number of parameters, namely, position, width, and asymmetry. Logistic Function Profile Fit (LFPF) is a robust, least-squares fitting program in which the nonlinear extended logistic function is linearized by a Taylor series expansion (equivalent to a Newton-Raphson approach) with no apparent introduction of bias in the analysis. The program provides reliable confidence limits for the parameters when systematic errors are minimal and provides a display of the residuals frommore » the fit for the detection of systematic errors. The program will aid researchers in applying ASTM E1636-10, 'Standard practice for analytically describing sputter-depth-profile and linescan-profile data by an extended logistic function,' and may also prove useful in applying ISO 18516: 2006, 'Surface chemical analysis-Auger electron spectroscopy and x-ray photoelectron spectroscopy-determination of lateral resolution.' Examples are given of LFPF fits to a secondary ion mass spectrometry depth profile, an Auger surface line scan, and synthetic data generated to exhibit known systematic errors for examining the significance of such errors to the extrapolation of partial profiles.« less

Performance and strategy comparisons of human listeners and logistic regression in discriminating underwater targets.

PubMed

Yang, Lixue; Chen, Kean

2015-11-01

To improve the design of underwater target recognition systems based on auditory perception, this study compared human listeners with automatic classifiers. Performances measures and strategies in three discrimination experiments, including discriminations between man-made and natural targets, between ships and submarines, and among three types of ships, were used. In the experiments, the subjects were asked to assign a score to each sound based on how confident they were about the category to which it belonged, and logistic regression, which represents linear discriminative models, also completed three similar tasks by utilizing many auditory features. The results indicated that the performances of logistic regression improved as the ratio between inter- and intra-class differences became larger, whereas the performances of the human subjects were limited by their unfamiliarity with the targets. Logistic regression performed better than the human subjects in all tasks but the discrimination between man-made and natural targets, and the strategies employed by excellent human subjects were similar to that of logistic regression. Logistic regression and several human subjects demonstrated similar performances when discriminating man-made and natural targets, but in this case, their strategies were not similar. An appropriate fusion of their strategies led to further improvement in recognition accuracy.

A computational approach to compare regression modelling strategies in prediction research.

PubMed

Pajouheshnia, Romin; Pestman, Wiebe R; Teerenstra, Steven; Groenwold, Rolf H H

2016-08-25

It is often unclear which approach to fit, assess and adjust a model will yield the most accurate prediction model. We present an extension of an approach for comparing modelling strategies in linear regression to the setting of logistic regression and demonstrate its application in clinical prediction research. A framework for comparing logistic regression modelling strategies by their likelihoods was formulated using a wrapper approach. Five different strategies for modelling, including simple shrinkage methods, were compared in four empirical data sets to illustrate the concept of a priori strategy comparison. Simulations were performed in both randomly generated data and empirical data to investigate the influence of data characteristics on strategy performance. We applied the comparison framework in a case study setting. Optimal strategies were selected based on the results of a priori comparisons in a clinical data set and the performance of models built according to each strategy was assessed using the Brier score and calibration plots. The performance of modelling strategies was highly dependent on the characteristics of the development data in both linear and logistic regression settings. A priori comparisons in four empirical data sets found that no strategy consistently outperformed the others. The percentage of times that a model adjustment strategy outperformed a logistic model ranged from 3.9 to 94.9 %, depending on the strategy and data set. However, in our case study setting the a priori selection of optimal methods did not result in detectable improvement in model performance when assessed in an external data set. The performance of prediction modelling strategies is a data-dependent process and can be highly variable between data sets within the same clinical domain. A priori strategy comparison can be used to determine an optimal logistic regression modelling strategy for a given data set before selecting a final modelling approach.

Explicit criteria for prioritization of cataract surgery

PubMed Central

Ma Quintana, José; Escobar, Antonio; Bilbao, Amaia

2006-01-01

Background Consensus techniques have been used previously to create explicit criteria to prioritize cataract extraction; however, the appropriateness of the intervention was not included explicitly in previous studies. We developed a prioritization tool for cataract extraction according to the RAND method. Methods Criteria were developed using a modified Delphi panel judgment process. A panel of 11 ophthalmologists was assembled. Ratings were analyzed regarding the level of agreement among panelists. We studied the effect of all variables on the final panel score using general linear and logistic regression models. Priority scoring systems were developed by means of optimal scaling and general linear models. The explicit criteria developed were summarized by means of regression tree analysis. Results Eight variables were considered to create the indications. Of the 310 indications that the panel evaluated, 22.6% were considered high priority, 52.3% intermediate priority, and 25.2% low priority. Agreement was reached for 31.9% of the indications and disagreement for 0.3%. Logistic regression and general linear models showed that the preoperative visual acuity of the cataractous eye, visual function, and anticipated visual acuity postoperatively were the most influential variables. Alternative and simple scoring systems were obtained by optimal scaling and general linear models where the previous variables were also the most important. The decision tree also shows the importance of the previous variables and the appropriateness of the intervention. Conclusion Our results showed acceptable validity as an evaluation and management tool for prioritizing cataract extraction. It also provides easy algorithms for use in clinical practice. PMID:16512893

Conservation of wildlife populations: factoring in incremental disturbance.

PubMed

Stewart, Abbie; Komers, Petr E

2017-06-01

Progressive anthropogenic disturbance can alter ecosystem organization potentially causing shifts from one stable state to another. This potential for ecosystem shifts must be considered when establishing targets and objectives for conservation. We ask whether a predator-prey system response to incremental anthropogenic disturbance might shift along a disturbance gradient and, if it does, whether any disturbance thresholds are evident for this system. Development of linear corridors in forested areas increases wolf predation effectiveness, while high density of development provides a safe-haven for their prey. If wolves limit moose population growth, then wolves and moose should respond inversely to land cover disturbance. Using general linear model analysis, we test how the rate of change in moose ( Alces alces ) density and wolf ( Canis lupus ) harvest density are influenced by the rate of change in land cover and proportion of land cover disturbed within a 300,000 km 2 area in the boreal forest of Alberta, Canada. Using logistic regression, we test how the direction of change in moose density is influenced by measures of land cover change. In response to incremental land cover disturbance, moose declines occurred where <43% of land cover was disturbed; in such landscapes, there were high rates of increase in linear disturbance and wolf density increased. By contrast, moose increases occurred where >43% of land cover was disturbed and wolf density declined. Wolves and moose appeared to respond inversely to incremental disturbance with the balance between moose decline and wolf increase shifting at about 43% of land cover disturbed. Conservation decisions require quantification of disturbance rates and their relationships to predator-prey systems because ecosystem responses to anthropogenic disturbance shift across disturbance gradients.

Poor sleep quality predicts decreased cognitive function independently of chronic mountain sickness score in young soldiers with polycythemia stationed in Tibet.

PubMed

Kong, Fan-Yi; Li, Qiang; Liu, Shi-Xiang

2011-01-01

Little is known about the association between poor sleep and cognitive function in people with polycythemia at high altitude. The aim of this study was to survey the sleep quality of individuals with polycythemia at high altitude and determine its association with cognitive abilities. We surveyed 230 soldiers stationed in Tibet (all men; mean age 21-52±4.30 yr) at altitudes ranging from 3658 to 3996 m. All participants were given a blood tests for hemoglobin level and a questionnaire survey of cognitive function. Polycythemia was defined as excessive erythrocytosis (Hb≥21 g/dL in men or ≥19 g/dL in women). Poor sleepers were defined as having a global Pittsburgh Sleep Quality Index score (PSQI)>5. Cognitive abilities were determined by the Chinese revision of the Wechsler Adult Intelligence Scale and the Benton Visual Retention Test. Multiple linear regression analysis was used to determine the association between the PSQI and cognitive function. Logistic regression analysis was performed to determine the independent effect of sleep quality on cognitive function. The global PSQI score of enrolled participants was 8.14±3.79. Seventy-five (32.6%) soldiers were diagnosed with polycythemia. The proportion of poor sleepers was 1.45 times greater in those with polycythemia compared with those without polycythemia [95% (confidence interval) CI 1.82-2.56], and they had a statistically significant lower score for cognitive function. Multiple linear regression analysis showed that the global PSQI score was negatively associated with IQ (β=0.11, 95% CI -0.16 to -0.05) and digit symbol scores (β=0.66, 95% CI -0.86 to -0.44). Poor sleep quality was determined to be an independent predictor of impaired IQ [odds ratio (OR) 1.59, 95% CI 1.30-1.95] and digit symbol score (OR 1.18, 95% CI 1.07-1.31) in logistic regression analysis. The present study showed that for young soldiers with polycythemia at high altitude impaired subjective sleep quality was an independent predictor of decreased cognitive function, especially IQ and verbal short-term memory.

Positive Parenting Practices Associated with Subsequent Childhood Weight Change

ERIC Educational Resources Information Center

Avula, Rasmi; Gonzalez, Wendy; Shapiro, Cheri J.; Fram, Maryah S.; Beets, Michael W.; Jones, Sonya J.; Blake, Christine E.; Frongillo, Edward A.

2011-01-01

We aimed to identify positive parenting practices that set children on differential weight-trajectories. Parenting practices studied were cognitively stimulating activities, limit-setting, disciplinary practices, and parent warmth. Data from two U.S. national longitudinal data sets and linear and logistic regression were used to examine…

Biological Applications in the Mathematics Curriculum

ERIC Educational Resources Information Center

Marland, Eric; Palmer, Katrina M.; Salinas, Rene A.

2008-01-01

In this article we provide two detailed examples of how we incorporate biological examples into two mathematics courses: Linear Algebra and Ordinary Differential Equations. We use Leslie matrix models to demonstrate the biological properties of eigenvalues and eigenvectors. For Ordinary Differential Equations, we show how using a logistic growth…

Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

NASA Astrophysics Data System (ADS)

Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

2013-02-01

Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local parameter estimates for all the variables and an important reduction of the autocorrelation in the residuals of the GW linear model. Despite the fitting improvement of local models, GW regression, more than an alternative to "global" or traditional regression modelling, seems to be a valuable complement to explore the non-stationary relationships between the response variable and the explanatory variables. The synergy of global and local modelling provides insights into fire management and policy and helps further our understanding of the fire problem over large areas while at the same time recognizing its local character.

Understanding Child Stunting in India: A Comprehensive Analysis of Socio-Economic, Nutritional and Environmental Determinants Using Additive Quantile Regression

PubMed Central

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A.

2013-01-01

Background Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. Objective We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Design Using cross-sectional data for children aged 0–24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. Results At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Conclusions Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role. PMID:24223839

Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression.

PubMed

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A

2013-01-01

Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Using cross-sectional data for children aged 0-24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

PubMed

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

Comparative Research of Navy Voluntary Education at Operational Commands

DTIC Science & Technology

2017-03-01

return on investment, ROI, logistic regression, multivariate analysis, descriptive statistics, Markov, time-series, linear programming 15. NUMBER...21  B.  DESCRIPTIVE STATISTICS TABLES ...............................................25  C.  PRIVACY CONSIDERATIONS...THIS PAGE INTENTIONALLY LEFT BLANK xi LIST OF TABLES Table 1.  Variables and Descriptions . Adapted from NETC (2016). .......................21

Diversity and Educational Benefits: Moving Beyond Self-Reported Questionnaire Data

ERIC Educational Resources Information Center

Herzog, Serge

2007-01-01

Effects of ethnic/racial diversity among students and faculty on cognitive growth of undergraduate students are estimated via a series of hierarchical linear and multinomial logistic regression models. Using objective measures of compositional, curricular, and interactional diversity based on actuarial course enrollment records of over 6,000…

A Comparison of Strategies for Estimating Conditional DIF

ERIC Educational Resources Information Center

Moses, Tim; Miao, Jing; Dorans, Neil J.

2010-01-01

In this study, the accuracies of four strategies were compared for estimating conditional differential item functioning (DIF), including raw data, logistic regression, log-linear models, and kernel smoothing. Real data simulations were used to evaluate the estimation strategies across six items, DIF and No DIF situations, and four sample size…

Association of sleep disturbances with cognitive impairment and depression in maintenance memodialysis patients

USDA-ARS?s Scientific Manuscript database

There are few data on the relationship of sleep with measures of cognitive function and symptoms of depression in dialysis patients. We evaluated the relationship of sleep with cognitive function and symptoms of depression in 168 hemodialysis patients, using multivariable linear and logistic regress...

School Health Promotion Policies and Adolescent Risk Behaviors in Israel: A Multilevel Analysis

ERIC Educational Resources Information Center

Tesler, Riki; Harel-Fisch, Yossi; Baron-Epel, Orna

2016-01-01

Background: Health promotion policies targeting risk-taking behaviors are being implemented across schools in Israel. This study identified the most effective components of these policies influencing cigarette smoking and alcohol consumption among adolescents. Methods: Logistic hierarchical linear model (HLM) analysis of data for 5279 students in…

Relationship between acculturation, discrimination, and suicidal ideation and attempts among US Hispanics in the National Epidemiologic Survey of Alcohol and Related Conditions.

PubMed

Perez-Rodriguez, M Mercedes; Baca-Garcia, Enrique; Oquendo, Maria A; Wang, Shuai; Wall, Melanie M; Liu, Shang-Min; Blanco, Carlos

2014-04-01

Acculturation is the process by which immigrants acquire the culture of the dominant society. Little is known about the relationship between acculturation and suicidal ideation and attempts among US Hispanics. Our aim was to examine the impact of 5 acculturation measures (age at migration, time in the United States, social network composition, language, race/ethnic orientation) on suicidal ideation and attempts in the largest available nationally representative sample of US Hispanics. Study participants were US Hispanics (N = 6,359) from Wave 2 of the 2004-2005 National Epidemiologic Survey of Alcohol and Related Conditions (N = 34,653). We used linear χ(2) tests and logistic regression models to analyze the association between acculturation and risk of suicidal ideation and attempts. Factors associated with a linear increase in lifetime risk for suicidal ideation and attempts were (1) younger age at migration (linear χ(2)(1) = 57.15; P < .0001), (2) longer time in the United States (linear χ(2)(1)= 36.09; P < .0001), (3) higher degree of English-language orientation (linear χ(2)(1) = 74.08; P <.0001), (4) lower Hispanic composition of social network (linear χ(2)(1) = 36.34; P < .0001), and (5) lower Hispanic racial/ethnic identification (linear χ(2)(1) = 47.77; P <.0001). Higher levels of perceived discrimination were associated with higher lifetime risk for suicidal ideation (β = 0.051; P < .001) and attempts (β = 0.020; P = .003). There was a linear association between multiple dimensions of acculturation and lifetime suicidal ideation and attempts. Discrimination was also associated with lifetime risk for suicidal ideation and attempts. Our results highlight protective aspects of the traditional Hispanic culture, such as high social support, coping strategies, and moral objections to suicide, which are modifiable factors and potential targets for public health interventions aimed at decreasing suicide risk. Culturally sensitive mental health resources need to be made more available to decrease discrimination and stigma. © Copyright 2014 Physicians Postgraduate Press, Inc.

Association of antidiabetic medication use, cognitive decline, and risk of cognitive impairment in older people with type 2 diabetes: Results from the population-based Mayo Clinic Study of Aging.

PubMed

Wennberg, Alexandra M V; Hagen, Clinton E; Edwards, Kelly; Roberts, Rosebud O; Machulda, Mary M; Knopman, David S; Petersen, Ronald C; Mielke, Michelle M

2018-06-05

To determine the cross-sectional and longitudinal associations between diabetes treatment type and cognitive outcomes among type II diabetics. We examined the association between metformin use, as compared to other diabetic treatment (ie, insulin, other oral medications, and diet/exercise) and cognitive test performance and mild cognitive impairment (MCI) diagnosis among 508 cognitively unimpaired at baseline type II diabetics enrolled in the Mayo Clinic Study of Aging. We created propensity scores to adjust for treatment effects. We used multivariate linear and logistic regression models to investigate the cross-sectional association between treatment type and cognitive test z scores, respectively. Mixed effects models and competing risk regression models were used to determine the longitudinal association between treatment type and change in cognitive test z scores and risk of developing incident MCI. In linear regression analyses adjusted for age, sex, education, body mass index, APOE ε4, insulin treatment, medical comorbidities, number of medications, duration of diabetes, and propensity score, we did not observe an association between metformin use and cognitive test performance. Additionally, we did not observe an association between metformin use and cognitive test performance over time (median = 3.7-year follow-up). Metformin was associated with an increased risk of MCI (subhazard ratio (SHR) = 2.75; 95% CI = 1.64, 4.63, P < .001). Similarly, other oral medications (SHR = 1.96; 95% CI = 1.19, 3.25; P = .009) and insulin (SHR = 3.17; 95% CI = 1.27, 7.92; P = .014) use were also associated with risk of MCI diagnosis. These findings suggest that metformin use, as compared to management of diabetes with other treatments, is not associated with cognitive test performance. However, metformin was associated with incident MCI diagnosis. Copyright © 2018 John Wiley & Sons, Ltd.

Validation Test Report For The CRWMS Analysis and Logistics Visually Interactive Model Calvin Version 3.0, 10074-Vtr-3.0-00

DOE Office of Scientific and Technical Information (OSTI.GOV)

S. Gillespie

2000-07-27

This report describes the tests performed to validate the CRWMS ''Analysis and Logistics Visually Interactive'' Model (CALVIN) Version 3.0 (V3.0) computer code (STN: 10074-3.0-00). To validate the code, a series of test cases was developed in the CALVIN V3.0 Validation Test Plan (CRWMS M&O 1999a) that exercises the principal calculation models and options of CALVIN V3.0. Twenty-five test cases were developed: 18 logistics test cases and 7 cost test cases. These cases test the features of CALVIN in a sequential manner, so that the validation of each test case is used to demonstrate the accuracy of the input to subsequentmore » calculations. Where necessary, the test cases utilize reduced-size data tables to make the hand calculations used to verify the results more tractable, while still adequately testing the code's capabilities. Acceptance criteria, were established for the logistics and cost test cases in the Validation Test Plan (CRWMS M&O 1999a). The Logistics test cases were developed to test the following CALVIN calculation models: Spent nuclear fuel (SNF) and reactivity calculations; Options for altering reactor life; Adjustment of commercial SNF (CSNF) acceptance rates for fiscal year calculations and mid-year acceptance start; Fuel selection, transportation cask loading, and shipping to the Monitored Geologic Repository (MGR); Transportation cask shipping to and storage at an Interim Storage Facility (ISF); Reactor pool allocation options; and Disposal options at the MGR. Two types of cost test cases were developed: cases to validate the detailed transportation costs, and cases to validate the costs associated with the Civilian Radioactive Waste Management System (CRWMS) Management and Operating Contractor (M&O) and Regional Servicing Contractors (RSCs). For each test case, values calculated using Microsoft Excel 97 worksheets were compared to CALVIN V3.0 scenarios with the same input data and assumptions. All of the test case results compare with the CALVIN V3.0 results within the bounds of the acceptance criteria. Therefore, it is concluded that the CALVIN V3.0 calculation models and options tested in this report are validated.« less

Modelling a flows in supply chain with analytical models: Case of a chemical industry

NASA Astrophysics Data System (ADS)

Benhida, Khalid; Azougagh, Yassine; Elfezazi, Said

2016-02-01

This study is interested on the modelling of the logistics flows in a supply chain composed on a production sites and a logistics platform. The contribution of this research is to develop an analytical model (integrated linear programming model), based on a case study of a real company operating in the phosphate field, considering a various constraints in this supply chain to resolve the planning problems for a better decision-making. The objectives of this model is to determine and define the optimal quantities of different products to route, to and from the various entities in the supply chain studied.

Aided diagnosis methods of breast cancer based on machine learning

NASA Astrophysics Data System (ADS)

Zhao, Yue; Wang, Nian; Cui, Xiaoyu

2017-08-01

In the field of medicine, quickly and accurately determining whether the patient is malignant or benign is the key to treatment. In this paper, K-Nearest Neighbor, Linear Discriminant Analysis, Logistic Regression were applied to predict the classification of thyroid,Her-2,PR,ER,Ki67,metastasis and lymph nodes in breast cancer, in order to recognize the benign and malignant breast tumors and achieve the purpose of aided diagnosis of breast cancer. The results showed that the highest classification accuracy of LDA was 88.56%, while the classification effect of KNN and Logistic Regression were better than that of LDA, the best accuracy reached 96.30%.

Stochastic growth logistic model with aftereffect for batch fermentation process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah

2014-06-19

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

Stochastic growth logistic model with aftereffect for batch fermentation process

NASA Astrophysics Data System (ADS)

Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md

2014-06-01

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

Logistic growth for the Nuzi cuneiform tablets: Analyzing family networks in ancient Mesopotamia

NASA Astrophysics Data System (ADS)

Ueda, Sumie; Makino, Kumi; Itoh, Yoshiaki; Tsuchiya, Takashi

2015-03-01

We reconstruct the published year of each cuneiform tablet of the Nuzi society in ancient Mesopotamia. The tablets are on land transaction, marriage, loan, slavery contracts, etc. The number of tablets seems to increase by logistic growth. It may show the dynamics of concentration of lands or other properties into few powerful families in a period of about sixty years and most of them are in about thirty years. We reconstruct family trees and social networks of Nuzi and estimate the published years of cuneiform tablets consistently with the trees and networks, formulating least squares problems with linear inequality constraints.

Exploring associations between parental and peer variables, personal variables and physical activity among adolescents: a mediation analysis.

PubMed

Verloigne, Maïté; Veitch, Jenny; Carver, Alison; Salmon, Jo; Cardon, Greet; De Bourdeaudhuij, Ilse; Timperio, Anna

2014-09-18

This study aimed to investigate how parental and peer variables are associated with moderate- to-vigorous intensity physical activity (MVPA) on week- and weekend days among Australian adolescents (13-15 y), and whether perceived internal barriers (e.g. lack of time), external barriers (e.g. lack of others to be physically active with) and self-efficacy mediated these associations. Cross-sectional data were drawn from the Health, Eating and Play Study, conducted in Melbourne, Australia. Adolescents (mean age = 14.11 ± 0.59 years, 51% girls) and one of their parents completed a questionnaire and adolescents wore an ActiGraph accelerometer for a week (n = 134). Mediating effects of perceived barriers and self-efficacy were tested using MacKinnon's product-of-coefficients test based on multilevel linear regression analyses. Parental logistic support was positively related to MVPA on weekdays (τ = 0.035) and weekend days (τ = 0.078), peer interest (τ =0.036) was positively related to MVPA on weekdays, and parental control (τ = -0.056) and parental concern (τ = -0.180) were inversely related to MVPA on weekdays. Internal barriers significantly mediated the association between parental logistic support and MVPA on weekdays (42.9% proportion mediated). Self-efficacy and external barriers did not mediate any association. Interventions aiming to increase adolescents' MVPA should involve parents, as parental support may influence MVPA on weekdays by reducing adolescents' perceived internal barriers. Longitudinal and experimental research is needed to confirm these findings and to investigate other personal mediators.

Prevalence of Dry Eye Syndrome after a Three-Year Exposure to a Clean Room

PubMed Central

2014-01-01

Objective To measure the prevalence of dry eye syndrome (DES) among clean room (relative humidity ≤1%) workers from 2011 to 2013. Methods Three annual DES examinations were performed completely in 352 clean room workers aged 20–40 years who were working at a secondary battery factory. Each examination comprised the tear-film break-up test (TFBUT), Schirmer’s test I, slit-lamp microscopic examination, and McMonnies questionnaire. DES grades were measured using the Delphi approach. The annual examination results were analyzed using a general linear model and post-hoc analysis with repeated-ANOVA (Tukey). Multiple logistic regression was performed using the examination results from 2013 (dependent variable) to analyze the effect of years spent working in the clean room (independent variable). Results The prevalence of DES among these workers was 14.8% in 2011, 27.1% in 2012, and 32.8% in 2013. The TFBUT and McMonnies questionnaire showed that DES grades worsened over time. Multiple logistic regression analysis indicated that the odds ratio for having dry eyes was 1.130 (95% CI 1.012–1.262) according to the findings of the McMonnies questionnaire. Conclusions This 3-year trend suggests that the increased prevalence of DES was associated with longer working hours. To decrease the prevalence of DES, employees should be assigned reasonable working hours with shift assignments that include appropriate break times. Workers should also wear protective eyewear, subdivide their working process to minimize exposure, and utilize preservative-free eye drops. PMID:25339991

Remarkable experiences of the nuclear tests in residents near the Semipalatinsk nuclear test site: analysis based on the questionnaire surveys.

PubMed

Kawano, Noriyuki; Ohtaki, Megu

2006-02-01

The main objective of this paper is to identify salient experiences of those who were exposed to radiation by the nuclear tests at the Semipalatinsk Nuclear Tests Site (SNTS). In 2002, our research team of the Research Institute for Radiation Biology and Medicine, Hiroshima University, started to conduct some field research by means of a questionnaire survey. Through this, we expected to examine the health condition of the residents near the SNTS, identify their experiences from the nuclear tests, and understand the exposure path. This attempt at clarifying the reality of radiation exposure at Semipalatinsk through the use of a survey research method is the first of its kind. Among the responses to our survey, the present paper focuses mainly upon responses to the questions concerning the experiences of the nuclear tests. It deals mainly with direct experiences of nuclear tests of the residents characteristic to Semipalatinsk, including some new experiences hitherto unnoticed. The present paper touches upon their concrete direct experiences of flash, bomb blast, heat, rain and dust. We also discuss distinct experiences in Semipalatinsk such as evacuation, through the additional use of their testimonies. The data have been compared with the results obtained in a similar survey made in Hiroshima and Nagasaki. For the data analysis, a statistical method called logistic multiple linear regression analysis has been used.

Dynamic modeling and optimization for space logistics using time-expanded networks

NASA Astrophysics Data System (ADS)

Ho, Koki; de Weck, Olivier L.; Hoffman, Jeffrey A.; Shishko, Robert

2014-12-01

This research develops a dynamic logistics network formulation for lifecycle optimization of mission sequences as a system-level integrated method to find an optimal combination of technologies to be used at each stage of the campaign. This formulation can find the optimal transportation architecture considering its technology trades over time. The proposed methodologies are inspired by the ground logistics analysis techniques based on linear programming network optimization. Particularly, the time-expanded network and its extension are developed for dynamic space logistics network optimization trading the quality of the solution with the computational load. In this paper, the methodologies are applied to a human Mars exploration architecture design problem. The results reveal multiple dynamic system-level trades over time and give recommendation of the optimal strategy for the human Mars exploration architecture. The considered trades include those between In-Situ Resource Utilization (ISRU) and propulsion technologies as well as the orbit and depot location selections over time. This research serves as a precursor for eventual permanent settlement and colonization of other planets by humans and us becoming a multi-planet species.

Resolution of an uncertain closed-loop logistics model: an application to fuzzy linear programs with risk analysis.

PubMed

Wang, Hsiao-Fan; Hsu, Hsin-Wei

2010-11-01

With the urgency of global warming, green supply chain management, logistics in particular, has drawn the attention of researchers. Although there are closed-loop green logistics models in the literature, most of them do not consider the uncertain environment in general terms. In this study, a generalized model is proposed where the uncertainty is expressed by fuzzy numbers. An interval programming model is proposed by the defined means and mean square imprecision index obtained from the integrated information of all the level cuts of fuzzy numbers. The resolution for interval programming is based on the decision maker (DM)'s preference. The resulting solution provides useful information on the expected solutions under a confidence level containing a degree of risk. The results suggest that the more optimistic the DM is, the better is the resulting solution. However, a higher risk of violation of the resource constraints is also present. By defining this probable risk, a solution procedure was developed with numerical illustrations. This provides a DM trade-off mechanism between logistic cost and the risk. Copyright 2010 Elsevier Ltd. All rights reserved.

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

PubMed

Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

[Current situation of sleeping duration in Chinese Han students in 2010].

PubMed

Song, Yi; Zhang, Bing; Hu, Peijin; Ma, Jun

2014-07-01

To analyze the characteristics of sleep duration in Chinese primary and middle school students. The data was collected from 30 provinces (Autonomous regions, Municipalities) in 165 363 Han Primary school students above 4 grade, the junior and senior high school students who participated in 2010 National Physical Fitness and Health Surveillance by using stratified random cluster sampling method, and the questionnaire of sleep duration, insufficient sleep and commuting way from school was conducted at the same time.χ² test and χ² linear-by-linear test were used to analyze the difference between the different groups, and logistic regression was used to analyze the factors of insufficient sleep. Nationwide in 2010, 39.09% (64 646/165 363) of students reported they had more than 8 hours sleep duration per day, the prevalence was lower among urban (37.06% (30 767/83 027)) than rural (41.15% (33 879/82 336)) students (χ² = 290.53, P < 0.01), and higher among boys (40.25% (33 193/82 446)) than girls (37.94% (31 453/82 897)) (χ² = 92.51, P < 0.01). The prevalence of having more than 8 hours sleep duration per day in 9-12 years group, 13-15 years group and 16-18 years group was 70.24% (43 934/62 549), 31.31% (16 166/51 652) and 8.89% (546/51 162), respectively, and decreased with the age increasing (χ² linear-by-linear = 50 617.75, P < 0.01). The prevalence of insufficient sleep was 93.64% (154 838/165 363) in total students, the prevalence was higher among urban (94.94% (78 829/83 027)) than rural students (92.32% (76 009/82 336)) (χ² = 479.14, P < 0.01), and lower among boys (92.65% (76 408/82 466) than girls 94.61% (78 430/82 897) (χ² = 265.79, P < 0.01). The prevalence of insufficient sleep in 9-12 years group, 13-15 years group and 16-18 years group was 96.42% (60 310/62 549), 92.76% (47 912/51 562) and 91.11% (46 616/51 162), respectively. A multivariate logistic regression analysis (OR (95% CI)) revealed that the insufficient sleep was significantly associated with being urban (1.58 (1.51-1.65)), being girls (1.39 (1.34-1.45)), being 9-12 years group (2.77 (2.62-2.93)), living in the middle (1.19 (1.13-1.25)) or western (1.08 (1.03-1.13)) of China, and commuting from school by bicycle (1.21 (1.14-1.28)), bus/car (1.09 (1.03-1.15)), or in a boarding school (1.17 (1.10-1.24)). The sleep duration in Chinese school children is low, a sizeable proportion of school children sleep less than the recommended hours. The prevalence of insufficient sleep is high, and there are significant differences in different groups.

Hybrid Genetic Agorithms and Line Search Method for Industrial Production Planning with Non-Linear Fitness Function

NASA Astrophysics Data System (ADS)

Vasant, Pandian; Barsoum, Nader

2008-10-01

Many engineering, science, information technology and management optimization problems can be considered as non linear programming real world problems where the all or some of the parameters and variables involved are uncertain in nature. These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic. The main objective of this research paper is to solve non linear fuzzy optimization problem where the technological coefficient in the constraints involved are fuzzy numbers which was represented by logistic membership functions by using hybrid evolutionary optimization approach. To explore the applicability of the present study a numerical example is considered to determine the production planning for the decision variables and profit of the company.

In-space propellant logistics. Volume 4: Project planning data

NASA Technical Reports Server (NTRS)

1972-01-01

The prephase A conceptual project planning data as it pertains to the development of the selected logistics module configuration transported into earth orbit by the space shuttle orbiter. The data represents the test, implementation, and supporting research and technology requirements for attaining the propellant transfer operational capability for early 1985. The plan is based on a propellant module designed to support the space-based tug with cryogenic oxygen-hydrogen propellants. A logical sequence of activities that is required to define, design, develop, fabricate, test, launch, and flight test the propellant logistics module is described. Included are the facility and ground support equipment requirements. The schedule of activities are based on the evolution and relationship between the R and T, the development issues, and the resultant test program.

Sepsis mortality prediction with the Quotient Basis Kernel.

PubMed

Ribas Ripoll, Vicent J; Vellido, Alfredo; Romero, Enrique; Ruiz-Rodríguez, Juan Carlos

2014-05-01

This paper presents an algorithm to assess the risk of death in patients with sepsis. Sepsis is a common clinical syndrome in the intensive care unit (ICU) that can lead to severe sepsis, a severe state of septic shock or multi-organ failure. The proposed algorithm may be implemented as part of a clinical decision support system that can be used in combination with the scores deployed in the ICU to improve the accuracy, sensitivity and specificity of mortality prediction for patients with sepsis. In this paper, we used the Simplified Acute Physiology Score (SAPS) for ICU patients and the Sequential Organ Failure Assessment (SOFA) to build our kernels and algorithms. In the proposed method, we embed the available data in a suitable feature space and use algorithms based on linear algebra, geometry and statistics for inference. We present a simplified version of the Fisher kernel (practical Fisher kernel for multinomial distributions), as well as a novel kernel that we named the Quotient Basis Kernel (QBK). These kernels are used as the basis for mortality prediction using soft-margin support vector machines. The two new kernels presented are compared against other generative kernels based on the Jensen-Shannon metric (centred, exponential and inverse) and other widely used kernels (linear, polynomial and Gaussian). Clinical relevance is also evaluated by comparing these results with logistic regression and the standard clinical prediction method based on the initial SAPS score. As described in this paper, we tested the new methods via cross-validation with a cohort of 400 test patients. The results obtained using our methods compare favourably with those obtained using alternative kernels (80.18% accuracy for the QBK) and the standard clinical prediction method, which are based on the basal SAPS score or logistic regression (71.32% and 71.55%, respectively). The QBK presented a sensitivity and specificity of 79.34% and 83.24%, which outperformed the other kernels analysed, logistic regression and the standard clinical prediction method based on the basal SAPS score. Several scoring systems for patients with sepsis have been introduced and developed over the last 30 years. They allow for the assessment of the severity of disease and provide an estimate of in-hospital mortality. Physiology-based scoring systems are applied to critically ill patients and have a number of advantages over diagnosis-based systems. Severity score systems are often used to stratify critically ill patients for possible inclusion in clinical trials. In this paper, we present an effective algorithm that combines both scoring methodologies for the assessment of death in patients with sepsis that can be used to improve the sensitivity and specificity of the currently available methods. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of the application of an automated electronic milk analyzer for the enumeration of total bacteria in raw goat milk.

PubMed

Ramsahoi, L; Gao, A; Fabri, M; Odumeru, J A

2011-07-01

Automated electronic milk analyzers for rapid enumeration of total bacteria counts (TBC) are widely used for raw milk testing by many analytical laboratories worldwide. In Ontario, Canada, Bactoscan flow cytometry (BsnFC; Foss Electric, Hillerød, Denmark) is the official anchor method for TBC in raw cow milk. Penalties are levied at the BsnFC equivalent level of 50,000 cfu/mL, the standard plate count (SPC) regulatory limit. This study was conducted to assess the BsnFC for TBC in raw goat milk, to determine the mathematical relationship between the SPC and BsnFC methods, and to identify probable reasons for the difference in the SPC:BsnFC equivalents for goat and cow milks. Test procedures were conducted according to International Dairy Federation Bulletin guidelines. Approximately 115 farm bulk tank milk samples per month were tested for inhibitor residues, SPC, BsnFC, psychrotrophic bacteria count, composition (fat, protein, lactose, lactose and other solids, and freezing point), and somatic cell count from March 2009 to February 2010. Data analysis of the results for the samples tested indicated that the BsnFC method would be a good alternative to the SPC method, providing accurate and more precise results with a faster turnaround time. Although a linear regression model showed good correlation and prediction, tests for linearity indicated that the relationship was linear only beyond log 4.1 SPC. The logistic growth curve best modeled the relationship between the SPC and BsnFC for the entire sample population. The BsnFC equivalent to the SPC 50,000 cfu/mL regulatory limit was estimated to be 321,000 individual bacteria count (ibc)/mL. This estimate differs considerably from the BsnFC equivalent for cow milk (121,000 ibc/mL). Because of the low frequency of bulk tank milk pickups at goat farms, 78.5% of the samples had their oldest milking in the tank to be 6.5 to 9.0 d old when tested, compared with the cow milk samples, which had their oldest milking at 4 d old when tested. This may be one of the major factors contributing to the larger goat milk BsnFC equivalence. Correlations and interactions between various test results were also discussed to further understand differences between the 2 methods for goat and cow milks. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The influence of filtering and downsampling on the estimation of transfer entropy

PubMed Central

Florin, Esther; von Papen, Michael; Timmermann, Lars

2017-01-01

Transfer entropy (TE) provides a generalized and model-free framework to study Wiener-Granger causality between brain regions. Because of its nonparametric character, TE can infer directed information flow also from nonlinear systems. Despite its increasing number of applications in neuroscience, not much is known regarding the influence of common electrophysiological preprocessing on its estimation. We test the influence of filtering and downsampling on a recently proposed nearest neighborhood based TE estimator. Different filter settings and downsampling factors were tested in a simulation framework using a model with a linear coupling function and two nonlinear models with sigmoid and logistic coupling functions. For nonlinear coupling and progressively lower low-pass filter cut-off frequencies up to 72% false negative direct connections and up to 26% false positive connections were identified. In contrast, for the linear model, a monotonic increase was only observed for missed indirect connections (up to 86%). High-pass filtering (1 Hz, 2 Hz) had no impact on TE estimation. After low-pass filtering interaction delays were significantly underestimated. Downsampling the data by a factor greater than the assumed interaction delay erased most of the transmitted information and thus led to a very high percentage (67–100%) of false negative direct connections. Low-pass filtering increases the number of missed connections depending on the filters cut-off frequency. Downsampling should only be done if the sampling factor is smaller than the smallest assumed interaction delay of the analyzed network. PMID:29149201

Determinants of Anabolic-Androgenic Steroid Risk Perceptions in Youth Populations: A Multivariate Analysis

ERIC Educational Resources Information Center

Denham, Bryan E.

2009-01-01

Grounded conceptually in social cognitive theory, this research examines how personal, behavioral, and environmental factors are associated with risk perceptions of anabolic-androgenic steroids. Ordinal logistic regression and logit log-linear models applied to data gathered from high-school seniors (N = 2,160) in the 2005 Monitoring the Future…

Measuring the Impact of Inquiry-Based Learning on Outcomes and Student Satisfaction

ERIC Educational Resources Information Center

Zafra-Gómez, José Luis; Román-Martínez, Isabel; Gómez-Miranda, María Elena

2015-01-01

The aim of this study is to determine the impact of inquiry-based learning (IBL) on students' academic performance and to assess their satisfaction with the process. Linear and logistic regression analyses show that examination grades are positively related to attendance at classes and tutorials; moreover, there is a positive significant…

Fortran Programs for Weapon Systems Analysis

DTIC Science & Technology

1990-06-01

interested in ballistics and related work. The programs include skeletal combat models , a set of discrete-event timing routines, mathematical and...32 4.3 LinEqs: Solve Linear Equations Like a Textbook ........................................................................... 34...military applications as it is of computer science. This crisis occurs in all fields, including the modeling of logistics, mobility, ballistics, and combat

Comparison of IRT Likelihood Ratio Test and Logistic Regression DIF Detection Procedures

ERIC Educational Resources Information Center

Atar, Burcu; Kamata, Akihito

2011-01-01

The Type I error rates and the power of IRT likelihood ratio test and cumulative logit ordinal logistic regression procedures in detecting differential item functioning (DIF) for polytomously scored items were investigated in this Monte Carlo simulation study. For this purpose, 54 simulation conditions (combinations of 3 sample sizes, 2 sample…

Multiple balance tests improve the assessment of postural stability in subjects with Parkinson's disease

PubMed Central

Jacobs, J V; Horak, F B; Tran, V K; Nutt, J G

2006-01-01

Objectives Clinicians often base the implementation of therapies on the presence of postural instability in subjects with Parkinson's disease (PD). These decisions are frequently based on the pull test from the Unified Parkinson's Disease Rating Scale (UPDRS). We sought to determine whether combining the pull test, the one‐leg stance test, the functional reach test, and UPDRS items 27–29 (arise from chair, posture, and gait) predicts balance confidence and falling better than any test alone. Methods The study included 67 subjects with PD. Subjects performed the one‐leg stance test, the functional reach test, and the UPDRS motor exam. Subjects also responded to the Activities‐specific Balance Confidence (ABC) scale and reported how many times they fell during the previous year. Regression models determined the combination of tests that optimally predicted mean ABC scores or categorised fall frequency. Results When all tests were included in a stepwise linear regression, only gait (UPDRS item 29), the pull test (UPDRS item 30), and the one‐leg stance test, in combination, represented significant predictor variables for mean ABC scores (r2 = 0.51). A multinomial logistic regression model including the one‐leg stance test and gait represented the model with the fewest significant predictor variables that correctly identified the most subjects as fallers or non‐fallers (85% of subjects were correctly identified). Conclusions Multiple balance tests (including the one‐leg stance test, and the gait and pull test items of the UPDRS) that assess different types of postural stress provide an optimal assessment of postural stability in subjects with PD. PMID:16484639

Three methods to construct predictive models using logistic regression and likelihood ratios to facilitate adjustment for pretest probability give similar results.

PubMed

Chan, Siew Foong; Deeks, Jonathan J; Macaskill, Petra; Irwig, Les

2008-01-01

To compare three predictive models based on logistic regression to estimate adjusted likelihood ratios allowing for interdependency between diagnostic variables (tests). This study was a review of the theoretical basis, assumptions, and limitations of published models; and a statistical extension of methods and application to a case study of the diagnosis of obstructive airways disease based on history and clinical examination. Albert's method includes an offset term to estimate an adjusted likelihood ratio for combinations of tests. Spiegelhalter and Knill-Jones method uses the unadjusted likelihood ratio for each test as a predictor and computes shrinkage factors to allow for interdependence. Knottnerus' method differs from the other methods because it requires sequencing of tests, which limits its application to situations where there are few tests and substantial data. Although parameter estimates differed between the models, predicted "posttest" probabilities were generally similar. Construction of predictive models using logistic regression is preferred to the independence Bayes' approach when it is important to adjust for dependency of tests errors. Methods to estimate adjusted likelihood ratios from predictive models should be considered in preference to a standard logistic regression model to facilitate ease of interpretation and application. Albert's method provides the most straightforward approach.

Optimizing the US Navy’s Combat Logistics Force

DTIC Science & Technology

2008-01-01

Optimizing the US Navy’s Combat Logistics Force Gerald G. Brown, W. Matthew Carlyle Operations Research Department, Naval Postgraduate School...Wiley InterScience (www.interscience.wiley.com). Abstract: We study how changes to the composition and employment of the US Navy combat logistic force...evaluate new CLF ship designs, advise what number of ships in a new ship class would be needed, test concepts for forward at-sea logistics bases in lieu

Quantifying the potential impact of measurement error in an investigation of autism spectrum disorder (ASD).

PubMed

Heavner, Karyn; Newschaffer, Craig; Hertz-Picciotto, Irva; Bennett, Deborah; Burstyn, Igor

2014-05-01

The Early Autism Risk Longitudinal Investigation (EARLI), an ongoing study of a risk-enriched pregnancy cohort, examines genetic and environmental risk factors for autism spectrum disorders (ASDs). We simulated the potential effects of both measurement error (ME) in exposures and misclassification of ASD-related phenotype (assessed as Autism Observation Scale for Infants (AOSI) scores) on measures of association generated under this study design. We investigated the impact on the power to detect true associations with exposure and the false positive rate (FPR) for a non-causal correlate of exposure (X2, r=0.7) for continuous AOSI score (linear model) versus dichotomised AOSI (logistic regression) when the sample size (n), degree of ME in exposure, and strength of the expected (true) OR (eOR)) between exposure and AOSI varied. Exposure was a continuous variable in all linear models and dichotomised at one SD above the mean in logistic models. Simulations reveal complex patterns and suggest that: (1) There was attenuation of associations that increased with eOR and ME; (2) The FPR was considerable under many scenarios; and (3) The FPR has a complex dependence on the eOR, ME and model choice, but was greater for logistic models. The findings will stimulate work examining cost-effective strategies to reduce the impact of ME in realistic sample sizes and affirm the importance for EARLI of investment in biological samples that help precisely quantify a wide range of environmental exposures.

Improving power and robustness for detecting genetic association with extreme-value sampling design.

PubMed

Chen, Hua Yun; Li, Mingyao

2011-12-01

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus may lead to loss of power in detecting genetic association. An alternative approach to analyzing such data is to model the dose-response relationship by a linear regression model. However, parameter estimation from this model can be biased, which may lead to inflated type I errors. We propose a robust and efficient approach that takes into consideration of both the biased sampling design and the potential dose-response relationship. Extensive simulations demonstrate that the proposed method is more powerful than the traditional logistic regression analysis and is more robust than the linear regression analysis. We applied our method to the analysis of a candidate gene association study on high-density lipoprotein cholesterol (HDL-C) which includes study subjects with extremely high or low HDL-C levels. Using our method, we identified several SNPs showing a stronger evidence of association with HDL-C than the traditional case-control logistic regression analysis. Our results suggest that it is important to appropriately model the quantitative traits and to adjust for the biased sampling when dose-response relationship exists in extreme-value sampling designs. © 2011 Wiley Periodicals, Inc.

Influence of landscape-scale factors in limiting brook trout populations in Pennsylvania streams

USGS Publications Warehouse

Kocovsky, P.M.; Carline, R.F.

2006-01-01

Landscapes influence the capacity of streams to produce trout through their effect on water chemistry and other factors at the reach scale. Trout abundance also fluctuates over time; thus, to thoroughly understand how spatial factors at landscape scales affect trout populations, one must assess the changes in populations over time to provide a context for interpreting the importance of spatial factors. We used data from the Pennsylvania Fish and Boat Commission's fisheries management database to investigate spatial factors that affect the capacity of streams to support brook trout Salvelinus fontinalis and to provide models useful for their management. We assessed the relative importance of spatial and temporal variation by calculating variance components and comparing relative standard errors for spatial and temporal variation. We used binary logistic regression to predict the presence of harvestable-length brook trout and multiple linear regression to assess the mechanistic links between landscapes and trout populations and to predict population density. The variance in trout density among streams was equal to or greater than the temporal variation for several streams, indicating that differences among sites affect population density. Logistic regression models correctly predicted the absence of harvestable-length brook trout in 60% of validation samples. The r 2-value for the linear regression model predicting density was 0.3, indicating low predictive ability. Both logistic and linear regression models supported buffering capacity against acid episodes as an important mechanistic link between landscapes and trout populations. Although our models fail to predict trout densities precisely, their success at elucidating the mechanistic links between landscapes and trout populations, in concert with the importance of spatial variation, increases our understanding of factors affecting brook trout abundance and will help managers and private groups to protect and enhance populations of wild brook trout. ?? Copyright by the American Fisheries Society 2006.

Explaining Match Outcome During The Men’s Basketball Tournament at The Olympic Games

PubMed Central

Leicht, Anthony S.; Gómez, Miguel A.; Woods, Carl T.

2017-01-01

In preparation for the Olympics, there is a limited opportunity for coaches and athletes to interact regularly with team performance indicators providing important guidance to coaches for enhanced match success at the elite level. This study examined the relationship between match outcome and team performance indicators during men’s basketball tournaments at the Olympic Games. Twelve team performance indicators were collated from all men’s teams and matches during the basketball tournament of the 2004-2016 Olympic Games (n = 156). Linear and non-linear analyses examined the relationship between match outcome and team performance indicator characteristics; namely, binary logistic regression and a conditional interference (CI) classification tree. The most parsimonious logistic regression model retained ‘assists’, ‘defensive rebounds’, ‘field-goal percentage’, ‘fouls’, ‘fouls against’, ‘steals’ and ‘turnovers’ (delta AIC <0.01; Akaike weight = 0.28) with a classification accuracy of 85.5%. Conversely, four performance indicators were retained with the CI classification tree with an average classification accuracy of 81.4%. However, it was the combination of ‘field-goal percentage’ and ‘defensive rebounds’ that provided the greatest probability of winning (93.2%). Match outcome during the men’s basketball tournaments at the Olympic Games was identified by a unique combination of performance indicators. Despite the average model accuracy being marginally higher for the logistic regression analysis, the CI classification tree offered a greater practical utility for coaches through its resolution of non-linear phenomena to guide team success. Key points A unique combination of team performance indicators explained 93.2% of winning observations in men’s basketball at the Olympics. Monitoring of these team performance indicators may provide coaches with the capability to devise multiple game plans or strategies to enhance their likelihood of winning. Incorporation of machine learning techniques with team performance indicators may provide a valuable and strategic approach to explain patterns within multivariate datasets in sport science. PMID:29238245

Space shuttle program: Shuttle Avionics Integration Laboratory. Volume 7: Logistics management plan

NASA Technical Reports Server (NTRS)

1974-01-01

The logistics management plan for the shuttle avionics integration laboratory defines the organization, disciplines, and methodology for managing and controlling logistics support. Those elements requiring management include maintainability and reliability, maintenance planning, support and test equipment, supply support, transportation and handling, technical data, facilities, personnel and training, funding, and management data.

Logistic Achievement Test Scaling and Equating with Fixed versus Estimated Lower Asymptotes.

ERIC Educational Resources Information Center

Phillips, S. E.

This study compared the lower asymptotes estimated by the maximum likelihood procedures of the LOGIST computer program with those obtained via application of the Norton methodology. The study also compared the equating results from the three-parameter logistic model with those obtained from the equipercentile, Rasch, and conditional…

Logistical Consideration in Computer-Based Screening of Astronaut Applicants

NASA Technical Reports Server (NTRS)

Galarza, Laura

2000-01-01

This presentation reviews the logistical, ergonomic, and psychometric issues and data related to the development and operational use of a computer-based system for the psychological screening of astronaut applicants. The Behavioral Health and Performance Group (BHPG) at the Johnson Space Center upgraded its astronaut psychological screening and selection procedures for the 1999 astronaut applicants and subsequent astronaut selection cycles. The questionnaires, tests, and inventories were upgraded from a paper-and-pencil system to a computer-based system. Members of the BHPG and a computer programmer designed and developed needed interfaces (screens, buttons, etc.) and programs for the astronaut psychological assessment system. This intranet-based system included the user-friendly computer-based administration of tests, test scoring, generation of reports, the integration of test administration and test output to a single system, and a complete database for past, present, and future selection data. Upon completion of the system development phase, four beta and usability tests were conducted with the newly developed system. The first three tests included 1 to 3 participants each. The final system test was conducted with 23 participants tested simultaneously. Usability and ergonomic data were collected from the system (beta) test participants and from 1999 astronaut applicants who volunteered the information in exchange for anonymity. Beta and usability test data were analyzed to examine operational, ergonomic, programming, test administration and scoring issues related to computer-based testing. Results showed a preference for computer-based testing over paper-and -pencil procedures. The data also reflected specific ergonomic, usability, psychometric, and logistical concerns that should be taken into account in future selection cycles. Conclusion. Psychological, psychometric, human and logistical factors must be examined and considered carefully when developing and using a computer-based system for psychological screening and selection.

A comparison of item response models for accuracy and speed of item responses with applications to adaptive testing.

PubMed

van Rijn, Peter W; Ali, Usama S

2017-05-01

We compare three modelling frameworks for accuracy and speed of item responses in the context of adaptive testing. The first framework is based on modelling scores that result from a scoring rule that incorporates both accuracy and speed. The second framework is the hierarchical modelling approach developed by van der Linden (2007, Psychometrika, 72, 287) in which a regular item response model is specified for accuracy and a log-normal model for speed. The third framework is the diffusion framework in which the response is assumed to be the result of a Wiener process. Although the three frameworks differ in the relation between accuracy and speed, one commonality is that the marginal model for accuracy can be simplified to the two-parameter logistic model. We discuss both conditional and marginal estimation of model parameters. Models from all three frameworks were fitted to data from a mathematics and spelling test. Furthermore, we applied a linear and adaptive testing mode to the data off-line in order to determine differences between modelling frameworks. It was found that a model from the scoring rule framework outperformed a hierarchical model in terms of model-based reliability, but the results were mixed with respect to correlations with external measures. © 2017 The British Psychological Society.

Increasing body mass index z-score is continuously associated with complications of overweight in children, even in the healthy weight range.

PubMed

Bell, Lana M; Byrne, Sue; Thompson, Alisha; Ratnam, Nirubasini; Blair, Eve; Bulsara, Max; Jones, Timothy W; Davis, Elizabeth A

2007-02-01

Overweight/obesity in children is increasing. Incidence data for medical complications use arbitrary cutoff values for categories of overweight and obesity. Continuous relationships are seldom reported. The objective of this study is to report relationships of child body mass index (BMI) z-score as a continuous variable with the medical complications of overweight. This study is a part of the larger, prospective cohort Growth and Development Study. Children were recruited from the community through randomly selected primary schools. Overweight children seeking treatment were recruited through tertiary centers. Children aged 6-13 yr were community-recruited normal weight (n = 73), community-recruited overweight (n = 53), and overweight treatment-seeking (n = 51). Medical history, family history, and symptoms of complications of overweight were collected by interview, and physical examination was performed. Investigations included oral glucose tolerance tests, fasting lipids, and liver function tests. Adjusted regression was used to model each complication of obesity with age- and sex-specific child BMI z-scores entered as a continuous dependent variable. Adjusted logistic regression showed the proportion of children with musculoskeletal pain, obstructive sleep apnea symptoms, headaches, depression, anxiety, bullying, and acanthosis nigricans increased with child BMI z-score. Adjusted linear regression showed BMI z-score was significantly related to systolic and diastolic blood pressure, insulin during oral glucose tolerance test, total cholesterol, high-density lipoprotein, triglycerides, and alanine aminotransferase. Child's BMI z-score is independently related to complications of overweight and obesity in a linear or curvilinear fashion. Children's risks of most complications increase across the entire range of BMI values and are not defined by thresholds.

Community-based comprehensive intervention for people with schizophrenia in Guangzhou, China: Effects on clinical symptoms, social functioning, internalized stigma and discrimination.

PubMed

Li, Jie; Huang, Yuan-Guang; Ran, Mao-Sheng; Fan, Yu; Chen, Wen; Evans-Lacko, Sara; Thornicroft, Graham

2018-04-01

Comprehensive interventions including components of stigma and discrimination reduction in schizophrenia in low- and middle-income countries (LMICs) are lacking. We developed a community-based comprehensive intervention to evaluate its effects on clinical symptoms, social functioning, internalized stigma and discrimination among patients with schizophrenia. A randomized controlled trial including an intervention group (n = 169) and a control group (n = 158) was performed. The intervention group received comprehensive intervention (strategies against stigma and discrimination, psycho-education, social skills training and cognitive behavioral therapy) and the control group received face to face interview. Both lasted for nine months. Participants were measured at baseline, 6 months and 9 months using the Internalized Stigma of Mental Illness scale (ISMI), Discrimination and Stigma Scale (DISC-12), Global Assessment of Functioning (GAF), Schizophrenia Quality of Life Scale (SQLS), Self-Esteem Scale (SES), Brief Psychiatric Rating Scale (BPRS) and PANSS negative scale (PANSS-N). Insight and medication compliance were evaluated by senior psychiatrists. Data were analyzed by descriptive statistics, t-test, chi-square test or Fisher's exact test. Linear Mixed Models were used to show intervention effectiveness on scales. General Linear Mixed Models with multinomial logistic link function were used to assess the effectiveness on medication compliance and insight. We found a significant reduction on anticipated discrimination, BPRS and PANSS-N total scores, and an elevation on overcoming stigma and GAF in the intervention group after 9 months. These suggested the intervention may be effective in reducing anticipated discrimination, increasing skills overcoming stigma as well as improving clinical symptoms and social functioning in Chinese patients with schizophrenia. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Testing Gene-Gene Interactions in the Case-Parents Design

PubMed Central

Yu, Zhaoxia

2011-01-01

The case-parents design has been widely used to detect genetic associations as it can prevent spurious association that could occur in population-based designs. When examining the effect of an individual genetic locus on a disease, logistic regressions developed by conditioning on parental genotypes provide complete protection from spurious association caused by population stratification. However, when testing gene-gene interactions, it is unknown whether conditional logistic regressions are still robust. Here we evaluate the robustness and efficiency of several gene-gene interaction tests that are derived from conditional logistic regressions. We found that in the presence of SNP genotype correlation due to population stratification or linkage disequilibrium, tests with incorrectly specified main-genetic-effect models can lead to inflated type I error rates. We also found that a test with fully flexible main genetic effects always maintains correct test size and its robustness can be achieved with negligible sacrifice of its power. When testing gene-gene interactions is the focus, the test allowing fully flexible main effects is recommended to be used. PMID:21778736

Inequality in Disability in Bangladesh

PubMed Central

Tareque, Md. Ismail; Begum, Sharifa; Saito, Yasuhiko

2014-01-01

Objective To investigate inequality in disability in Bangladesh. Methods The study used both household level and individual level data from a large nationally representative data set, Bangladesh’s Household Income and Expenditure Survey - 2010. Principal component analysis was used to construct a wealth index based on household assets from household level data. Then, using data from 49,809 individuals aged 5 years and over, chi-square tests and logistic regression were performed to test the association between wealth level and disability. Findings Women and older people are significantly more likely to report having disabilities than men and younger people. For middle and rich families, respectively, there is a 14 percent lower likelihood of reporting disabilities than for poor families. Changes in the probability of having disabilities are linear with increasing wealth. In addition, the study identifies some significant factors affecting disability, namely, age, sex, education, marital status, and place of residence including divisional differences. Conclusion In Bangladesh, worse health among the poor argues for policies prioritizing this group while at the same time giving special attention to women and the elderly. PMID:25075513

Supplementing Menu Labeling With Calorie Recommendations to Test for Facilitation Effects

PubMed Central

Wisdom, Jessica; Wansink, Brian; Loewenstein, George

2013-01-01

Objectives. We examined the effect on food purchases of adding recommended calorie intake per day or per meal to the mandated calorie information posted on chain restaurant menus. Methods. Before and after New York City implemented calorie posting on chain restaurant menus in 2008, we provided daily, per-meal, or no calorie recommendations to randomized subsets of adult lunchtime customers (n = 1121) entering 2 McDonald’s restaurants, in Manhattan and Brooklyn, and collected receipts and survey responses as they exited. In linear and logistic regressions, with adjustment for gender, race, age, and day, we tested for simple differences in calories consumed and interactions between variables. Results. Posting calorie benchmarks had no direct impact, nor did it moderate the impact of calorie labels on food purchases. The recommendation appeared to promote a slight increase in calorie intake, attributable to increased purchases of higher-calorie entrées. Conclusions. These results do not support the introduction of calorie recommendations as a means of enhancing the impact of posted calorie information or reducing the contribution of restaurant dining to the obesity epidemic. PMID:23865657

Comparison of data mining techniques applied to fetal heart rate parameters for the early identification of IUGR fetuses.

PubMed

Magenes, G; Bellazzi, R; Malovini, A; Signorini, M G

2016-08-01

The onset of fetal pathologies can be screened during pregnancy by means of Fetal Heart Rate (FHR) monitoring and analysis. Noticeable advances in understanding FHR variations were obtained in the last twenty years, thanks to the introduction of quantitative indices extracted from the FHR signal. This study searches for discriminating Normal and Intra Uterine Growth Restricted (IUGR) fetuses by applying data mining techniques to FHR parameters, obtained from recordings in a population of 122 fetuses (61 healthy and 61 IUGRs), through standard CTG non-stress test. We computed N=12 indices (N=4 related to time domain FHR analysis, N=4 to frequency domain and N=4 to non-linear analysis) and normalized them with respect to the gestational week. We compared, through a 10-fold crossvalidation procedure, 15 data mining techniques in order to select the more reliable approach for identifying IUGR fetuses. The results of this comparison highlight that two techniques (Random Forest and Logistic Regression) show the best classification accuracy and that both outperform the best single parameter in terms of mean AUROC on the test sets.

Private traits and attributes are predictable from digital records of human behavior

PubMed Central

Kosinski, Michal; Stillwell, David; Graepel, Thore

2013-01-01

We show that easily accessible digital records of behavior, Facebook Likes, can be used to automatically and accurately predict a range of highly sensitive personal attributes including: sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender. The analysis presented is based on a dataset of over 58,000 volunteers who provided their Facebook Likes, detailed demographic profiles, and the results of several psychometric tests. The proposed model uses dimensionality reduction for preprocessing the Likes data, which are then entered into logistic/linear regression to predict individual psychodemographic profiles from Likes. The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases. For the personality trait “Openness,” prediction accuracy is close to the test–retest accuracy of a standard personality test. We give examples of associations between attributes and Likes and discuss implications for online personalization and privacy. PMID:23479631

Predicting space telerobotic operator training performance from human spatial ability assessment

NASA Astrophysics Data System (ADS)

Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

2013-11-01

Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

Analysis on a diffusive SIS epidemic model with logistic source

NASA Astrophysics Data System (ADS)

Li, Bo; Li, Huicong; Tong, Yachun

2017-08-01

In this paper, we are concerned with an SIS epidemic reaction-diffusion model with logistic source in spatially heterogeneous environment. We first discuss some basic properties of the parabolic system, including the uniform upper bound of solutions and global stability of the endemic equilibrium when spatial environment is homogeneous. Our primary focus is to determine the asymptotic profile of endemic equilibria (when exist) if the diffusion (migration) rate of the susceptible or infected population is small or large. Combined with the results of Li et al. (J Differ Equ 262:885-913, 2017) where the case of linear source is studied, our analysis suggests that varying total population enhances persistence of infectious disease.

Gender-Specific Trends in Educational Attainment and Self-Rated Health, 1972–2002

PubMed Central

Hill, Terrence D.; Needham, Belinda L.

2006-01-01

Objectives. We tested whether self-rated health has improved over time (1972–2002) for women and men. We also considered the degree to which historical gains in educational attainment help to explain any observed trends. Methods. Using 21 years of repeated cross-sectional data from the General Social Survey, we estimated a series of ordered logistic regression models predicting self-rated health. Results. Our results show that women’s health status has steadily improved over the 30-year period under study, and these improvements are largely explained by gains in educational attainment. We also found that the health trend for men is nonlinear, suggesting significant fluctuations in health status over time. Conclusions. Based on the linear health status trend and strong mediation pattern for women, and the nonlinear health status trend for men, women have benefited more than men, in terms of self-rated health, from increased educational attainment. PMID:16735623

On the design of henon and logistic map-based random number generator

NASA Astrophysics Data System (ADS)

Magfirawaty; Suryadi, M. T.; Ramli, Kalamullah

2017-10-01

The key sequence is one of the main elements in the cryptosystem. True Random Number Generators (TRNG) method is one of the approaches to generating the key sequence. The randomness source of the TRNG divided into three main groups, i.e. electrical noise based, jitter based and chaos based. The chaos based utilizes a non-linear dynamic system (continuous time or discrete time) as an entropy source. In this study, a new design of TRNG based on discrete time chaotic system is proposed, which is then simulated in LabVIEW. The principle of the design consists of combining 2D and 1D chaotic systems. A mathematical model is implemented for numerical simulations. We used comparator process as a harvester method to obtain the series of random bits. Without any post processing, the proposed design generated random bit sequence with high entropy value and passed all NIST 800.22 statistical tests.

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics

PubMed Central

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications. PMID:27806075

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics.

PubMed

Miguel-Hurtado, Oscar; Guest, Richard; Stevenage, Sarah V; Neil, Greg J; Black, Sue

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications.

A Multilevel Study of Students' Motivations of Studying Accounting: Implications for Employers

ERIC Educational Resources Information Center

Law, Philip; Yuen, Desmond

2012-01-01

Purpose: The purpose of this study is to examine the influence of factors affecting students' choice of accounting as a study major in Hong Kong. Design/methodology/approach: Multinomial logistic regression and Hierarchical Generalized Linear Modeling (HGLM) are used to analyze the survey data for the level one and level two data, which is the…

High Achievers from Low Socioeconomic Backgrounds: The Critical Role of Disciplinary Climate and Grit

ERIC Educational Resources Information Center

Huang, Haigen; Zhu, Hao

2017-01-01

The purpose of this study was to examine whether school disciplinary climate and grit predicted low socioeconomic status (SES) students being high achievers in mathematics and science with a representative sample of 15-year-old students in the United States. Our analysis, using a two-level logistic hierarchical linear model (HLM), indicated both…

Relationship between Type of Trauma Exposure and Posttraumatic Stress Disorder among Urban Children and Adolescents

ERIC Educational Resources Information Center

Luthra, Rohini; Abramovitz, Robert; Greenberg, Rick; Schoor, Alan; Newcorn, Jeffrey; Schmeidler, James; Levine, Paul; Nomura, Yoko; Chemtob, Claude M.

2009-01-01

This study examines the association between trauma exposure and posttraumatic stress disorder (PTSD) among 157 help-seeking children (aged 8-17). Structured clinical interviews are carried out, and linear and logistic regression analyses are conducted to examine the relationship between PTSD and type of trauma exposure controlling for age, gender,…

Barriers and benefits of a healthy diet in spain: comparison with other European member states.

PubMed

Holgado, B; de Irala-Estévez, J; Martínez-González, M A; Gibney, M; Kearney, J; Martínez, J A

2000-06-01

Our purpose was to identify the main barriers and benefits perceived by the European citizens in regard to following a healthy diet and to assess the differences in expected benefits and difficulties between Spain and the remaining countries of the European Union. A cross-sectional study in which quota-controlled, nationally representative samples of approximately 1000 adults from each country completed a questionnaire. The survey was carried out between October 1995 and February 1996 in the 15 member states of the European Union. Participants (aged 15 y and older) were selected and interviewed in their homes about their attitudes towards healthy diets. They were asked to select two options from a list of 22 potential barriers to achieve a healthy diet and the benefits derived from a healthy diet. The associations of the perceived benefits of barriers with the sociodemographic variables within Spain and the rest of the European Union were compared with the Pearson chi-squared test and the chi-squared linear trend test. Two multivariate logistic regression models were also fitted to assess the characteristics independently related to the selection of 'Resistance to change' among the main barriers and to the selection of 'Prevent disease/stay healthy' as the main perceived benefits. The barrier most frequently mentioned in Spain was 'Irregular work hours' (29.7%) in contrast with the rest of the European Union where 'Giving up foods that I like' was the barrier most often chosen (26.2%). In the multivariate logistic regression model studying resistance to change, Spaniards were less resistant to change than the rest of the European Union. The benefit more frequently mentioned across Europe was 'Prevent disease/stay healthy'. In the multivariate logistic regression model women, older individuals, and people with a higher educational level were more likely to choose this benefit. It is apparent that there are many barriers to achieve healthy eating, mostly lack of time. For this reason a higher availability of food in line with the nutrition guidelines could be helpful. The population could have a better knowledge of the benefits derived from a healthy diet.

EEG-based mild depressive detection using feature selection methods and classifiers.

PubMed

Li, Xiaowei; Hu, Bin; Sun, Shuting; Cai, Hanshu

2016-11-01

Depression has become a major health burden worldwide, and effectively detection of such disorder is a great challenge which requires latest technological tool, such as Electroencephalography (EEG). This EEG-based research seeks to find prominent frequency band and brain regions that are most related to mild depression, as well as an optimal combination of classification algorithms and feature selection methods which can be used in future mild depression detection. An experiment based on facial expression viewing task (Emo_block and Neu_block) was conducted, and EEG data of 37 university students were collected using a 128 channel HydroCel Geodesic Sensor Net (HCGSN). For discriminating mild depressive patients and normal controls, BayesNet (BN), Support Vector Machine (SVM), Logistic Regression (LR), k-nearest neighbor (KNN) and RandomForest (RF) classifiers were used. And BestFirst (BF), GreedyStepwise (GSW), GeneticSearch (GS), LinearForwordSelection (LFS) and RankSearch (RS) based on Correlation Features Selection (CFS) were applied for linear and non-linear EEG features selection. Independent Samples T-test with Bonferroni correction was used to find the significantly discriminant electrodes and features. Data mining results indicate that optimal performance is achieved using a combination of feature selection method GSW based on CFS and classifier KNN for beta frequency band. Accuracies achieved 92.00% and 98.00%, and AUC achieved 0.957 and 0.997, for Emo_block and Neu_block beta band data respectively. T-test results validate the effectiveness of selected features by search method GSW. Simplified EEG system with only FP1, FP2, F3, O2, T3 electrodes was also explored with linear features, which yielded accuracies of 91.70% and 96.00%, AUC of 0.952 and 0.972, for Emo_block and Neu_block respectively. Classification results obtained by GSW + KNN are encouraging and better than previously published results. In the spatial distribution of features, we find that left parietotemporal lobe in beta EEG frequency band has greater effect on mild depression detection. And fewer EEG channels (FP1, FP2, F3, O2 and T3) combined with linear features may be good candidates for usage in portable systems for mild depression detection. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley P.

2004-01-01

Propulsion ground test facilities face the daily challenges of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Due to budgetary and schedule constraints, NASA and industry customers are pushing to test more components, for less money, in a shorter period of time. As these new rocket engine component test programs are undertaken, the lack of technology maturity in the test articles, combined with pushing the test facilities capabilities to their limits, tends to lead to an increase in facility breakdowns and unsuccessful tests. Over the last five years Stennis Space Center's propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and broken numerous test facility and test article parts. While various initiatives have been implemented to provide better propulsion test techniques and improve the quality, reliability, and maintainability of goods and parts used in the propulsion test facilities, unexpected failures during testing still occur quite regularly due to the harsh environment in which the propulsion test facilities operate. Previous attempts at modeling the lifecycle of a propulsion component test project have met with little success. Each of the attempts suffered form incomplete or inconsistent data on which to base the models. By focusing on the actual test phase of the tests project rather than the formulation, design or construction phases of the test project, the quality and quantity of available data increases dramatically. A logistic regression model has been developed form the data collected over the last five years, allowing the probability of successfully completing a rocket propulsion component test to be calculated. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),..,X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure. Logistic regression has primarily been used in the fields of epidemiology and biomedical research, but lends itself to many other applications. As indicated the use of logistic regression is not new, however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from the models provide project managers with insight and confidence into the affectivity of rocket engine component ground test projects. The initial success in modeling rocket propulsion ground test projects clears the way for more complex models to be developed in this area.

Regression approaches in the test-negative study design for assessment of influenza vaccine effectiveness.

PubMed

Bond, H S; Sullivan, S G; Cowling, B J

2016-06-01

Influenza vaccination is the most practical means available for preventing influenza virus infection and is widely used in many countries. Because vaccine components and circulating strains frequently change, it is important to continually monitor vaccine effectiveness (VE). The test-negative design is frequently used to estimate VE. In this design, patients meeting the same clinical case definition are recruited and tested for influenza; those who test positive are the cases and those who test negative form the comparison group. When determining VE in these studies, the typical approach has been to use logistic regression, adjusting for potential confounders. Because vaccine coverage and influenza incidence change throughout the season, time is included among these confounders. While most studies use unconditional logistic regression, adjusting for time, an alternative approach is to use conditional logistic regression, matching on time. Here, we used simulation data to examine the potential for both regression approaches to permit accurate and robust estimates of VE. In situations where vaccine coverage changed during the influenza season, the conditional model and unconditional models adjusting for categorical week and using a spline function for week provided more accurate estimates. We illustrated the two approaches on data from a test-negative study of influenza VE against hospitalization in children in Hong Kong which resulted in the conditional logistic regression model providing the best fit to the data.

Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure–flow relation: The CARNet study

PubMed Central

Meel-van den Abeelen, Aisha S.S.; Simpson, David M.; Wang, Lotte J.Y.; Slump, Cornelis H.; Zhang, Rong; Tarumi, Takashi; Rickards, Caroline A.; Payne, Stephen; Mitsis, Georgios D.; Kostoglou, Kyriaki; Marmarelis, Vasilis; Shin, Dae; Tzeng, Yu-Chieh; Ainslie, Philip N.; Gommer, Erik; Müller, Martin; Dorado, Alexander C.; Smielewski, Peter; Yelicich, Bernardo; Puppo, Corina; Liu, Xiuyun; Czosnyka, Marek; Wang, Cheng-Yen; Novak, Vera; Panerai, Ronney B.; Claassen, Jurgen A.H.R.

2014-01-01

Transfer function analysis (TFA) is a frequently used method to assess dynamic cerebral autoregulation (CA) using spontaneous oscillations in blood pressure (BP) and cerebral blood flow velocity (CBFV). However, controversies and variations exist in how research groups utilise TFA, causing high variability in interpretation. The objective of this study was to evaluate between-centre variability in TFA outcome metrics. 15 centres analysed the same 70 BP and CBFV datasets from healthy subjects (n = 50 rest; n = 20 during hypercapnia); 10 additional datasets were computer-generated. Each centre used their in-house TFA methods; however, certain parameters were specified to reduce a priori between-centre variability. Hypercapnia was used to assess discriminatory performance and synthetic data to evaluate effects of parameter settings. Results were analysed using the Mann–Whitney test and logistic regression. A large non-homogeneous variation was found in TFA outcome metrics between the centres. Logistic regression demonstrated that 11 centres were able to distinguish between normal and impaired CA with an AUC > 0.85. Further analysis identified TFA settings that are associated with large variation in outcome measures. These results indicate the need for standardisation of TFA settings in order to reduce between-centre variability and to allow accurate comparison between studies. Suggestions on optimal signal processing methods are proposed. PMID:24725709

An Application of a Multidimensional Extension of the Two-Parameter Logistic Latent Trait Model.

ERIC Educational Resources Information Center

McKinley, Robert L.; Reckase, Mark D.

A latent trait model is described that is appropriate for use with tests that measure more than one dimension, and its application to both real and simulated test data is demonstrated. Procedures for estimating the parameters of the model are presented. The research objectives are to determine whether the two-parameter logistic model more…

Computerized Classification Testing under the One-Parameter Logistic Response Model with Ability-Based Guessing

ERIC Educational Resources Information Center

Wang, Wen-Chung; Huang, Sheng-Yun

2011-01-01

The one-parameter logistic model with ability-based guessing (1PL-AG) has been recently developed to account for effect of ability on guessing behavior in multiple-choice items. In this study, the authors developed algorithms for computerized classification testing under the 1PL-AG and conducted a series of simulations to evaluate their…

REECo activities and sample logistics in support of the Nevada Applied Ecology Group

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wireman, D.L.; Rosenberry, C.E. Jr.; White, M.G.

Activities and sample logistics of Reynolds Electrical and Engineering Co., Inc. (REECo), in support of the Nevada Applied Ecology Group (NAEG), are discussed in this summary report. Activities include the collection, preparation, and shipment of samples of soils, vegetation, and small animals collected at Pu-contaminated areas of the Nevada Test Site and Tonopah Test Range. (CH)

Challenges and models in supporting logistics system design for dedicated-biomass-based bioenergy industry.

PubMed

Zhu, Xiaoyan; Li, Xueping; Yao, Qingzhu; Chen, Yuerong

2011-01-01

This paper analyzed the uniqueness and challenges in designing the logistics system for dedicated biomass-to-bioenergy industry, which differs from the other industries, due to the unique features of dedicated biomass (e.g., switchgrass) including its low bulk density, restrictions on harvesting season and frequency, content variation with time and circumambient conditions, weather effects, scattered distribution over a wide geographical area, and so on. To design it, this paper proposed a mixed integer linear programming model. It covered from planting and harvesting switchgrass to delivering to a biorefinery and included the residue handling, concentrating on integrating strategic decisions on the supply chain design and tactical decisions on the annual operation schedules. The present numerical examples verified the model and demonstrated its use in practice. This paper showed that the operations of the logistics system were significantly different for harvesting and non-harvesting seasons, and that under the well-designed biomass logistics system, the mass production with a steady and sufficient supply of biomass can increase the unit profit of bioenergy. The analytical model and practical methodology proposed in this paper will help realize the commercial production in biomass-to-bioenergy industry. Copyright © 2010 Elsevier Ltd. All rights reserved.

Social complexity, modernity and suicide: an assessment of Durkheim's suicide from the perspective of a non-linear analysis of complex social systems.

PubMed

Condorelli, Rosalia

2016-01-01

Can we share even today the same vision of modernity which Durkheim left us by its suicide analysis? or can society 'surprise us'? The answer to these questions can be inspired by several studies which found that beginning the second half of the twentieth century suicides in western countries more industrialized and modernized do not increase in a constant, linear way as modernization and social fragmentation process increases, as well as Durkheim's theory seems to lead us to predict. Despite continued modernizing process, they found stabilizing or falling overall suicide rate trends. Therefore, a gradual process of adaptation to the stress of modernization associated to low social integration levels seems to be activated in modern society. Assuming this perspective, the paper highlights as this tendency may be understood in the light of the new concept of social systems as complex adaptive systems, systems which are able to adapt to environmental perturbations and generate as a whole surprising, emergent effects due to nonlinear interactions among their components. So, in the frame of Nonlinear Dynamical System Modeling, we formalize the logic of suicide decision-making process responsible for changes at aggregate level in suicide growth rates by a nonlinear differential equation structured in a logistic way, and in so doing we attempt to capture the mechanism underlying the change process in suicide growth rate and to test the hypothesis that system's dynamics exhibits a restrained increase process as expression of an adaptation process to the liquidity of social ties in modern society. In particular, a Nonlinear Logistic Map is applied to suicide data in a modern society such as the Italian one from 1875 to 2010. The analytic results, seeming to confirm the idea of the activation of an adaptation process to the liquidity of social ties, constitutes an opportunity for a more general reflection on the current configuration of modern society, by relating the Durkheimian Theory with the Halbwachs' Theory and most current visions of modernity such as the Baumanian one. Complexity completes the interpretative framework by rooting the generating mechanism of adaptation process in the precondition of a new General Theory of Systems making the non linearity property of social system's interactions and surprise the functioning and evolution rule of social systems.

Acculturation and healthy lifestyle habits among Hispanics in United States-Mexico border communities.

PubMed

Ghaddar, Suad; Brown, Cynthia J; Pagán, José A; Díaz, Violeta

2010-09-01

To explore the relationship between acculturation and healthy lifestyle habits in the largely Hispanic populations living in underserved communities in the United States of America along the U.S.-Mexico border. A cross-sectional study was conducted from April 2006 to June 2008 using survey data from the Alliance for a Healthy Border, a program designed to reduce health disparities in the U.S.-Mexico border region by funding nutrition and physical activity education programs at 12 federally qualified community health centers in Arizona, California, New Mexico, and Texas. The survey included questions on acculturation, diet, exercise, and demographic factors and was completed by 2,381 Alliance program participants, of whom 95.3% were Hispanic and 45.4% were under the U.S. poverty level for 2007. Chi-square (χ2) and Student's t tests were used for bivariate comparisons between acculturation and dietary and physical activity measures. Linear regression and binary logistic regression were used to control for factors associated with nutrition and exercise. Based on univariate tests and confirmed by regression analysis controlling for sociodemographic and health variables, less acculturated survey respondents reported a significantly higher frequency of fruit and vegetable consumption and healthier dietary habits than those who were more acculturated. Adjusted binary logistic regression confirmed that individuals with low language acculturation were less likely to engage in physical activity than those with moderate to high acculturation (odds ratio 0.75, 95% confidence interval 0.59-0.95). Findings confirmed an association between acculturation and healthy lifestyle habits and supported the hypothesis that acculturation in border community populations tends to decrease the practice of some healthy dietary habits while increasing exposure to and awareness of the importance of other healthy behaviors.

Health and Nutrition Literacy and Adherence to Treatment in Children, Adolescents, and Young Adults With Chronic Kidney Disease and Hypertension, North Carolina, 2015

PubMed Central

Ferris, Maria; Rak, Eniko

2016-01-01

Introduction Adherence to treatment and dietary restrictions is important for health outcomes of patients with chronic/end-stage kidney disease and hypertension. The relationship of adherence with nutritional and health literacy in children, adolescents, and young adults is not well understood. The current study examined the relationship of health literacy, nutrition knowledge, nutrition knowledge–behavior concordance, and medication adherence in a sample of children and young people with chronic/end-stage kidney disease and hypertension. Methods We enrolled 74 patients (aged 7–29 y) with a diagnosis of chronic/end-stage kidney disease and hypertension from the University of North Carolina Kidney Center. Participants completed instruments of nutrition literacy (Disease-Specific Nutrition Knowledge Test), health literacy (Newest Vital Sign), nutrition behavior (Nutrition Knowledge–Behavior Concordance Scale), and medication adherence (Morisky Medication Adherence Scale). Linear and binary logistic regressions were used to test the associations. Results In univariate comparisons, nutrition knowledge was significantly higher in people with adequate health literacy. Medication adherence was related to nutrition knowledge and nutrition knowledge–behavior concordance. Multivariate regression models demonstrated that knowledge of disease-specific nutrition restrictions did not significantly predict nutrition knowledge–behavior concordance scores. In logistic regression, knowledge of nutrition restrictions did not significantly predict medication adherence. Lastly, health literacy and nutrition knowledge–behavior concordance were significant predictors of medication adherence. Conclusion Nutrition knowledge and health literacy skills are positively associated. Nutrition knowledge, health literacy, and nutrition knowledge–behavior concordance are positively related to medication adherence. Future research should focus on additional factors that may predict disease-specific nutrition behavior (adherence to dietary restrictions) in children and young people with chronic conditions. PMID:27490366

Using artificial intelligence to predict the risk for posterior capsule opacification after phacoemulsification.

PubMed

Mohammadi, Seyed-Farzad; Sabbaghi, Mostafa; Z-Mehrjardi, Hadi; Hashemi, Hassan; Alizadeh, Somayeh; Majdi, Mercede; Taee, Farough

2012-03-01

To apply artificial intelligence models to predict the occurrence of posterior capsule opacification (PCO) after phacoemulsification. Farabi Eye Hospital, Tehran, Iran. Clinical-based cross-sectional study. The posterior capsule status of eyes operated on for age-related cataract and the need for laser capsulotomy were determined. After a literature review, data polishing, and expert consultation, 10 input variables were selected. The QUEST algorithm was used to develop a decision tree. Three back-propagation artificial neural networks were constructed with 4, 20, and 40 neurons in 2 hidden layers and trained with the same transfer functions (log-sigmoid and linear transfer) and training protocol with randomly selected eyes. They were then tested on the remaining eyes and the networks compared for their performance. Performance indices were used to compare resultant models with the results of logistic regression analysis. The models were trained using 282 randomly selected eyes and then tested using 70 eyes. Laser capsulotomy for clinically significant PCO was indicated or had been performed 2 years postoperatively in 40 eyes. A sample decision tree was produced with accuracy of 50% (likelihood ratio 0.8). The best artificial neural network, which showed 87% accuracy and a positive likelihood ratio of 8, was achieved with 40 neurons. The area under the receiver-operating-characteristic curve was 0.71. In comparison, logistic regression reached accuracy of 80%; however, the likelihood ratio was not measurable because the sensitivity was zero. A prototype artificial neural network was developed that predicted posterior capsule status (requiring capsulotomy) with reasonable accuracy. No author has a financial or proprietary interest in any material or method mentioned. Copyright © 2012 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

A secure distributed logistic regression protocol for the detection of rare adverse drug events

PubMed Central

El Emam, Khaled; Samet, Saeed; Arbuckle, Luk; Tamblyn, Robyn; Earle, Craig; Kantarcioglu, Murat

2013-01-01

Background There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant privacy concerns that would need to be addressed. Existing protocols for addressing these concerns can result in reduced analysis accuracy and can allow sensitive information to leak. Objective To develop a secure distributed multi-party computation protocol for logistic regression that provides strong privacy guarantees. Methods We developed a secure distributed logistic regression protocol using a single analysis center with multiple sites providing data. A theoretical security analysis demonstrates that the protocol is robust to plausible collusion attacks and does not allow the parties to gain new information from the data that are exchanged among them. The computational performance and accuracy of the protocol were evaluated on simulated datasets. Results The computational performance scales linearly as the dataset sizes increase. The addition of sites results in an exponential growth in computation time. However, for up to five sites, the time is still short and would not affect practical applications. The model parameters are the same as the results on pooled raw data analyzed in SAS, demonstrating high model accuracy. Conclusion The proposed protocol and prototype system would allow the development of logistic regression models in a secure manner without requiring the sharing of personal health information. This can alleviate one of the key barriers to the establishment of large-scale post-marketing surveillance programs. We extended the secure protocol to account for correlations among patients within sites through generalized estimating equations, and to accommodate other link functions by extending it to generalized linear models. PMID:22871397

A secure distributed logistic regression protocol for the detection of rare adverse drug events.

PubMed

El Emam, Khaled; Samet, Saeed; Arbuckle, Luk; Tamblyn, Robyn; Earle, Craig; Kantarcioglu, Murat

2013-05-01

There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant privacy concerns that would need to be addressed. Existing protocols for addressing these concerns can result in reduced analysis accuracy and can allow sensitive information to leak. To develop a secure distributed multi-party computation protocol for logistic regression that provides strong privacy guarantees. We developed a secure distributed logistic regression protocol using a single analysis center with multiple sites providing data. A theoretical security analysis demonstrates that the protocol is robust to plausible collusion attacks and does not allow the parties to gain new information from the data that are exchanged among them. The computational performance and accuracy of the protocol were evaluated on simulated datasets. The computational performance scales linearly as the dataset sizes increase. The addition of sites results in an exponential growth in computation time. However, for up to five sites, the time is still short and would not affect practical applications. The model parameters are the same as the results on pooled raw data analyzed in SAS, demonstrating high model accuracy. The proposed protocol and prototype system would allow the development of logistic regression models in a secure manner without requiring the sharing of personal health information. This can alleviate one of the key barriers to the establishment of large-scale post-marketing surveillance programs. We extended the secure protocol to account for correlations among patients within sites through generalized estimating equations, and to accommodate other link functions by extending it to generalized linear models.

BRCA1/2 Test Results Impact Risk Management Attitudes, Intentions and Uptake

PubMed Central

O’Neill, Suzanne C.; Valdimarsdottir, Heiddis B.; DeMarco, Tiffani A.; Peshkin, Beth N.; Graves, Kristi D.; Brown, Karen; Hurley, Karen E.; Isaacs, Claudine; Hecker, Sharon; Schwartz, Marc D.

2011-01-01

BACKGROUND Women who receive positive or uninformative BRCA1/2 test results face a number of decisions about how to manage their cancer risk. The purpose of this study was to prospectively examine the effect of receiving a positive vs. uninformative BRCA1/2 genetic test result on the perceived pros and cons of risk-reducing mastectomy (RRM) and risk-reducing oophorectomy (RRO) and breast cancer screening. We further examined how perceived pros and cons of surgery predict intention for and uptake of surgery. METHODS 308 women (146 positive, 162 uninformative) were included in RRM and breast cancer screening analyses. 276 women were included in RRO analyses. Participants completed questionnaires at pre-disclosure baseline and 1-, 6-and 12-months post-disclosure. We used linear multiple regression to assess whether test result contributed to change in pros and cons and logistic regression to predict intentions and surgery uptake. RESULTS Receipt of a positive BRCA1/2 test result predicted stronger pros for RRM and RRO (Ps < .001), but not perceived cons of RRM and RRO. Pros of surgery predicted RRM and RRO intentions in carriers and RRO intentions in uninformatives. Cons predicted RRM intentions in carriers. Pros and cons predicted carriers’ RRO uptake in the year after testing (Ps < .001). CONCLUSIONS Receipt of BRCA1/2 mutation test results impacts how carriers see the positive aspects of RRO and RRM and their surgical intentions. Both the positive and negative aspects predict uptake of surgery. PMID:20383578

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

PubMed Central

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods: In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. Results: The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Conclusion: Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended. PMID:26793655

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

PubMed

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

Bifurcation behaviors of synchronized regions in logistic map networks with coupling delay

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Longkun, E-mail: tomlk@hqu.edu.cn, E-mail: xqwu@whu.edu.cn; Wu, Xiaoqun, E-mail: tomlk@hqu.edu.cn, E-mail: xqwu@whu.edu.cn; Lu, Jun-an, E-mail: jalu@whu.edu.cn

2015-03-15

Network synchronized regions play an extremely important role in network synchronization according to the master stability function framework. This paper focuses on network synchronous state stability via studying the effects of nodal dynamics, coupling delay, and coupling way on synchronized regions in Logistic map networks. Theoretical and numerical investigations show that (1) network synchronization is closely associated with its nodal dynamics. Particularly, the synchronized region bifurcation points through which the synchronized region switches from one type to another are in good agreement with those of the uncoupled node system, and chaotic nodal dynamics can greatly impede network synchronization. (2) Themore » coupling delay generally impairs the synchronizability of Logistic map networks, which is also dominated by the parity of delay for some nodal parameters. (3) A simple nonlinear coupling facilitates network synchronization more than the linear one does. The results found in this paper will help to intensify our understanding for the synchronous state stability in discrete-time networks with coupling delay.« less

The arcsine is asinine: the analysis of proportions in ecology.

PubMed

Warton, David I; Hui, Francis K C

2011-01-01

The arcsine square root transformation has long been standard procedure when analyzing proportional data in ecology, with applications in data sets containing binomial and non-binomial response variables. Here, we argue that the arcsine transform should not be used in either circumstance. For binomial data, logistic regression has greater interpretability and higher power than analyses of transformed data. However, it is important to check the data for additional unexplained variation, i.e., overdispersion, and to account for it via the inclusion of random effects in the model if found. For non-binomial data, the arcsine transform is undesirable on the grounds of interpretability, and because it can produce nonsensical predictions. The logit transformation is proposed as an alternative approach to address these issues. Examples are presented in both cases to illustrate these advantages, comparing various methods of analyzing proportions including untransformed, arcsine- and logit-transformed linear models and logistic regression (with or without random effects). Simulations demonstrate that logistic regression usually provides a gain in power over other methods.

Analysis Test of Understanding of Vectors with the Three-Parameter Logistic Model of Item Response Theory and Item Response Curves Technique

ERIC Educational Resources Information Center

Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

2016-01-01

This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming…

Least Squares Method for Equating Logistic Ability Scales: A General Approach and Evaluation. Iowa Testing Programs Occasional Papers, Number 30.

ERIC Educational Resources Information Center

Haebara, Tomokazu

When several ability scales in item response models are separately derived from different test forms administered to different samples of examinees, these scales must be equated to a common scale because their units and origins are arbitrarily determined and generally different from scale to scale. A general method for equating logistic ability…

Predicting Student Success on the Texas Chemistry STAAR Test: A Logistic Regression Analysis

ERIC Educational Resources Information Center

Johnson, William L.; Johnson, Annabel M.; Johnson, Jared

2012-01-01

Background: The context is the new Texas STAAR end-of-course testing program. Purpose: The authors developed a logistic regression model to predict who would pass-or-fail the new Texas chemistry STAAR end-of-course exam. Setting: Robert E. Lee High School (5A) with an enrollment of 2700 students, Tyler, Texas. Date of the study was the 2011-2012…

Forecasting Workload for Defense Logistics Agency Distribution

DTIC Science & Technology

2014-12-01

Distribution workload ...........................18 Monthly DD Sales for the four primary supply chains ( Avn , Land, Maritime, Ind HW) plotted to...average AVN Aviation BSM Business Systems Modernization CIT consumable items transfer C&E Construction and Equipment C&T Clothing...992081.437 See Figure 2 below for the graphical output of the linear regression. Monthly DD Sales for the four primary supply chains ( Avn , Land

Placement Model for First-Time Freshmen in Calculus I (Math 131): University of Northern Colorado

ERIC Educational Resources Information Center

Heiny, Robert L.; Heiny, Erik L.; Raymond, Karen

2017-01-01

Two approaches, Linear Discriminant Analysis, and Logistic Regression are used and compared to predict success or failure for first-time freshmen in the first calculus course at a medium-sized public, 4-year institution prior to Fall registration. The predictor variables are high school GPA, the number, and GPA's of college prep mathematics…

Analysis of the Effects of the Commander’s Battle Positioning on Unit Combat Performance

DTIC Science & Technology

1991-03-01

Analysis ......... .. 58 Logistic Regression Analysis ......... .. 61 Canonical Correlation Analysis ........ .. 62 Descriminant Analysis...entails classifying objects into two or more distinct groups, or responses. Dillon defines descriminant analysis as "deriving linear combinations of the...object given it’s predictor variables. The second objective is, through analysis of the parameters of the descriminant functions, determine those

Length bias correction in gene ontology enrichment analysis using logistic regression.

PubMed

Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

2012-01-01

When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

Growth models of Rhizophora mangle L. seedlings in tropical southwestern Atlantic

NASA Astrophysics Data System (ADS)

Lima, Karen Otoni de Oliveira; Tognella, Mônica Maria Pereira; Cunha, Simone Rabelo; Andrade, Humber Agrelli de

2018-07-01

The present study selected and compared regression models that best describe the growth curves of Rhizophora mangle seedlings based on the height (cm) and time (days) variables. The Linear, Exponential, Power Law, Monomolecular, Logistic, and Gompertz models were adjusted with non-linear formulations and minimization of the sum of the squares of the residues. The Akaike Information Criterion was used to select the best model for each seedling. After this selection, the determination coefficient, which evaluates how well a model describes height variation as a time function, was inspected. Differing from the classic population ecology studies, the Monomolecular, Three-parameter Logistic, and Gompertz models presented the best performance in describing growth, suggesting they are the most adequate options for long-term studies. The different growth curves reflect the complexity of stem growth at the seedling stage for R. mangle. The analysis of the joint distribution of the parameters initial height, growth rate, and, asymptotic size allowed the study of the species ecological attributes and to observe its intraspecific variability in each model. Our results provide a basis for interpretation of the dynamics of seedlings growth during their establishment in a mature forest, as well as its regeneration processes.

Factors Associated With Health Care Utilization of Recurrent Clostridium difficile Infection in New York State.

PubMed

Mathews, Steven N; Lamm, Ryan; Yang, Jie; Park, Jihye; Tzimas, Demetrios; Buscaglia, Jonathan M; Pryor, Aurora; Talamini, Mark; Telem, Dana; Bucobo, Juan C

2018-03-21

The incidence of infection due to Clostridium difficile infection (CDI) and subsequent economic burden are substantial. The impact of changing practice patterns on demographics at risk and utilization of health care resources for recurrence of CDI remains unclear. A total of 291,163 patients hospitalized for CDI were identified from 1995 to 2014 from the New York SPARCS database. The χ test, the Welch t test, and multivariable logistic regression analysis were performed to evaluate factors related to readmission. Hospital admissions and readmissions for CDI peaked in 2008 at 20,487 and 13,795, respectively, and have since decreased (linear trend, 0.9706 and 0.9464, respectively; P<0.0001). In total, 60,077 (21%) patients required ≥2 admissions. Risk factors for readmission included: age 55 to 74, government insurance, hypertension, diabetes, anemia, hypothyroidism, chronic pulmonary disease, rheumatoid arthritis, renal failure, peripheral vascular disease, and depression (all P<0.05). Trends in surgery showed a similar peak in 2008 at 165 and have since decreased (linear trend, 0.8660; P<0.0001). A total of 1830 (0.63%) patients with CDI underwent surgery, with emergent being more common than elective (71% vs. 29%). Hospital admissions and readmissions for CDI peaked in 2008 and have since been steadily declining. These trends may be secondary to improved diagnostic capabilities and evolving antibiotic regimens. More than 1 in 5 hospitalized patients had at least 1 readmission. Numerous risk factors for these patients have been identified. Although <1% of all patients with CDI undergo surgery, these rates have also been declining.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

Satellite rainfall retrieval by logistic regression

NASA Technical Reports Server (NTRS)

Chiu, Long S.

1986-01-01

The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

NASA Shuttle Logistics Depot (NSLD) - The application of ATE

NASA Technical Reports Server (NTRS)

Simpkins, Lorenz G.; Jenkins, Henry C.; Mauceri, A. Jack

1990-01-01

The concept of the NASA Shuttle Logistics Depot (NSLD) developed for the Space Shuttle Orbiter Program is described. The function of the NSLD at Cape Canaveral is to perform the acceptance and diagnostic testing of the Shuttle's space-rated line-replaceable units and shop-replaceable units (SRUs). The NSLD includes a comprehensive electronic automatic test station, program development stations, and assorted manufacturing support equipment (including thermal and vibration test equipment, special test equipment, and a card SRU test system). The depot activities also include the establishment of the functions for manufacturing of mechanical parts, soldering, welding, painting, clean room operation, procurement, and subcontract management.

Randomized noninferiority study evaluating the efficacy of 2 commercial dry cow mastitis formulations.

PubMed

Johnson, A P; Godden, S M; Royster, E; Zuidhof, S; Miller, B; Sorg, J

2016-01-01

The study objective was to compare the efficacy of 2 commercial dry cow mastitis formulations containing cloxacillin benzathine or ceftiofur hydrochloride. Quarter-level outcomes included prevalence of intramammary infection (IMI) postcalving, risk for cure of preexisting infections, risk for acquiring a new IMI during the dry period, and risk for clinical mastitis between dry off and 100 d in milk (DIM). Cow-level outcomes included the risk for clinical mastitis and the risk for removal from the herd between dry off and 100 DIM, as well as Dairy Herd Improvement Association (DHIA) test-day milk component and production measures between calving and 100 DIM. A total of 799 cows from 4 Wisconsin dairy herds were enrolled at dry off and randomized to 1 of the 2 commercial dry cow therapy (DCT) treatments: cloxacillin benzathine (DC; n=401) or ceftiofur hydrochloride (SM; n=398). Aseptic quarter milk samples were collected for routine bacteriological culture before DCT at dry off and again at 0 to 10 DIM. Data describing clinical mastitis cases and DHIA test-day results were retrieved from on-farm electronic records. The overall crude quarter-level prevalence of IMI at dry off was 34.7% and was not different between treatment groups. Ninety-six percent of infections at dry off were of gram-positive organisms, with coagulase-negative Staphylococcus and Aerococcus spp. isolated most frequently. Mixed logistic regression analysis showed no difference between treatments as to the risk for presence of IMI at 0 to 10 DIM (DC=22.4%, SM=19.9%) or on the risk for acquiring a new IMI between dry off and 0 to 10 DIM (DC=16.6%, SM=14.1%). Noninferiority analysis and mixed logistic regression analysis both showed no treatment difference in risk for a cure between dry off and 0 to 10 DIM (DC=84.8%, SM=85.7%). Cox proportional hazards regression showed no difference between treatments in quarter-level risk for clinical mastitis (DC=1.99%, SM=2.96%), cow-level risk for clinical mastitis (DC=17.0%, SM=15.3%), or on risk for removal from the herd (DC=10.7%, SM=10.3%) between dry off and 100 DIM. Finally, multivariable linear regression with repeated measures showed no overall no difference between treatments in DHIA test-day somatic cell count linear score (DC=2.19, SM=2.22), butterfat test (DC=3.84%, SM=3.86%), protein test (DC=3.02%, SM=3.02%), or 305-d mature-equivalent milk production (DC=11,817 kg, SM=11,932 kg) between calving and 100 DIM. In conclusion, DC was noninferior to SM in effecting a cure, and there was no difference in efficacy between these 2 DCT formulations as related to all other udder health or cow performance measures evaluated between dry off and 100 DIM. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Utilization of Genetic Testing Prior to Subspecialist Referral for Cerebellar Ataxia

PubMed Central

Fogel, Brent L.; Vickrey, Barbara G.; Walton-Wetzel, Jenny; Lieber, Eli

2013-01-01

Objective: To evaluate the utilization of laboratory testing in the diagnosis of cerebellar ataxia, including the completeness of initial standard testing for acquired causes, the early use of genetic testing, and associated clinical and nonclinical factors, among a cohort referred for subspecialty consultation. Methods: Data were abstracted from records of 95 consecutive ataxia patients referred to one neurogenetics subspecialist from 2006–2010 and linked to publicly available data on characteristics of referral clinicians. Multivariable logistic and linear regression models were used to analyze unique associations of clinical and nonclinical factors with laboratory investigation of acquired causes and with early genetic testing prior to referral. Results: At referral, 27 of 95 patients lacked evidence of any of 14 laboratory studies suggested for initial work-up of an acquired cause for ataxia (average number of tests=4.5). In contrast, 92% of patients had undergone brain magnetic resonance imaging prior to referral. Overall, 41.1% (n=39) had genetic testing prior to referral; there was no association between family history of ataxia and obtaining genetic testing prior to referral (p=0.39). The level of early genetic testing was 31.6%, primarily due to genetic testing despite an incomplete laboratory evaluation for acquired causes and no family history. A positive family history was consistently associated with less extensive laboratory testing (p=0.004), and referral by a neurologist was associated with higher levels of early genetic testing. Conclusions: Among consecutive referrals to a single center, a substantial proportion of sporadic cases had genetic testing without evidence of a work-up for acquired causes. Better strategies to guide decision making and subspecialty referrals in rare neurologic disorders are needed, given the cost and consequences of genetic testing. PMID:23725007

CTN summary of DSREDS, EDCARS, EDMICS CALS readiness testing. [Computer-aided Acquisition and Logistic Support (CALS) CALS Test Network (CTN), Digital Storage Retrieval Eng. Data System (DSREDS), Eng. Data Computer Assisted Retrieval System (EDCARS), Eng. Data Management Information and Control System (EDMICS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitschkowetz, N.; Vickers, D.L.

This report provides a summary of the Computer-aided Acquisition and Logistic Support (CALS) Test Network (CTN) Laboratory Acceptance Test (LAT) and User Application Test (UAT) activities undertaken to evaluate the CALS capabilities being implemented as part of the Department of Defense (DOD) engineering repositories. Although the individual testing activities provided detailed reports for each repository, a synthesis of the results, conclusions, and recommendations is offered to provide a more concise presentation of the issues and the strategies, as viewed from the CTN perspective.

MEG connectivity analysis in patients with Alzheimer's disease using cross mutual information and spectral coherence.

PubMed

Alonso, Joan Francesc; Poza, Jesús; Mañanas, Miguel Angel; Romero, Sergio; Fernández, Alberto; Hornero, Roberto

2011-01-01

Alzheimer's disease (AD) is an irreversible brain disorder which represents the most common form of dementia in western countries. An early and accurate diagnosis of AD would enable to develop new strategies for managing the disease; however, nowadays there is no single test that can accurately predict the development of AD. In this sense, only a few studies have focused on the magnetoencephalographic (MEG) AD connectivity patterns. This study compares brain connectivity in terms of linear and nonlinear couplings by means of spectral coherence and cross mutual information function (CMIF), respectively. The variables defined from these functions provide statistically significant differences (p < 0.05) between AD patients and control subjects, especially the variables obtained from CMIF. The results suggest that AD is characterized by both decreases and increases of functional couplings in different frequency bands as well as by an increase in regularity, that is, more evident statistical deterministic relationships in AD patients' MEG connectivity. The significant differences obtained indicate that AD could disturb brain interactions causing abnormal brain connectivity and operation. Furthermore, the combination of coherence and CMIF features to perform a diagnostic test based on logistic regression improved the tests based on individual variables for its robustness.

Respiratory symptoms, lung function, and sensitisation to flour in a British bakery.

PubMed Central

Musk, A W; Venables, K M; Crook, B; Nunn, A J; Hawkins, R; Crook, G D; Graneek, B J; Tee, R D; Farrer, N; Johnson, D A

1989-01-01

A survey of dust exposure, respiratory symptoms, lung function, and response to skin prick tests was conducted in a modern British bakery. Of the 318 bakery employees, 279 (88%) took part. Jobs were ranked from 0 to 10 by perceived dustiness and this ranking correlated well with total dust concentration measured in 79 personal dust samples. Nine samples had concentrations greater than 10 mg/m3, the exposure limit for nuisance dust. All participants completed a self administered questionnaire on symptoms and their relation to work. FEV1 and FVC were measured by a dry wedge spirometer and bronchial reactivity to methacholine was estimated. Skin prick tests were performed with three common allergens and with 11 allergens likely to be found in bakery dust, including mites and moulds. Of the participants in the main exposure group, 35% reported chest symptoms which in 13% were work related. The corresponding figures for nasal symptoms were 38% and 19%. Symptoms, lung function, bronchial reactivity, and response to skin prick tests were related to current or past exposure to dust using logistic or linear regression analysis as appropriate. Exposure rank was significantly associated with most of the response variables studied. The study shows that respiratory symptoms and sensitisation are common, even in a modern bakery. PMID:2789967

Suicide Risk across Latent Class Subgroups: A Test of the Generalizability of the Interpersonal Psychological Theory of Suicide.

PubMed

Ma, Jennifer S; Batterham, Philip J; Calear, Alison L; Han, Jin

2018-01-06

It remains unclear whether the Interpersonal Psychological Theory of Suicide (IPTS; Joiner, ) is generalizable to the population or holds more explanatory power for certain subgroups compared to others. The aim of this study was to (1) identify subgroups of individuals who endorsed suicide ideation in the past month based on a range of mental health and demographic variables, (2) compare levels of the IPTS constructs within these subgroups, and (3) test the IPTS predictions for suicide ideation and suicide attempt for each group. Latent class, negative binomial, linear, and logistic regression analyses were conducted on population-based data obtained from 1,321 adults recruited from Facebook. Among participants reporting suicide ideation, four distinct patterns of risk factors emerged based on age and severity of mental health symptoms. Groups with highly elevated mental health symptoms reported the highest levels of thwarted belongingness and perceived burdensomeness. Tests of the IPTS interactions provided partial support for the theory, primarily in young adults with elevated mental health symptoms. Lack of support found for the IPTS predictions across the subgroups and full sample in this study raise some questions around the broad applicability of the theory. © 2018 The American Association of Suicidology.

Long-term Erythrocytapheresis Is Associated With Reduced Liver Iron Concentration in Sickle Cell Disease.

PubMed

Myers, Scott N; Eid, Ryan; Myers, John; Bertolone, Salvatore; Panigrahi, Arun; Mullinax, Jennifer; Raj, Ashok B

2016-01-01

Erythrocytapheresis procedures are increasingly used in sickle cell disease. Serum ferritin and noninvasive magnetic resonance imaging measurements of liver iron concentration (LIC) are frequently used to monitor iron overload secondary to hypertransfusion. There is a paucity of data describing the impact of long-term erythrocytapheresis (LTE) on LIC. We measured magnetic resonance imaging liver and cardiac iron on LTE subjects and stratified them into 2 groups: higher LIC (>3 mg/g) and lower LIC (<3 mg/g). χ(2) and t test were used to test for differences between the 2 groups. Logistic regression and generalized linear mixed-effects models were used to test what impacted LIC. None of 29 sickle cell disease subjects maintained on LTE had high cardiac iron concentration. LIC was associated with serum ferritin (r=0.697, P<0.001) but was not associated with the total number of LTE procedures (r=-0.088, P=0.656) or total number of simple transfusions (r=0.316, P=0.108). The total number of LTE procedures was not associated with serum ferritin (r=0.040, P=0.838), the total number of simple transfusions (r=-0.258, P=0.184), or LIC group (r=-0.111, P=0.566). There was no significant correlation between duration of LTE maintenance and LIC.

Electronic health record interventions at the point of care improve documentation of care processes and decrease orders for genetic tests commonly ordered by nongeneticists.

PubMed

Scheuner, Maren T; Peredo, Jane; Tangney, Kelly; Schoeff, Diane; Sale, Taylor; Lubick-Goldzweig, Caroline; Hamilton, Alison; Hilborne, Lee; Lee, Martin; Mittman, Brian; Yano, Elizabeth M; Lubin, Ira M

2017-01-01

To determine whether electronic health record (EHR) tools improve documentation of pre- and postanalytic care processes for genetic tests ordered by nongeneticists. We conducted a nonrandomized, controlled, pre-/postintervention study of EHR point-of-care tools (informational messages and template report) for three genetic tests. Chart review assessed documentation of genetic testing processes of care, with points assigned for each documented item. Multiple linear and logistic regressions assessed factors associated with documentation. Preimplementation, there were no significant site differences (P > 0.05). Postimplementation, mean documentation scores increased (5.9 (2.1) vs. 5.0 (2.2); P = 0.0001) and records with clinically meaningful documentation increased (score >5: 59 vs. 47%; P = 0.02) at the intervention versus the control site. Pre- and postimplementation, a score >5 was positively associated with abnormal test results (OR = 4.0; 95% CI: 1.8-9.2) and trainee provider (OR = 2.3; 95% CI: 1.2-4.6). Postimplementation, a score >5 was also positively associated with intervention site (OR = 2.3; 95% CI: 1.1-5.1) and specialty clinic (OR = 2.0; 95% CI: 1.1-3.6). There were also significantly fewer tests ordered after implementation (264/100,000 vs. 204/100,000; P = 0.03), with no significant change at the control site (280/100,000 vs. 257/100,000; P = 0.50). EHR point-of-care tools improved documentation of genetic testing processes and decreased utilization of genetic tests commonly ordered by nongeneticists.Genet Med 19 1, 112-120.

Classical Testing in Functional Linear Models.

PubMed

Kong, Dehan; Staicu, Ana-Maria; Maity, Arnab

2016-01-01

We extend four tests common in classical regression - Wald, score, likelihood ratio and F tests - to functional linear regression, for testing the null hypothesis, that there is no association between a scalar response and a functional covariate. Using functional principal component analysis, we re-express the functional linear model as a standard linear model, where the effect of the functional covariate can be approximated by a finite linear combination of the functional principal component scores. In this setting, we consider application of the four traditional tests. The proposed testing procedures are investigated theoretically for densely observed functional covariates when the number of principal components diverges. Using the theoretical distribution of the tests under the alternative hypothesis, we develop a procedure for sample size calculation in the context of functional linear regression. The four tests are further compared numerically for both densely and sparsely observed noisy functional data in simulation experiments and using two real data applications.

Classical Testing in Functional Linear Models

PubMed Central

Kong, Dehan; Staicu, Ana-Maria; Maity, Arnab

2016-01-01

We extend four tests common in classical regression - Wald, score, likelihood ratio and F tests - to functional linear regression, for testing the null hypothesis, that there is no association between a scalar response and a functional covariate. Using functional principal component analysis, we re-express the functional linear model as a standard linear model, where the effect of the functional covariate can be approximated by a finite linear combination of the functional principal component scores. In this setting, we consider application of the four traditional tests. The proposed testing procedures are investigated theoretically for densely observed functional covariates when the number of principal components diverges. Using the theoretical distribution of the tests under the alternative hypothesis, we develop a procedure for sample size calculation in the context of functional linear regression. The four tests are further compared numerically for both densely and sparsely observed noisy functional data in simulation experiments and using two real data applications. PMID:28955155

Peripheral Nervous System Function and Organophosphate Pesticide Use among Licensed Pesticide Applicators in the Agricultural Health Study

PubMed Central

Starks, Sarah E.; Hoppin, Jane A.; Kamel, Freya; Lynch, Charles F.; Jones, Michael P.; Alavanja, Michael C.; Sandler, Dale P.

2012-01-01

Background: Evidence is limited that long-term human exposure to organophosphate (OP) pesticides, without poisoning, is associated with adverse peripheral nervous system (PNS) function. Objective: We investigated associations between OP pesticide use and PNS function by administering PNS tests to 701 male pesticide applicators in the Agricultural Health Study (AHS). Methods: Participants completed a neurological physical examination (NPx) and electrophysiological tests as well as tests of hand strength, sway speed, and vibrotactile threshold. Self-reported information on lifetime use of 16 OP pesticides was obtained from AHS interviews and a study questionnaire. Associations between pesticide use and measures of PNS function were estimated with linear and logistic regression controlling for age and outcome-specific covariates. Results: Significantly increased odds ratios (ORs) were observed for associations between ever use of 10 of the 16 OP pesticides and one or more of six NPx outcomes. Most notably, abnormal toe proprioception was significantly associated with ever use of 6 OP pesticides, with ORs ranging from 2.03 to 3.06; monotonic increases in strength of association with increasing use was observed for 3 of the 6 pesticides. Mostly null associations were observed between OP pesticide use and electrophysiological tests, hand strength, sway speed, and vibrotactile threshold. Conclusions: This study provides some evidence that long-term exposure to OP pesticides is associated with signs of impaired PNS function among pesticide applicators. PMID:22262687

Structural Dynamic Analyses And Test Predictions For Spacecraft Structures With Non-Linearities

NASA Astrophysics Data System (ADS)

Vergniaud, Jean-Baptiste; Soula, Laurent; Newerla, Alfred

2012-07-01

The overall objective of the mechanical development and verification process is to ensure that the spacecraft structure is able to sustain the mechanical environments encountered during launch. In general the spacecraft structures are a-priori assumed to behave linear, i.e. the responses to a static load or dynamic excitation, respectively, will increase or decrease proportionally to the amplitude of the load or excitation induced. However, past experiences have shown that various non-linearities might exist in spacecraft structures and the consequences of their dynamic effects can significantly affect the development and verification process. Current processes are mainly adapted to linear spacecraft structure behaviour. No clear rules exist for dealing with major structure non-linearities. They are handled outside the process by individual analysis and margin policy, and analyses after tests to justify the CLA coverage. Non-linearities can primarily affect the current spacecraft development and verification process on two aspects. Prediction of flights loads by launcher/satellite coupled loads analyses (CLA): only linear satellite models are delivered for performing CLA and no well-established rules exist how to properly linearize a model when non- linearities are present. The potential impact of the linearization on the results of the CLA has not yet been properly analyzed. There are thus difficulties to assess that CLA results will cover actual flight levels. Management of satellite verification tests: the CLA results generated with a linear satellite FEM are assumed flight representative. If the internal non- linearities are present in the tested satellite then there might be difficulties to determine which input level must be passed to cover satellite internal loads. The non-linear behaviour can also disturb the shaker control, putting the satellite at risk by potentially imposing too high levels. This paper presents the results of a test campaign performed in the frame of an ESA TRP study [1]. A bread-board including typical non-linearities has been designed, manufactured and tested through a typical spacecraft dynamic test campaign. The study has demonstrate the capabilities to perform non-linear dynamic test predictions on a flight representative spacecraft, the good correlation of test results with respect to Finite Elements Model (FEM) prediction and the possibility to identify modal behaviour and to characterize non-linearities characteristics from test results. As a synthesis for this study, overall guidelines have been derived on the mechanical verification process to improve level of expertise on tests involving spacecraft including non-linearity.

Active Travel to School: Findings from the Survey of US Health Behavior in School-Aged Children, 2009-2010

ERIC Educational Resources Information Center

Yang, Yong; Ivey, Stephanie S.; Levy, Marian C.; Royne, Marla B.; Klesges, Lisa M.

2016-01-01

Background: Whereas children's active travel to school (ATS) has confirmed benefits, only a few large national surveys of ATS exist. Methods: Using data from the Health Behavior in School-aged Children (HBSC) 2009-2010 US survey, we conducted a logistic regression model to estimate the odds ratios of ATS and a linear regression model to estimate…

On estimating probability of presence from use-availability or presence-background data.

PubMed

Phillips, Steven J; Elith, Jane

2013-06-01

A fundamental ecological modeling task is to estimate the probability that a species is present in (or uses) a site, conditional on environmental variables. For many species, available data consist of "presence" data (locations where the species [or evidence of it] has been observed), together with "background" data, a random sample of available environmental conditions. Recently published papers disagree on whether probability of presence is identifiable from such presence-background data alone. This paper aims to resolve the disagreement, demonstrating that additional information is required. We defined seven simulated species representing various simple shapes of response to environmental variables (constant, linear, convex, unimodal, S-shaped) and ran five logistic model-fitting methods using 1000 presence samples and 10 000 background samples; the simulations were repeated 100 times. The experiment revealed a stark contrast between two groups of methods: those based on a strong assumption that species' true probability of presence exactly matches a given parametric form had highly variable predictions and much larger RMS error than methods that take population prevalence (the fraction of sites in which the species is present) as an additional parameter. For six species, the former group grossly under- or overestimated probability of presence. The cause was not model structure or choice of link function, because all methods were logistic with linear and, where necessary, quadratic terms. Rather, the experiment demonstrates that an estimate of prevalence is not just helpful, but is necessary (except in special cases) for identifying probability of presence. We therefore advise against use of methods that rely on the strong assumption, due to Lele and Keim (recently advocated by Royle et al.) and Lancaster and Imbens. The methods are fragile, and their strong assumption is unlikely to be true in practice. We emphasize, however, that we are not arguing against standard statistical methods such as logistic regression, generalized linear models, and so forth, none of which requires the strong assumption. If probability of presence is required for a given application, there is no panacea for lack of data. Presence-background data must be augmented with an additional datum, e.g., species' prevalence, to reliably estimate absolute (rather than relative) probability of presence.

Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach

NASA Astrophysics Data System (ADS)

Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi

Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Cao, Faxian; Yang, Zhijing; Ren, Jinchang; Ling, Wing-Kuen; Zhao, Huimin; Marshall, Stephen

2017-12-01

Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values. This has significantly constrained its applications for hyperspectral image (HSI) classification. In order to tackle these two drawbacks, an extreme sparse multinomial logistic regression (ESMLR) is proposed for effective classification of HSI. First, the HSI dataset is projected to a new feature space with randomly generated weight and bias. Second, an optimization model is established by the Lagrange multiplier method and the dual principle to automatically determine a good initial regressor for SMLR via minimizing the training error and the regressor value. Furthermore, the extended multi-attribute profiles (EMAPs) are utilized for extracting both the spectral and spatial features. A combinational linear multiple features learning (MFL) method is proposed to further enhance the features extracted by ESMLR and EMAPs. Finally, the logistic regression via the variable splitting and the augmented Lagrangian (LORSAL) is adopted in the proposed framework for reducing the computational time. Experiments are conducted on two well-known HSI datasets, namely the Indian Pines dataset and the Pavia University dataset, which have shown the fast and robust performance of the proposed ESMLR framework.

Navy Technical Information Presentation System (NTIPS) Test and Implementation Strategy

DTIC Science & Technology

1981-12-01

IC AROEROCK I NAOI S ~ i P RF R M N C AVI AT OIO N A N DDEPARTMENT STIPRUCTRMNES COMPUATIONAN DEPARTMENT -MATHEMATICS AND 17 LOGISTICS DEPARTMENT leI...and Subtitle) S . TYPE OF REPORT & PERIOD COVERED NAVY TECHNICAL INFORMATION PRESENTATION Final SYSTEM (NTIPS) TEST AND IMPLEMENTATION 6. PERFORMING...CLASSIFICATION OP THIS PAGE (1nor. Data Enteed) ock 20 continued) system operation, training, maintenance, and logistics support. This system was

Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography.

PubMed

Kim, Sun Mi; Kim, Yongdai; Jeong, Kuhwan; Jeong, Heeyeong; Kim, Jiyoung

2018-01-01

The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD) into the image analysis in order to improve the diagnosis of breast cancer. This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We applied and compared two regression methods-stepwise logistic (SL) regression and logistic least absolute shrinkage and selection operator (LASSO) regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC) of the tests. Logistic LASSO regression was superior (P<0.05) to SL regression, regardless of whether CDD was included in the covariates, in terms of test misclassification errors (0.234 vs. 0.253, without CDD; 0.196 vs. 0.258, with CDD) and AUC (0.785 vs. 0.759, without CDD; 0.873 vs. 0.735, with CDD). However, it was inferior (P<0.05) to the agreement of three radiologists in terms of test misclassification errors (0.234 vs. 0.168, without CDD; 0.196 vs. 0.088, with CDD) and the AUC without CDD (0.785 vs. 0.844, P<0.001), but was comparable to the AUC with CDD (0.873 vs. 0.880, P=0.141). Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

National Test and Evaluation Conference (26th)

DTIC Science & Technology

2010-03-04

Operations Division, Office of the Chief of Naval Operations (OPNAV N41) Luncheon Speaker · BrigGen Mike Dana , USMC, Director of Logistics...Speaker u BrigGen Mike Dana , USMC, Director of Logistics & Engineering, J4, NORAD and USNORTHCOM u Col Alex Vohr, USMC, Director of Logistics, J4...are the Core Elements of a Curriculum on Contemporary Strategy, and What are the Best Methods of Teaching Them? Dr Richard Betts, Arnold A. Saltzman

Information Processing Capacity of Dynamical Systems

NASA Astrophysics Data System (ADS)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-07-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory.

Non-linear quantitative structure-activity relationship for adenine derivatives as competitive inhibitors of adenosine deaminase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sadat Hayatshahi, Sayyed Hamed; Abdolmaleki, Parviz; Safarian, Shahrokh

2005-12-16

Logistic regression and artificial neural networks have been developed as two non-linear models to establish quantitative structure-activity relationships between structural descriptors and biochemical activity of adenosine based competitive inhibitors, toward adenosine deaminase. The training set included 24 compounds with known k {sub i} values. The models were trained to solve two-class problems. Unlike the previous work in which multiple linear regression was used, the highest of positive charge on the molecules was recognized to be in close relation with their inhibition activity, while the electric charge on atom N1 of adenosine was found to be a poor descriptor. Consequently, themore » previously developed equation was improved and the newly formed one could predict the class of 91.66% of compounds correctly. Also optimized 2-3-1 and 3-4-1 neural networks could increase this rate to 95.83%.« less

Information Processing Capacity of Dynamical Systems

PubMed Central

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-01-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory. PMID:22816038

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

An integrated evaluation of some faecal indicator bacteria (FIB) and chemical markers as potential tools for monitoring sewage contamination in subtropical estuaries.

PubMed

Cabral, Ana Caroline; Stark, Jonathan S; Kolm, Hedda E; Martins, César C

2018-04-01

Sewage input and the relationship between chemical markers (linear alkylbenzenes and coprostanol) and fecal indicator bacteria (FIB, Escherichia coli and enterococci), were evaluated in order to establish thresholds values for chemical markers in suspended particulate matter (SPM) as indicators of sewage contamination in two subtropical estuaries in South Atlantic Brazil. Both chemical markers presented no linear relationship with FIB due to high spatial microbiological variability, however, microbiological water quality was related to coprostanol values when analyzed by logistic regression, indicating that linear models may not be the best representation of the relationship between both classes of indicators. Logistic regression was performed with all data and separately for two sampling seasons, using 800 and 100 MPN 100 mL -1 of E. coli and enterococci, respectively, as the microbiological limits of sewage contamination. Threshold values of coprostanol varied depending on the FIB and season, ranging between 1.00 and 2.23 μg g -1 SPM. The range of threshold values of coprostanol for SPM are relatively higher and more variable than those suggested in literature for sediments (0.10-0.50 μg g -1 ), probably due to higher concentration of coprostanol in SPM than in sediment. Temperature may affect the relationship between microbiological indicators and coprostanol, since the threshold value of coprostanol found here was similar to tropical areas, but lower than those found during winter in temperate areas, reinforcing the idea that threshold values should be calibrated for different climatic conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Large scale landslide susceptibility assessment using the statistical methods of logistic regression and BSA - study case: the sub-basin of the small Niraj (Transylvania Depression, Romania)

NASA Astrophysics Data System (ADS)

Roşca, S.; Bilaşco, Ş.; Petrea, D.; Fodorean, I.; Vescan, I.; Filip, S.; Măguţ, F.-L.

2015-11-01

The existence of a large number of GIS models for the identification of landslide occurrence probability makes difficult the selection of a specific one. The present study focuses on the application of two quantitative models: the logistic and the BSA models. The comparative analysis of the results aims at identifying the most suitable model. The territory corresponding to the Niraj Mic Basin (87 km2) is an area characterised by a wide variety of the landforms with their morphometric, morphographical and geological characteristics as well as by a high complexity of the land use types where active landslides exist. This is the reason why it represents the test area for applying the two models and for the comparison of the results. The large complexity of input variables is illustrated by 16 factors which were represented as 72 dummy variables, analysed on the basis of their importance within the model structures. The testing of the statistical significance corresponding to each variable reduced the number of dummy variables to 12 which were considered significant for the test area within the logistic model, whereas for the BSA model all the variables were employed. The predictability degree of the models was tested through the identification of the area under the ROC curve which indicated a good accuracy (AUROC = 0.86 for the testing area) and predictability of the logistic model (AUROC = 0.63 for the validation area).

Blackmail propagation on small-world networks

NASA Astrophysics Data System (ADS)

Shao, Zhi-Gang; Jian-Ping Sang; Zou, Xian-Wu; Tan, Zhi-Jie; Jin, Zhun-Zhi

2005-06-01

The dynamics of the blackmail propagation model based on small-world networks is investigated. It is found that for a given transmitting probability λ the dynamical behavior of blackmail propagation transits from linear growth type to logistical growth one with the network randomness p increases. The transition takes place at the critical network randomness pc=1/N, where N is the total number of nodes in the network. For a given network randomness p the dynamical behavior of blackmail propagation transits from exponential decrease type to logistical growth one with the transmitting probability λ increases. The transition occurs at the critical transmitting probability λc=1/, where is the average number of the nearest neighbors. The present work will be useful for understanding computer virus epidemics and other spreading phenomena on communication and social networks.

Effects of habitat characteristics on the growth of carrier population leading to increased spread of typhoid fever: a model.

PubMed

Shukla, J B; Goyal, Ashish; Singh, Shikha; Chandra, Peeyush

2014-06-01

In this paper, a non-linear model is proposed and analyzed to study the effects of habitat characteristics favoring logistically growing carrier population leading to increased spread of typhoid fever. It is assumed that the cumulative density of habitat characteristics and the density of carrier population are governed by logistic models; the growth rate of the former increases as the density of human population increases. The model is analyzed by stability theory of differential equations and computer simulation. The analysis shows that as the density of the infective carrier population increases due to habitat characteristics, the spread of typhoid fever increases in comparison with the case without such factors. Copyright © 2013 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

Logistics Reduction and Repurposing Technology for Long Duration Space Missions

NASA Technical Reports Server (NTRS)

Broyan, James L.; Chu, Andrew; Ewert, Michael K.

2014-01-01

One of NASA's Advanced Exploration Systems (AES) projects is the Logistics Reduction and Repurposing (LRR) project, which has the goal of reducing logistics resupply items through direct and indirect means. Various technologies under development in the project will reduce the launch mass of consumables and their packaging, enable reuse and repurposing of items and make logistics tracking more efficient. Repurposing also reduces the trash burden onboard spacecraft and indirectly reduces launch mass by replacing some items on the manifest. Examples include reuse of trash as radiation shielding or propellant. This paper provides the status of the LRR technologies in their third year of development under AES. Advanced clothing systems (ACS) are being developed to enable clothing to be worn longer, directly reducing launch mass. ACS has completed a ground exercise clothing study in preparation for an International Space Station (ISS) technology demonstration in 2014. Development of launch packaging containers and other items that can be repurposed on-orbit as part of habitation outfitting has resulted in a logistics-to-living (L2L) concept. L2L has fabricated and evaluated several multi-purpose cargo transfer bags (MCTBs) for potential reuse on orbit. Autonomous logistics management (ALM) is using radio frequency identification (RFID) to track items and thus reduce crew requirements for logistics functions. An RFID dense reader prototype is under construction and plans for integrated testing are being made. Development of a heat melt compactor (HMC) second generation unit for processing trash into compact and stable tiles is nearing completion. The HMC prototype compaction chamber has been completed and system development testing is underway. Research has been conducted on the conversion of trash-to-gas (TtG) for high levels of volume reduction and for use in propulsion systems. A steam reformation system was selected for further system definition of the TtG technology. And benefits analysis of all LRR technologies have been updated with the latest test and analysis results.

Economic growth and CO2 emissions: an investigation with smooth transition autoregressive distributed lag models for the 1800-2014 period in the USA.

PubMed

Bildirici, Melike; Ersin, Özgür Ömer

2018-01-01

The study aims to combine the autoregressive distributed lag (ARDL) cointegration framework with smooth transition autoregressive (STAR)-type nonlinear econometric models for causal inference. Further, the proposed STAR distributed lag (STARDL) models offer new insights in terms of modeling nonlinearity in the long- and short-run relations between analyzed variables. The STARDL method allows modeling and testing nonlinearity in the short-run and long-run parameters or both in the short- and long-run relations. To this aim, the relation between CO 2 emissions and economic growth rates in the USA is investigated for the 1800-2014 period, which is one of the largest data sets available. The proposed hybrid models are the logistic, exponential, and second-order logistic smooth transition autoregressive distributed lag (LSTARDL, ESTARDL, and LSTAR2DL) models combine the STAR framework with nonlinear ARDL-type cointegration to augment the linear ARDL approach with smooth transitional nonlinearity. The proposed models provide a new approach to the relevant econometrics and environmental economics literature. Our results indicated the presence of asymmetric long-run and short-run relations between the analyzed variables that are from the GDP towards CO 2 emissions. By the use of newly proposed STARDL models, the results are in favor of important differences in terms of the response of CO 2 emissions in regimes 1 and 2 for the estimated LSTAR2DL and LSTARDL models.

Associations of age, aerobic fitness, and body mass index with injury in an operational Army brigade.

PubMed

Rappole, Catherine; Grier, Tyson; Anderson, Morgan K; Hauschild, Veronique; Jones, Bruce H

2017-11-01

To investigate the effects of age, aerobic fitness, and body mass index (BMI) on injury risk in operational Army soldiers. Retrospective cohort study. Male soldiers from an operational Army brigade were administered electronic surveys regarding personal characteristics, physical fitness, and injuries occurring over the last 12 months. Injury risks were stratified by age, 2-mile run time, and BMI. Analyses included descriptive incidence, a Mantel-Haenszel χ 2 test to determine trends, a multivariable logistic regression to determine factors associated with injury, and a one-way analysis of variance (ANOVA). Forty-seventy percent of 1099 respondents reported at least one injury. A linear trend showed that as age, 2-mile run time, and BMI increased, so did injury risk (p<0.01). When controlling for BMI, the most significant independent injury risk factors were older age (odd ratio (OR) 30years-35years/≤24years=1.25, 95%CI: 1.08-2.32), (OR≥36years/≤24years=2.05, 95%CI: 1.36-3.10), and slow run times (OR≥15.9min/≤13.9min=1.91, 95%CI: 1.28-2.85). An ANOVA showed that both run times and BMI increased with age. The stratified analysis and the multivariable logistic regression suggested that older age and poor aerobic fitness are stronger predictors of injury than BMI. Copyright © 2017 Sports Medicine Australia. All rights reserved.

Simulation of changes in heavy metal contamination in farmland soils of a typical manufacturing center through logistic-based cellular automata modeling.

PubMed

Qiu, Menglong; Wang, Qi; Li, Fangbai; Chen, Junjian; Yang, Guoyi; Liu, Liming

2016-01-01

A customized logistic-based cellular automata (CA) model was developed to simulate changes in heavy metal contamination (HMC) in farmland soils of Dongguan, a manufacturing center in Southern China, and to discover the relationship between HMC and related explanatory variables (continuous and categorical). The model was calibrated through the simulation and validation of HMC in 2012. Thereafter, the model was implemented for the scenario simulation of development alternatives for HMC in 2022. The HMC in 2002 and 2012 was determined through soil tests and cokriging. Continuous variables were divided into two groups by odds ratios. Positive variables (odds ratios >1) included the Nemerow synthetic pollution index in 2002, linear drainage density, distance from the city center, distance from the railway, slope, and secondary industrial output per unit of land. Negative variables (odds ratios <1) included elevation, distance from the road, distance from the key polluting enterprises, distance from the town center, soil pH, and distance from bodies of water. Categorical variables, including soil type, parent material type, organic content grade, and land use type, also significantly influenced HMC according to Wald statistics. The relative operating characteristic and kappa coefficients were 0.91 and 0.64, respectively, which proved the validity and accuracy of the model. The scenario simulation shows that the government should not only implement stricter environmental regulation but also strengthen the remediation of the current polluted area to effectively mitigate HMC.

The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes.

PubMed

Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

2018-04-15

Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour.

Equating Scores from Adaptive to Linear Tests

ERIC Educational Resources Information Center

van der Linden, Wim J.

2006-01-01

Two local methods for observed-score equating are applied to the problem of equating an adaptive test to a linear test. In an empirical study, the methods were evaluated against a method based on the test characteristic function (TCF) of the linear test and traditional equipercentile equating applied to the ability estimates on the adaptive test…

Limitations of Reliability for Long-Endurance Human Spaceflight

NASA Technical Reports Server (NTRS)

Owens, Andrew C.; de Weck, Olivier L.

2016-01-01

Long-endurance human spaceflight - such as missions to Mars or its moons - will present a never-before-seen maintenance logistics challenge. Crews will be in space for longer and be farther way from Earth than ever before. Resupply and abort options will be heavily constrained, and will have timescales much longer than current and past experience. Spare parts and/or redundant systems will have to be included to reduce risk. However, the high cost of transportation means that this risk reduction must be achieved while also minimizing mass. The concept of increasing system and component reliability is commonly discussed as a means to reduce risk and mass by reducing the probability that components will fail during a mission. While increased reliability can reduce maintenance logistics mass requirements, the rate of mass reduction decreases over time. In addition, reliability growth requires increased test time and cost. This paper assesses trends in test time requirements, cost, and maintenance logistics mass savings as a function of increase in Mean Time Between Failures (MTBF) for some or all of the components in a system. In general, reliability growth results in superlinear growth in test time requirements, exponential growth in cost, and sublinear benefits (in terms of logistics mass saved). These trends indicate that it is unlikely that reliability growth alone will be a cost-effective approach to maintenance logistics mass reduction and risk mitigation for long-endurance missions. This paper discusses these trends as well as other options to reduce logistics mass such as direct reduction of part mass, commonality, or In-Space Manufacturing (ISM). Overall, it is likely that some combination of all available options - including reliability growth - will be required to reduce mass and mitigate risk for future deep space missions.

Model building strategy for logistic regression: purposeful selection.

PubMed

Zhang, Zhongheng

2016-03-01

Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

Short-term cascaded hydroelectric system scheduling based on chaotic particle swarm optimization using improved logistic map

NASA Astrophysics Data System (ADS)

He, Yaoyao; Yang, Shanlin; Xu, Qifa

2013-07-01

In order to solve the model of short-term cascaded hydroelectric system scheduling, a novel chaotic particle swarm optimization (CPSO) algorithm using improved logistic map is introduced, which uses the water discharge as the decision variables combined with the death penalty function. According to the principle of maximum power generation, the proposed approach makes use of the ergodicity, symmetry and stochastic property of improved logistic chaotic map for enhancing the performance of particle swarm optimization (PSO) algorithm. The new hybrid method has been examined and tested on two test functions and a practical cascaded hydroelectric system. The experimental results show that the effectiveness and robustness of the proposed CPSO algorithm in comparison with other traditional algorithms.

Haughton-Mars Project Expedition 2005

NASA Technical Reports Server (NTRS)

deWeck, Olivier; Simchi-Levi, David

2006-01-01

The 2005 expedition to the Haughton-Mars Project (HMP) research station on Devon Island was part of a NASA-funded project on Space Logistics. A team of nine r&searchers from MIT went to the Canadian Arctic to participate in the annual I-IMP field campaign from July 8 to August 12, 2005. We investigated the applicability of the HMP research station as an analogue for planetary macro- and micro-logistics to the Moon and Mars, and began collecting data for modeling purposes. We also tested new technologies and procedures to enhance the ability of humans and robots to jointly explore remote environments. The expedition had four main objectives. We briefly summarize our key findings in each of these areas. 1. Classes of Supply: First, we wanted to understand what supply items existed at the HMP research station in support of planetary science and exploration research at and around the Haughton Crater. We also wanted to quantify the total amount of imported mass at HMP and compare this with predictions from existing parametric lunar base demand models. 2. Macro-Logistics Transportation Network: Our second objective was to understand the nodes, transportation routes, vehicles, capacities and crew and cargo mass flow rates required to support the HMP logistics network. 3. Agent and Asset Tracking: Since the current inventory management system on ISS relies heavily on barcodes and manual tracking, we wanted to test new automated technologies and procedures such as radio frequency identification RFID) to support exploration logistics. 4. Micro-Logistics (EVA): Finally, we wanted to understand the micro-logistical requirements of conducting both short (<1 day) and long traverses in the Mars-analog terrain on Devon Island. Micro-logistics involves the movement of surface vehicles, people and supplies from base to various exploration sites over short distances (<100 km).

A heuristic approach using multiple criteria for environmentally benign 3PLs selection

NASA Astrophysics Data System (ADS)

Kongar, Elif

2005-11-01

Maintaining competitiveness in an environment where price and quality differences between competing products are disappearing depends on the company's ability to reduce costs and supply time. Timely responses to rapidly changing market conditions require an efficient Supply Chain Management (SCM). Outsourcing logistics to third-party logistics service providers (3PLs) is one commonly used way of increasing the efficiency of logistics operations, while creating a more "core competency focused" business environment. However, this alone may not be sufficient. Due to recent environmental regulations and growing public awareness regarding environmental issues, 3PLs need to be not only efficient but also environmentally benign to maintain companies' competitiveness. Even though an efficient and environmentally benign combination of 3PLs can theoretically be obtained using exhaustive search algorithms, heuristics approaches to the selection process may be superior in terms of the computational complexity. In this paper, a hybrid approach that combines a multiple criteria Genetic Algorithm (GA) with Linear Physical Weighting Algorithm (LPPW) to be used in efficient and environmentally benign 3PLs is proposed. A numerical example is also provided to illustrate the method and the analyses.

Growth curves for ostriches (Struthio camelus) in a Brazilian population.

PubMed

Ramos, S B; Caetano, S L; Savegnago, R P; Nunes, B N; Ramos, A A; Munari, D P

2013-01-01

The objective of this study was to fit growth curves using nonlinear and linear functions to describe the growth of ostriches in a Brazilian population. The data set consisted of 112 animals with BW measurements from hatching to 383 d of age. Two nonlinear growth functions (Gompertz and logistic) and a third-order polynomial function were applied. The parameters for the models were estimated using the least-squares method and Gauss-Newton algorithm. The goodness-of-fit of the models was assessed using R(2) and the Akaike information criterion. The R(2) calculated for the logistic growth model was 0.945 for hens and 0.928 for cockerels and for the Gompertz growth model, 0.938 for hens and 0.924 for cockerels. The third-order polynomial fit gave R(2) of 0.938 for hens and 0.924 for cockerels. Among the Akaike information criterion calculations, the logistic growth model presented the lowest values in this study, both for hens and for cockerels. Nonlinear models are more appropriate for describing the sigmoid nature of ostrich growth.

Sparse Logistic Regression for Diagnosis of Liver Fibrosis in Rat by Using SCAD-Penalized Likelihood

PubMed Central

Yan, Fang-Rong; Lin, Jin-Guan; Liu, Yu

2011-01-01

The objective of the present study is to find out the quantitative relationship between progression of liver fibrosis and the levels of certain serum markers using mathematic model. We provide the sparse logistic regression by using smoothly clipped absolute deviation (SCAD) penalized function to diagnose the liver fibrosis in rats. Not only does it give a sparse solution with high accuracy, it also provides the users with the precise probabilities of classification with the class information. In the simulative case and the experiment case, the proposed method is comparable to the stepwise linear discriminant analysis (SLDA) and the sparse logistic regression with least absolute shrinkage and selection operator (LASSO) penalty, by using receiver operating characteristic (ROC) with bayesian bootstrap estimating area under the curve (AUC) diagnostic sensitivity for selected variable. Results show that the new approach provides a good correlation between the serum marker levels and the liver fibrosis induced by thioacetamide (TAA) in rats. Meanwhile, this approach might also be used in predicting the development of liver cirrhosis. PMID:21716672

Age and mortality after injury: is the association linear?

PubMed

Friese, R S; Wynne, J; Joseph, B; Hashmi, A; Diven, C; Pandit, V; O'Keeffe, T; Zangbar, B; Kulvatunyou, N; Rhee, P

2014-10-01

Multiple studies have demonstrated a linear association between advancing age and mortality after injury. An inflection point, or an age at which outcomes begin to differ, has not been previously described. We hypothesized that the relationship between age and mortality after injury is non-linear and an inflection point exists. We performed a retrospective cohort analysis at our urban level I center from 2007 through 2009. All patients aged 65 years and older with the admission diagnosis of injury were included. Non-parametric logistic regression was used to identify the functional form between mortality and age. Multivariate logistic regression was utilized to explore the association between age and mortality. Age 65 years was used as the reference. Significance was defined as p < 0.05. A total of 1,107 patients were included in the analysis. One-third required intensive care unit (ICU) admission and 48 % had traumatic brain injury. 229 patients (20.6 %) were 84 years of age or older. The overall mortality was 7.2 %. Our model indicates that mortality is a quadratic function of age. After controlling for confounders, age is associated with mortality with a regression coefficient of 1.08 for the linear term (p = 0.02) and a regression coefficient of -0.006 for the quadratic term (p = 0.03). The model identified 84.4 years of age as the inflection point at which mortality rates begin to decline. The risk of death after injury varies linearly with age until 84 years. After 84 years of age, the mortality rates decline. These findings may reflect the varying severity of comorbidities and differences in baseline functional status in elderly trauma patients. Specifically, a proportion of our injured patient population less than 84 years old may be more frail, contributing to increased mortality after trauma, whereas a larger proportion of our injured patients over 84 years old, by virtue of reaching this advanced age, may, in fact, be less frail, contributing to less risk of death.

Analysis of a database to predict the result of allergy testing in vivo in patients with chronic nasal symptoms.

PubMed

Lacagnina, Valerio; Leto-Barone, Maria S; La Piana, Simona; Seidita, Aurelio; Pingitore, Giuseppe; Di Lorenzo, Gabriele

2014-01-01

This article uses the logistic regression model for diagnostic decision making in patients with chronic nasal symptoms. We studied the ability of the logistic regression model, obtained by the evaluation of a database, to detect patients with positive allergy skin-prick test (SPT) and patients with negative SPT. The model developed was validated using the data set obtained from another medical institution. The analysis was performed using a database obtained from a questionnaire administered to the patients with nasal symptoms containing personal data, clinical data, and results of allergy testing (SPT). All variables found to be significantly different between patients with positive and negative SPT (p < 0.05) were selected for the logistic regression models and were analyzed with backward stepwise logistic regression, evaluated with area under the curve of the receiver operating characteristic curve. A second set of patients from another institution was used to prove the model. The accuracy of the model in identifying, over the second set, both patients whose SPT will be positive and negative was high. The model detected 96% of patients with nasal symptoms and positive SPT and classified 94% of those with negative SPT. This study is preliminary to the creation of a software that could help the primary care doctors in a diagnostic decision making process (need of allergy testing) in patients complaining of chronic nasal symptoms.

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network

PubMed Central

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins. PMID:27418910

A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

PubMed

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

PubMed

Crane, Paul K; Gibbons, Laura E; Jolley, Lance; van Belle, Gerald

2006-11-01

We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic regression models are applied to each item. Model testing begins with examination of the statistical significance of the interaction term between ability and the group indicator, consistent with nonuniform DIF. Then we turn our attention to the coefficient of the ability term in models with and without the group term. If including the group term has a marked effect on that coefficient, we declare that it has uniform DIF. We examined DIF related to language of test administration in addition to self-reported race, Hispanic ethnicity, age, years of education, and sex. We used PARSCALE for IRT analyses and STATA for ordinal logistic regression approaches. We used an iterative technique for adjusting IRT ability estimates on the basis of DIF findings. Five items were found to have DIF related to language. These same items also had DIF related to other covariates. The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for DIF detection. There appear to be several items with significant DIF related to language of test administration in the MMSE. More attention needs to be paid to the specific criteria used to determine whether an item has DIF, not just the technique used to identify DIF.

Prevalent high-risk HPV infection and vaginal microbiota in Nigerian women.

PubMed

Dareng, E O; Ma, B; Famooto, A O; Adebamowo, S N; Offiong, R A; Olaniyan, O; Dakum, P S; Wheeler, C M; Fadrosh, D; Yang, H; Gajer, P; Brotman, R M; Ravel, J; Adebamowo, C A

2016-01-01

In this study, we evaluated the association between high-risk human papillomavirus (hrHPV) and the vaginal microbiome. Participants were recruited in Nigeria between April and August 2012. Vaginal bacterial composition was characterized by deep sequencing of barcoded 16S rRNA gene fragments (V4) on Illumina MiSeq and HPV was identified using the Roche Linear Array® HPV genotyping test. We used exact logistic regression models to evaluate the association between community state types (CSTs) of vaginal microbiota and hrHPV infection, weighted UniFrac distances to compare the vaginal microbiota of individuals with prevalent hrHPV to those without prevalent hrHPV infection, and the Linear Discriminant Analysis effect size (LEfSe) algorithm to characterize bacteria associated with prevalent hrHPV infection. We observed four CSTs: CST IV-B with a low relative abundance of Lactobacillus spp. in 50% of participants; CST III (dominated by L. iners) in 39·2%; CST I (dominated by L. crispatus) in 7·9%; and CST VI (dominated by proteobacteria) in 2·9% of participants. LEfSe analysis suggested an association between prevalent hrHPV infection and a decreased abundance of Lactobacillus sp. with increased abundance of anaerobes particularly of the genera Prevotella and Leptotrichia in HIV-negative women (P < 0·05). These results are hypothesis generating and further studies are required.

Assessing the Validity of Self-Rated Health with the Short Physical Performance Battery: A Cross-Sectional Analysis of the International Mobility in Aging Study.

PubMed

Pérez-Zepeda, Mario U; Belanger, Emmanuelle; Zunzunegui, Maria-Victoria; Phillips, Susan; Ylli, Alban; Guralnik, Jack

2016-01-01

The aim of this study was to explore the validity of self-rated health across different populations of older adults, when compared to the Short Physical Performance Battery. Cross-sectional analysis of the International Mobility in Aging Study. Five locations: Saint-Hyacinthe and Kingston (Canada), Tirana (Albania), Manizales (Colombia), and Natal (Brazil). Older adults between 65 and 74 years old (n = 1,995). The Short Physical Performance Battery (SPPB) was used to measure physical performance. Self-rated health was assessed with one single five-point question. Linear trends between SPPB scores and self-rated health were tested separately for men and women at each of the five international study sites. Poor physical performance (independent variable) (SPPB less than 8) was used in logistic regression models of self-rated health (dependent variable), adjusting for potential covariates. All analyses were stratified by gender and site of origin. A significant linear association was found between the mean scores of the Short Physical Performance Battery and ordinal categories of self-rated health across research sites and gender groups. After extensive control for objective physical and mental health indicators and socio-demographic variables, these graded associations became non-significant in some research sites. These findings further confirm the validity of SRH as a measure of overall health status in older adults.

Comparison between a Weibull proportional hazards model and a linear model for predicting the genetic merit of US Jersey sires for daughter longevity.

PubMed

Caraviello, D Z; Weigel, K A; Gianola, D

2004-05-01

Predicted transmitting abilities (PTA) of US Jersey sires for daughter longevity were calculated using a Weibull proportional hazards sire model and compared with predictions from a conventional linear animal model. Culling data from 268,008 Jersey cows with first calving from 1981 to 2000 were used. The proportional hazards model included time-dependent effects of herd-year-season contemporary group and parity by stage of lactation interaction, as well as time-independent effects of sire and age at first calving. Sire variances and parameters of the Weibull distribution were estimated, providing heritability estimates of 4.7% on the log scale and 18.0% on the original scale. The PTA of each sire was expressed as the expected risk of culling relative to daughters of an average sire. Risk ratios (RR) ranged from 0.7 to 1.3, indicating that the risk of culling for daughters of the best sires was 30% lower than for daughters of average sires and nearly 50% lower than than for daughters of the poorest sires. Sire PTA from the proportional hazards model were compared with PTA from a linear model similar to that used for routine national genetic evaluation of length of productive life (PL) using cross-validation in independent samples of herds. Models were compared using logistic regression of daughters' stayability to second, third, fourth, or fifth lactation on their sires' PTA values, with alternative approaches for weighting the contribution of each sire. Models were also compared using logistic regression of daughters' stayability to 36, 48, 60, 72, and 84 mo of life. The proportional hazards model generally yielded more accurate predictions according to these criteria, but differences in predictive ability between methods were smaller when using a Kullback-Leibler distance than with other approaches. Results of this study suggest that survival analysis methodology may provide more accurate predictions of genetic merit for longevity than conventional linear models.

Fire spread in chaparral – a comparison of laboratory data and model predictions in burning live fuels

Treesearch

David R. Weise; Eunmo Koo; Xiangyang Zhou; Shankar Mahalingam; Frédéric Morandini; Jacques-Henri Balbi

2016-01-01

Fire behaviour data from 240 laboratory fires in high-density live chaparral fuel beds were compared with model predictions. Logistic regression was used to develop a model to predict fire spread success in the fuel beds and linear regression was used to predict rate of spread. Predictions from the Rothermel equation and three proposed changes as well as two physically...

Regional Differences in Demand for Coal as A Basis for Development of A Product Distribution Model for Mining Companies in the Individual Customers Segment

NASA Astrophysics Data System (ADS)

Magda, Roman; Bogacz, Paweł; Franik, Tadeusz; Celej, Maciej; Migza, Marcin

2014-10-01

The article presents a proposal of methodology based on the process of relationship marketing, serving to determine the level of demand for coal in the individual customer segment, as well as fuel distribution model for this customer group in Poland developed on the basis of this methodology. It also includes selected results of tests carried out using the proposed methods. These proposals have been defined on the basis of market capacity indicators, which can be determined for the district level based on data from the Polish Central Statistical Office. The study also included the use of linear programming, based on the cost of coal logistics, data concerning railway, road and storage infrastructure present on the Polish market and taking into account the legal aspects. The presented results may provide a basis for mining companies to develop a system of coal distribution management in the locations with the highest demand values.

Climate change, weather and road deaths.

PubMed

Robertson, Leon

2018-06-01

In 2015, a 7% increase in road deaths per population in the USA reversed the 35-year downward trend. Here I test the hypothesis that weather influenced the change in trend. I used linear regression to estimate the effect of temperature and precipitation on miles driven per capita in urbanizedurbanised areas of the USA during 2010. I matched date and county of death with temperature on that date and number of people exposed to that temperature to calculate the risk per persons exposed to specific temperatures. I employed logistic regression analysis of temperature, precipitation and other risk factors prevalent in 2014 to project expected deaths in 2015 among the 100 most populous counties in the USA. Comparison of actual and projected deaths provided an estimate of deaths expected without the temperature increase. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Healthcare use and cost in dementia caregivers: Longitudinal results from the Predictors Caregiver Study

PubMed Central

Zhu, Carolyn W.; Scarmeas, Nikolaos; Ornstein, Katherine; Albert, Marilyn; Brandt, Jason; Blacker, Deborah; Sano, Mary; Stern, Yaakov

2014-01-01

OBJECTIVE: To examine the effects of caregiver and patient characteristics on caregivers’ medical care use and cost. METHODS: 147 caregiver/patient dyads were followed annually for 6 years in 3 academic AD centers in the US. Logistic, negative binomial, and generalized linear mixed models were used to examine overall effects of caregiver/patient characteristics on caregivers’ hospitalizations, doctor visits, outpatient tests and procedures, and prescription and over-the-counter medications. RESULTS: Patients’ comorbid conditions and dependence were associated with increased healthcare use and costs of caregivers. Increases in caregiver depressive symptoms are associated with increases in multiple domains of caregivers’ healthcare use and costs. DISCUSSION: Findings suggest that we should expand our focus on dementia patients to include family caregivers to obtain a fuller picture of effects of caregiving. Primary care providers should integrate caregivers’ needs in healthcare planning and delivery. Clinical interventions that treat patients and caregivers as a whole will likely achieve the greatest beneficial effects. PMID:24637299

Internet sexuality research with rural men who have sex with men: can we recruit and retain them?

PubMed

Bowen, Anne

2005-11-01

This study examines the utility of internet banner ads for recruiting rural MSM and identifies correlates of internet HIV risk survey initiation and completion. Banner ads were shown on a popular internet dating site for one month and resulted in 1,045 rural MSM, from 49 States, Canada, Australia/New Zealand, and 5 from other countries initiating the questionnaire. Logistic regression indicated that progression beyond screening questions was negatively related to "expecting pay, but not being paid" and positively related to "using chat rooms to find friends" and identifying as gay. Linear regression indicated that the absolute number of responses by consenting participants was positively correlated with reimbursement, number of sexual partners, motivated by money, and having been HIV tested. Overall, this sample represents one of the largest rural MSM samples; survey completion was high and strengthened by reimbursement and possibly by awareness of HIV risk. Generalizability was limited by low participation of minority and non-gay identified MSM.

Effect of Integrated Pest Management Training on Ugandan Small-Scale Farmers

PubMed Central

Clausen, Anna Sabine; Jørs, Erik; Atuhaire, Aggrey; Thomsen, Jane Frølund

2017-01-01

Small-scale farmers in developing countries use hazardous pesticides taking few or no safety measures. Farmer field schools (FFSs) teaching integrated pest management (IPM) have been shown to reduce pesticide use among trained farmers. This cross-sectional study compares pesticide-related knowledge, attitude, practice (KAP), potential exposure, and self-reported poisoning symptoms among 35 FFS farmers, 44 neighboring farmers, and 35 control farmers after an IPM intervention in Uganda (2011-2012). The FFS farmers were encouraged to teach their neighboring farmers. Data were based on standardized interviews and were analyzed using a linear trend test and logistic regression. The results showed that FFS and neighboring farmers used significantly fewer pesticide applications (P = .021) and used more safety measures. No differences were found on the hazardousness of pesticides used or self-reported symptoms. The study supports IPM as a method to reduce pesticide use and potential exposure and to improve pesticide-related KAP among small-scale farmers in developing countries. PMID:28469450

Unequal views of inequality: Cross-national support for redistribution 1985-2011.

PubMed

VanHeuvelen, Tom

2017-05-01

This research examines public views on government responsibility to reduce income inequality, support for redistribution. While individual-level correlates of support for redistribution are relatively well understood, many questions remain at the country-level. Therefore, I examine how country-level characteristics affect aggregate support for redistribution. I test explanations of aggregate support using a unique dataset combining 18 waves of the International Social Survey Programme and European Social Survey. Results from mixed-effects logistic regression and fixed-effects linear regression models show two primary and contrasting effects. States that reduce inequality through bundles of tax and transfer policies are rewarded with more supportive publics. In contrast, economic development has a seemingly equivalent and dampening effect on public support. Importantly, the effect of economic development grows at higher levels of development, potentially overwhelming the amplifying effect of state redistribution. My results therefore suggest a fundamental challenge to proponents of egalitarian politics. Copyright © 2016 Elsevier Inc. All rights reserved.

Medical mistrust as a key mediator in the association between perceived discrimination and adherence to antiretroviral therapy among HIV-positive Latino men.

PubMed

Galvan, Frank H; Bogart, Laura M; Klein, David J; Wagner, Glenn J; Chen, Ying-Tung

2017-10-01

Discrimination has been found to have deleterious effects on physical health. The goal of the present study was to examine the association between perceived discrimination and adherence to antiretroviral therapy (ART) among HIV-positive Latino men and the extent to which medical mistrust serves as a mediator of that association. A series of linear and logistic regression models was used to test for mediation for three types of perceived discrimination (related to being Latino, being perceived as gay and being HIV-positive). Medical mistrust was found to be significantly associated with perceived discrimination based on Latino ethnicity and HIV serostatus. Medical mistrust was found to mediate the associations between two types of perceived discrimination (related to being Latino and being HIV-positive) and ART adherence. Given these findings, interventions should be developed that increase the skills of HIV-positive Latino men to address both perceived discrimination and medical mistrust.

Plasma amino acid profile associated with fatty liver disease and co-occurrence of metabolic risk factors.

PubMed

Yamakado, Minoru; Tanaka, Takayuki; Nagao, Kenji; Imaizumi, Akira; Komatsu, Michiharu; Daimon, Takashi; Miyano, Hiroshi; Tani, Mizuki; Toda, Akiko; Yamamoto, Hiroshi; Horimoto, Katsuhisa; Ishizaka, Yuko

2017-11-03

Fatty liver disease (FLD) increases the risk of diabetes, cardiovascular disease, and steatohepatitis, which leads to fibrosis, cirrhosis, and hepatocellular carcinoma. Thus, the early detection of FLD is necessary. We aimed to find a quantitative and feasible model for discriminating the FLD, based on plasma free amino acid (PFAA) profiles. We constructed models of the relationship between PFAA levels in 2,000 generally healthy Japanese subjects and the diagnosis of FLD by abdominal ultrasound scan by multiple logistic regression analysis with variable selection. The performance of these models for FLD discrimination was validated using an independent data set of 2,160 subjects. The generated PFAA-based model was able to identify FLD patients. The area under the receiver operating characteristic curve for the model was 0.83, which was higher than those of other existing liver function-associated markers ranging from 0.53 to 0.80. The value of the linear discriminant in the model yielded the adjusted odds ratio (with 95% confidence intervals) for a 1 standard deviation increase of 2.63 (2.14-3.25) in the multiple logistic regression analysis with known liver function-associated covariates. Interestingly, the linear discriminant values were significantly associated with the progression of FLD, and patients with nonalcoholic steatohepatitis also exhibited higher values.

Internet gaming disorder in early adolescence: Associations with parental and adolescent mental health.

PubMed

Wartberg, L; Kriston, L; Kramer, M; Schwedler, A; Lincoln, T M; Kammerl, R

2017-06-01

Internet gaming disorder (IGD) has been included in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Currently, associations between IGD in early adolescence and mental health are largely unexplained. In the present study, the relation of IGD with adolescent and parental mental health was investigated for the first time. We surveyed 1095 family dyads (an adolescent aged 12-14 years and a related parent) with a standardized questionnaire for IGD as well as for adolescent and parental mental health. We conducted linear (dimensional approach) and logistic (categorical approach) regression analyses. Both with dimensional and categorical approaches, we observed statistically significant associations between IGD and male gender, a higher degree of adolescent antisocial behavior, anger control problems, emotional distress, self-esteem problems, hyperactivity/inattention and parental anxiety (linear regression model: corrected R 2 =0.41, logistic regression model: Nagelkerke's R 2 =0.41). IGD appears to be associated with internalizing and externalizing problems in adolescents. Moreover, the findings of the present study provide first evidence that not only adolescent but also parental mental health is relevant to IGD in early adolescence. Adolescent and parental mental health should be considered in prevention and intervention programs for IGD in adolescence. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Canadian Health Measures Survey pre-test: design, methods, results.

PubMed

Tremblay, Mark; Langlois, Renée; Bryan, Shirley; Esliger, Dale; Patterson, Julienne

2007-01-01

The Canadian Health Measures Survey (CHMS) pre-test was conducted to provide information about the challenges and costs associated with administering a physical health measures survey in Canada. To achieve the specific objectives of the pre-test, protocols were developed and tested, and methods for household interviewing and clinic testing were designed and revised. The cost, logistics and suitability of using fixed sites for the CHMS were assessed. Although data collection, transfer and storage procedures are complex, the pre-test experience confirmed Statistics Canada's ability to conduct a direct health measures survey and the willingness of Canadians to participate in such a health survey. Many operational and logistical procedures worked well and, with minor modifications, are being employed in the main survey. Fixed sites were problematic, and survey costs were higher than expected.

Smoking cue reactivity across massed extinction trials: negative affect and gender effects.

PubMed

Collins, Bradley N; Nair, Uma S; Komaroff, Eugene

2011-04-01

Designing and implementing cue exposure procedures to treat nicotine dependence remains a challenge. This study tested the hypothesis that gender and negative affect (NA) influence changes in smoking urge over time using data from a pilot project testing the feasibility of massed extinction procedures. Forty-three smokers and ex-smokers completed the behavioral laboratory procedures. All participants were over 17 years old, smoked at least 10 cigarettes daily over the last year (or the year prior to quitting) and had expired CO below 10 ppm at the beginning of the ~4-hour session. After informed consent, participants completed 45 min of baseline assessments, and then completed a series of 12 identical, 5-minute exposure trials with inter-trial breaks. Smoking cues included visual, tactile, and olfactory cues with a lit cigarette, in addition to smoking-related motor behaviors without smoking. After each trial, participants reported urge and negative affect (NA). Logistic growth curve models supported the hypothesis that across trials, participants would demonstrate an initial linear increase followed by a decrease in smoking urge (quadratic effect). Data supported hypothesized gender, NA, and gender×NA effects. Significant linear increases in urge were observed among high and low NA males, but not among females in either NA subgroup. A differential quadratic effect showed a significant decrease in urge for the low NA subgroup, but a non-significant decrease in urge in the high NA group. This is the first study to demonstrate gender differences and the effects of NA on the extinction process using a smoking cue exposure paradigm. Results could guide future cue reactivity research and exposure interventions for nicotine dependence. Copyright © 2010 Elsevier B.V. All rights reserved.

[A dose-response analysis on the association of gestational weight gain rate and the normal term neonate birth weight].

PubMed

Mao, Yuanyuan; Hu, Wenbin; Liu, Qin; Liu, Li; Li, Yuanming; Shen, Yueping

2015-08-01

To examine the dose-response relationship between gestational weight gain rate and the neonate birth weight. A total of 18 868 women with singleton gestations who delivered between January 2006 and December 2013 were included in this study. Maternal and neonate details of these women were drawn from the Perinatal Monitoring System database. Gestational weight gain rate was defined as the total weight gain during the last and first prenatal care visits divided by the interval weeks. Both Multiple logistic regression analysis and restricted cubic spline methods were performed. Confounding factors included maternal age, education, pre-pregnancy body mass index (BMI), state of residence, parity, gestational weeks of prenatal care entry, and sex of the neonate. The adjusted odds ratio for macrosomia was associated with gestational weight gain rate in lower pre-pregnancy BMI (OR = 3.15, 95% CI: 1.40-7.07), normal (OR = 3.64, 95% CI: 2.84-4.66) or overweight (OR = 2.37, 95% CI: 1.71-3.27). The odds ratios of low birth weight appeared a decrease in those women with lower pre-pregnancy BMI (OR = 0.28, 95% CI: 0.13-0.61) while the normal weight (OR = 0.37, 95% CI: 0.22-0.64) group with gestational weight gain, the rate showed an increase. Association of gestational weight gain rate for macrosomia was found a S-curve in those term delivery women (non-linearity test P < 0.000 1). However, L-curve was observed for low birth weight and gestational weight gain rate in term births (non-linearity test P < 0.000 1). A S-curve was seen between gestational weight gain rate and term delivered macrosomia while L-curve was observed among term delivered low birth weight neonates.

Cognition and screening for hearing loss in nursing home residents.

PubMed

Jupiter, Tina

2012-10-01

To compare hearing screening results using pure tones and distortion product otoacoustic emissions (DPOAEs) with nursing home residents who have dementia and explore the relationship of hearing impairment and cognitive function using the Mini- Mental Status Evaluation (MMSE). A correlational design was implemented to evaluate residents in a large inner city nursing home. One hundred one nursing home residents 65-108 years. DPOAEs and pure tone screenings were conducted at 30 dB HL and 40 dB HL at 1, 2, and 3 kHz. Pure tone thresholds at 1, 2, and 3 kHz were obtained. The MMSE was administered to all participants. Results showed that all residents failed the DPOAE screen, 97.1% failed at 30 dB HL, and 90.0% failed at 40 dB HL. Kendall's tau, phi correlation, linear by linear association, and χ(2) results indicated no significant relationship for any of the screening protocols and cognitive status other than a significant finding with left ear screening at 40 dB HL. Logistic regression analysis indicated that individuals who passed the screen had better MMSE scores. Results of the t test and Mann-Whitney U test revealed a significant difference in cognitive function for residents with a mild hearing loss compared with those with a more significant hearing loss. For screening nursing home residents, 40 dB HL screening level or DPOAEs can be used. The significant finding that residents with greater than a mild hearing loss have poorer cognitive function reinforces the importance of identifying residents with a hearing loss and providing rehabilitation and follow-up. Copyright © 2012 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.

Preserving Institutional Privacy in Distributed binary Logistic Regression.

PubMed

Wu, Yuan; Jiang, Xiaoqian; Ohno-Machado, Lucila

2012-01-01

Privacy is becoming a major concern when sharing biomedical data across institutions. Although methods for protecting privacy of individual patients have been proposed, it is not clear how to protect the institutional privacy, which is many times a critical concern of data custodians. Built upon our previous work, Grid Binary LOgistic REgression (GLORE)1, we developed an Institutional Privacy-preserving Distributed binary Logistic Regression model (IPDLR) that considers both individual and institutional privacy for building a logistic regression model in a distributed manner. We tested our method using both simulated and clinical data, showing how it is possible to protect the privacy of individuals and of institutions using a distributed strategy.

Evaluation of the Logistic Model for GAC Performance in Water Treatment

EPA Science Inventory

Full-scale field measurement and rapid small-scale column test data from the Greater Cincinnati (Ohio) Water Works (GCWW) were used to calibrate and investigate the application of the logistic model for simulating breakthrough of total organic carbon (TOC) in granular activated c...

Theory of chromatic noise masking applied to testing linearity of S-cone detection mechanisms.

PubMed

Giulianini, Franco; Eskew, Rhea T

2007-09-01

A method for testing the linearity of cone combination of chromatic detection mechanisms is applied to S-cone detection. This approach uses the concept of mechanism noise, the noise as seen by a postreceptoral neural mechanism, to represent the effects of superposing chromatic noise components in elevating thresholds and leads to a parameter-free prediction for a linear mechanism. The method also provides a test for the presence of multiple linear detectors and off-axis looking. No evidence for multiple linear mechanisms was found when using either S-cone increment or decrement tests. The results for both S-cone test polarities demonstrate that these mechanisms combine their cone inputs nonlinearly.

A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.

PubMed

Bersabé, Rosa; Rivas, Teresa

2010-05-01

The authors derive a general equation to compute multiple cut-offs on a total test score in order to classify individuals into more than two ordinal categories. The equation is derived from the multinomial logistic regression (MLR) model, which is an extension of the binary logistic regression (BLR) model to accommodate polytomous outcome variables. From this analytical procedure, cut-off scores are established at the test score (the predictor variable) at which an individual is as likely to be in category j as in category j+1 of an ordinal outcome variable. The application of the complete procedure is illustrated by an example with data from an actual study on eating disorders. In this example, two cut-off scores on the Eating Attitudes Test (EAT-26) scores are obtained in order to classify individuals into three ordinal categories: asymptomatic, symptomatic and eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalises DSM-IV criteria for eating disorders. Alternatives to the MLR model to set multiple cut-off scores are discussed.

The increase in symptoms of anxiety and depressed mood among Icelandic adolescents: time trend between 2006 and 2016.

PubMed

Thorisdottir, Ingibjorg E; Asgeirsdottir, Bryndis B; Sigurvinsdottir, Rannveig; Allegrante, John P; Sigfusdottir, Inga D

2017-10-01

Both research and popular media reports suggest that adolescent mental health has been deteriorating across societies with advanced economies. This study sought to describe the trends in self-reported symptoms of depressed mood and anxiety among Icelandic adolescents. Data for this study come from repeated, cross-sectional, population-based school surveys of 43 482 Icelandic adolescents in 9th and 10th grade, with six waves of pooled data from 2006 to 2016. We used analysis of variance, linear regression and binomial logistic regression to examine trends in symptom scores of anxiety and depressed mood over time. Gender differences in trends of high symptoms were also tested for interactions. Linear regression analysis showed a significant linear increase over the course of the study period in mean symptoms of anxiety and depressed mood for girls only; however, symptoms of anxiety among boys decreased. The proportion of adolescents reporting high depressive symptoms increased by 1.6% for boys and 6.8% for girls; the proportion of those reporting high anxiety symptoms increased by 1.3% for boys and 8.6% for girls. Over the study period, the odds for reporting high depressive symptoms and high anxiety symptoms were significantly higher for both genders. Girls were more likely to report high symptoms of anxiety and depressed mood than boys. Self-reported symptoms of anxiety and depressed mood have increased over time among Icelandic adolescents. Our findings suggest that future research needs to look beyond mean changes and examine the trends among those adolescents who report high symptoms of emotional distress. © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

TU-FG-201-04: Computer Vision in Autonomous Quality Assurance of Linear Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, H; Jenkins, C; Yu, S

Purpose: Routine quality assurance (QA) of linear accelerators represents a critical and costly element of a radiation oncology center. Recently, a system was developed to autonomously perform routine quality assurance on linear accelerators. The purpose of this work is to extend this system and contribute computer vision techniques for obtaining quantitative measurements for a monthly multi-leaf collimator (MLC) QA test specified by TG-142, namely leaf position accuracy, and demonstrate extensibility for additional routines. Methods: Grayscale images of a picket fence delivery on a radioluminescent phosphor coated phantom are captured using a CMOS camera. Collected images are processed to correct formore » camera distortions, rotation and alignment, reduce noise, and enhance contrast. The location of each MLC leaf is determined through logistic fitting and a priori modeling based on knowledge of the delivered beams. Using the data collected and the criteria from TG-142, a decision is made on whether or not the leaf position accuracy of the MLC passes or fails. Results: The locations of all MLC leaf edges are found for three different picket fence images in a picket fence routine to 0.1mm/1pixel precision. The program to correct for image alignment and determination of leaf positions requires a runtime of 21– 25 seconds for a single picket, and 44 – 46 seconds for a group of three pickets on a standard workstation CPU, 2.2 GHz Intel Core i7. Conclusion: MLC leaf edges were successfully found using techniques in computer vision. With the addition of computer vision techniques to the previously described autonomous QA system, the system is able to quickly perform complete QA routines with minimal human contribution.« less

Is chloroquine chemoprophylaxis still effective to prevent low birth weight? Results of a study in Benin

PubMed Central

Denoeud, Lise; Fievet, Nadine; Aubouy, Agnès; Ayemonna, Paul; Kiniffo, Richard; Massougbodji, Achille; Cot, Michel

2007-01-01

Background In areas of stable transmission, malaria during pregnancy is associated with severe maternal and foetal outcomes, especially low birth weight (LBW). To prevent these complications, weekly chloroquine (CQ) chemoprophylaxis is now being replaced by intermittent preventive treatment with sulfadoxine-pyrimethamine in West Africa. The prevalence of placental malaria and its burden on LBW were assessed in Benin to evaluate the efficacy of weekly CQ chemoprophylaxis, prior to its replacement by intermittent preventive treatment. Methods In two maternity clinics in Ouidah, an observational study was conducted between April 2004 and April 2005. At each delivery, placental blood smears were examined for malaria infection and women were interviewed on their pregnancy history including CQ intake and dosage. CQ was measured in the urine of a sub-sample (n = 166). Multiple logistic and linear regression were used to assess factors associated with LBW and placental malaria. Results Among 1090 singleton live births, prevalence of placental malaria and LBW were 16% and 17% respectively. After adjustment, there was a non-significant association between placental malaria and LBW (adjusted OR = 1.43; P = 0.10). Multiple linear regression showed a positive association between placental malaria and decreased birth weight in primigravidae. More than 98% of the women reported regular chemoprophylaxis and CQ was detectable in 99% of urine samples. Protection from LBW was high in women reporting regular CQ prophylaxis, with a strong duration-effect relationship (test for linear trend: P < 0,001). Conclusion Despite high parasite resistance and limited effect on placental malaria, a CQ chemoprophylaxis taken at adequate doses showed to be still effective in reducing LBW in Benin. PMID:17341298

Estimation and Selection via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications

PubMed Central

Huang, Jian; Zhang, Cun-Hui

2013-01-01

The ℓ1-penalized method, or the Lasso, has emerged as an important tool for the analysis of large data sets. Many important results have been obtained for the Lasso in linear regression which have led to a deeper understanding of high-dimensional statistical problems. In this article, we consider a class of weighted ℓ1-penalized estimators for convex loss functions of a general form, including the generalized linear models. We study the estimation, prediction, selection and sparsity properties of the weighted ℓ1-penalized estimator in sparse, high-dimensional settings where the number of predictors p can be much larger than the sample size n. Adaptive Lasso is considered as a special case. A multistage method is developed to approximate concave regularized estimation by applying an adaptive Lasso recursively. We provide prediction and estimation oracle inequalities for single- and multi-stage estimators, a general selection consistency theorem, and an upper bound for the dimension of the Lasso estimator. Important models including the linear regression, logistic regression and log-linear models are used throughout to illustrate the applications of the general results. PMID:24348100

STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION.

PubMed

Fan, Jianqing; Xue, Lingzhou; Zou, Hui

2014-06-01

Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression.

STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Zou, Hui

2014-01-01

Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression. PMID:25598560

Leisure-Time and Occupational Physical Activity in Early and Late Adulthood in Relation to Later Life Physical Functioning.

PubMed

Kulmala, Jenni; Ngandu, Tiia; Pajala, Satu; Lehtisalo, Jenni; Levälahti, Esko; Antikainen, Riitta; Laatikainen, Tiina; Oksa, Heikki; Peltonen, Markku; Rauramaa, Rainer; Soininen, Hilkka; Strandberg, Timo; Tuomilehto, Jaakko; Kivipelto, Miia

2016-10-01

Physical activity (PA) has beneficial effects on older age physical functioning, but longitudinal studies with follow-ups extending up to decades are few. We investigated the association between leisure-time PA (LTPA) and occupational PA (OPA) from early to late adulthood in relation to later life performance-based physical functioning. The study involved 1260 people aged 60 to 79 years who took part in assessments of physical functioning (Short Physical Performance Battery [SPPB] test, 10-m maximal walking test, and grip strength test). Participants' data on earlier life LTPA/OPA (age range 25 to 74 years) were received from the previous studies (average follow-up 13.4 years). Logistic, linear, and censored regression models were used to assess the associations between LTPA/OPA earlier in life and subsequent physical functioning. A high level of LTPA earlier in life was associated with a lower risk of having difficulties on the SPPB test (odds ratio [OR]: 0.37; 95% confidence interval [CI], 0.24-0.58) and especially on the chair rise test (OR: 0.42; 95% CI, 0.27-0.64) in old age. Heavy manual work predicted difficulties on SPPB (OR: 1.91; 95% CI, 1.22-2.98) and the chair rise test (OR: 1.75; 95% CI, 1.14-2.69) and poorer walking speed (β = .10, P = .005). This study highlights the importance of LTPA on later life functioning, but also indicates the inverse effects that may be caused by heavy manual work.

Online Sex Partner Meeting Venues as a Risk Factor for Testing HIV Positive Among a Community-Based Sample of Black Men Who Have Sex With Men.

PubMed

Eaton, Lisa A; Maksut, Jessica L; Gamarel, Kristi E; Siembida, Elizabeth J; Driffin, Daniel D; Baldwin, Robert

2016-06-01

In the United States, black men who have sex with men (BMSM) are disproportionately affected by the HIV epidemic. The elevated estimates of HIV among BMSM suggest that to slow rates of HIV infections, a range of factors that may contribute to transmission must be researched. Use of online venues for seeking out sex partners is one such area that may further advance our understanding of risks for HIV among BMSM. Black men who have sex with men residing in Atlanta, GA, reporting HIV-negative/unknown status completed survey assessments and HIV antibody testing. Logistic regression using generalized linear modeling was used to conduct both bivariate and multivariable analyses of psychosocial variables-that is, substance use, sexually transmitted infection symptoms/diagnoses, sexual risk behavior, online sex partner meeting, and HIV test results. Two hundred thirty-two BMSM tested HIV negative and 39 BMSM tested HIV positive (14% new diagnoses). Reporting symptoms of a rectal sexually transmitted infection (odds ratio, 4.28; 95% confidence interval, 1.06-15.41) and use of sexual networking apps (odds ratio, 2.15; 95% confidence interval, 1.06-4.36) were both associated with testing HIV positive in a multivariable analysis. The use of sexual networking apps is associated with risks for HIV infection above and beyond what is captured by sexual risk behavior alone. Evaluating how sexual networking apps affect sexual networks and social norms regarding sexual risk taking and HIV transmission is an important and novel area for HIV prevention and intervention development.

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.

2003-01-01

Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.

Trace Element Study of H Chondrites: Evidence for Meteoroid Streams.

NASA Astrophysics Data System (ADS)

Wolf, Stephen Frederic

1993-01-01

Multivariate statistical analyses, both linear discriminant analysis and logistic regression, of the volatile trace elemental concentrations in H4-6 chondrites reveal compositionally distinguishable subpopulations. Observed difference in volatile trace element composition between Antarctic and non-Antarctic H4-6 chondrites (Lipschutz and Samuels, 1991) can be explained by a compositionaily distinct subpopulation found in Victoria Land, Antarctica. This population of H4-6 chondrites is compositionally distinct from non-Antarctic H4-6 chondrites and from Antarctic H4 -6 chondrites from Queen Maud Land. Comparisons of Queen Maud Land H4-6 chondrites with non-Antarctic H4-6 chondrites do not give reason to believe that these two populations are distinguishable from each other on the basis of the ten volatile trace element concentrations measured. ANOVA indicates that these differences are not the result of trivial causes such as weathering and analytical bias. Thermoluminescence properties of these populations parallels the results of volatile trace element comparisons. Given the differences in terrestrial age between Victoria Land, Queen Maud Land, and modern H4-6 chondrite falls, these results are consistent with a variation in H4-6 chondrite flux on a 300 ky timescale. This conclusion requires the existence of co-orbital meteoroid streams. Statistical analyses of the volatile trace elemental concentrations in non-Antarctic modern falls of H4-6 chondrites also demonstrate that a group of 13 H4-6 chondrites, Cluster 1, selected exclusively for their distinct fall parameters (Dodd, 1992) is compositionally distinguishable from a control group of 45 non-Antarctic modern H4-6 chondrites on the basis of the ten volatile trace element concentrations measured. Model-independent randomization-simulations based on both linear discriminant analysis and logistic regression verify these results. While ANOVA identifies two possible causes for this difference, analytical bias and group classification, a test validation experiment verifies that group classification is the more significant cause of compositional difference between Cluster 1 and non-Cluster 1 modern H4-6 chondrite falls. Thermoluminescence properties of these populations parallels the results of volatile trace element comparisons. This suggests that these meteorites are fragments of a co-orbital meteorite stream derived from a single parent body.

Logistic Approximation to the Normal: The KL Rationale

ERIC Educational Resources Information Center

Savalei, Victoria

2006-01-01

A rationale is proposed for approximating the normal distribution with a logistic distribution using a scaling constant based on minimizing the Kullback-Leibler (KL) information, that is, the expected amount of information available in a sample to distinguish between two competing distributions using a likelihood ratio (LR) test, assuming one of…

Logistic regression function for detection of suspicious performance during baseline evaluations using concussion vital signs.

PubMed

Hill, Benjamin David; Womble, Melissa N; Rohling, Martin L

2015-01-01

This study utilized logistic regression to determine whether performance patterns on Concussion Vital Signs (CVS) could differentiate known groups with either genuine or feigned performance. For the embedded measure development group (n = 174), clinical patients and undergraduate students categorized as feigning obtained significantly lower scores on the overall test battery mean for the CVS, Shipley-2 composite score, and California Verbal Learning Test-Second Edition subtests than did genuinely performing individuals. The final full model of 3 predictor variables (Verbal Memory immediate hits, Verbal Memory immediate correct passes, and Stroop Test complex reaction time correct) was significant and correctly classified individuals in their known group 83% of the time (sensitivity = .65; specificity = .97) in a mixed sample of young-adult clinical cases and simulators. The CVS logistic regression function was applied to a separate undergraduate college group (n = 378) that was asked to perform genuinely and identified 5% as having possibly feigned performance indicating a low false-positive rate. The failure rate was 11% and 16% at baseline cognitive testing in samples of high school and college athletes, respectively. These findings have particular relevance given the increasing use of computerized test batteries for baseline cognitive testing and return-to-play decisions after concussion.

[Clinical significance and distribution of BRCA genes mutation in sporadic high grade serous ovarian cancer].

PubMed

Liu, W L; Wang, Z Z; Zhao, J Z; Hou, Y Y; Wu, X X; Li, W; Dong, B; Tong, T T; Guo, Y J

2017-01-25

Objective: To investigate the mutations of BRCA genes in sporadic high grade serous ovarian cancer (HGSOC) and study its clinical significance. Methods: Sixty-eight patients between January 2015 and January 2016 from the Affiliated Cancer Hospital of Zhengzhou University were collected who were based on pathological diagnosis of ovarian cancer and had no reported family history, and all patients firstly hospitalized were untreated in other hospitals before. (1) The BRCA genes were detected by next-generation sequencing (NGS) method. (2) The serum tumor markers included carcinoembryonic antigen (CEA), CA(125), CA(199), and human epididymis protein 4 (HE4) were detected by the chemiluminescence methods, and their correlation was analyzed by Pearson linear correlation. Descriptive statistics and comparisons were performed using two-tailed t -tests, Pearson's chi square test, Fisher's exact tests or logistic regression analysis as appropriate to research the clinicopathologic features associated with BRCA mutations, including age, International Federation of Gynecology and Obstetrics (FIGO) stage, platinum-based chemotherapy sensitivity, distant metastases, serum tumor markers (STM) . Results: (1) Fifteen cases (22%, 15/68) BRCA mutations were identified (BRCA1: 11 cases; BRCA2: 4 cases), and four novel mutations were observed. (2) The levels of CEA, CA(199), and HE4 were lower in BRCA mutations compared to that in control group, while no significant differences were found ( P >0.05), but the level of CA(125) was much higher in BRCA mutation group than that in controls ( t =-3.536, P =0.003). Further linear regression analysis found that there was a significant linear correlation between CA(125) and HE4 group ( r =0.494, P <0.01), and the same correlation as CEA and CA(199) group ( r =0.897, P <0.01). (3) Single factor analysis showed that no significant differences were observed in onset age, FIGO stage, distant metastasis, and STM between BRCA(+) and BRCA(-) group ( P >0.05), while significant differences were found in CA(125) and sensitivity to platinum-based chemotherapy between the patients with BRCA mutation and wild type ( P <0.05). The multiple factors analysis showed that the high level of CA(125) was a independent risk factor of BRCA mutations in sporadic HGSOC ( P =0.007). Conclusion: The combination of CA(125) with BRCA have great clinical significance, the mutation of BRCA gene could guild the clinical chemotherapy regiments.

Calibration and LOD/LOQ estimation of a chemiluminescent hybridization assay for residual DNA in recombinant protein drugs expressed in E. coli using a four-parameter logistic model.

PubMed

Lee, K R; Dipaolo, B; Ji, X

2000-06-01

Calibration is the process of fitting a model based on reference data points (x, y), then using the model to estimate an unknown x based on a new measured response, y. In DNA assay, x is the concentration, and y is the measured signal volume. A four-parameter logistic model was used frequently for calibration of immunoassay when the response is optical density for enzyme-linked immunosorbent assay (ELISA) or adjusted radioactivity count for radioimmunoassay (RIA). Here, it is shown that the same model or a linearized version of the curve are equally useful for the calibration of a chemiluminescent hybridization assay for residual DNA in recombinant protein drugs and calculation of performance measures of the assay.

Estimating interaction on an additive scale between continuous determinants in a logistic regression model.

PubMed

Knol, Mirjam J; van der Tweel, Ingeborg; Grobbee, Diederick E; Numans, Mattijs E; Geerlings, Mirjam I

2007-10-01

To determine the presence of interaction in epidemiologic research, typically a product term is added to the regression model. In linear regression, the regression coefficient of the product term reflects interaction as departure from additivity. However, in logistic regression it refers to interaction as departure from multiplicativity. Rothman has argued that interaction estimated as departure from additivity better reflects biologic interaction. So far, literature on estimating interaction on an additive scale using logistic regression only focused on dichotomous determinants. The objective of the present study was to provide the methods to estimate interaction between continuous determinants and to illustrate these methods with a clinical example. and results From the existing literature we derived the formulas to quantify interaction as departure from additivity between one continuous and one dichotomous determinant and between two continuous determinants using logistic regression. Bootstrapping was used to calculate the corresponding confidence intervals. To illustrate the theory with an empirical example, data from the Utrecht Health Project were used, with age and body mass index as risk factors for elevated diastolic blood pressure. The methods and formulas presented in this article are intended to assist epidemiologists to calculate interaction on an additive scale between two variables on a certain outcome. The proposed methods are included in a spreadsheet which is freely available at: http://www.juliuscenter.nl/additive-interaction.xls.

Environmental factors and flow paths related to Escherichia coli concentrations at two beaches on Lake St. Clair, Michigan, 2002–2005

USGS Publications Warehouse

Holtschlag, David J.; Shively, Dawn; Whitman, Richard L.; Haack, Sheridan K.; Fogarty, Lisa R.

2008-01-01

Regression analyses and hydrodynamic modeling were used to identify environmental factors and flow paths associated with Escherichia coli (E. coli) concentrations at Memorial and Metropolitan Beaches on Lake St. Clair in Macomb County, Mich. Lake St. Clair is part of the binational waterway between the United States and Canada that connects Lake Huron with Lake Erie in the Great Lakes Basin. Linear regression, regression-tree, and logistic regression models were developed from E. coli concentration and ancillary environmental data. Linear regression models on log10 E. coli concentrations indicated that rainfall prior to sampling, water temperature, and turbidity were positively associated with bacteria concentrations at both beaches. Flow from Clinton River, changes in water levels, wind conditions, and log10 E. coli concentrations 2 days before or after the target bacteria concentrations were statistically significant at one or both beaches. In addition, various interaction terms were significant at Memorial Beach. Linear regression models for both beaches explained only about 30 percent of the variability in log10 E. coli concentrations. Regression-tree models were developed from data from both Memorial and Metropolitan Beaches but were found to have limited predictive capability in this study. The results indicate that too few observations were available to develop reliable regression-tree models. Linear logistic models were developed to estimate the probability of E. coli concentrations exceeding 300 most probable number (MPN) per 100 milliliters (mL). Rainfall amounts before bacteria sampling were positively associated with exceedance probabilities at both beaches. Flow of Clinton River, turbidity, and log10 E. coli concentrations measured before or after the target E. coli measurements were related to exceedances at one or both beaches. The linear logistic models were effective in estimating bacteria exceedances at both beaches. A receiver operating characteristic (ROC) analysis was used to determine cut points for maximizing the true positive rate prediction while minimizing the false positive rate. A two-dimensional hydrodynamic model was developed to simulate horizontal current patterns on Lake St. Clair in response to wind, flow, and water-level conditions at model boundaries. Simulated velocity fields were used to track hypothetical massless particles backward in time from the beaches along flow paths toward source areas. Reverse particle tracking for idealized steady-state conditions shows changes in expected flow paths and traveltimes with wind speeds and directions from 24 sectors. The results indicate that three to four sets of contiguous wind sectors have similar effects on flow paths in the vicinity of the beaches. In addition, reverse particle tracking was used for transient conditions to identify expected flow paths for 10 E. coli sampling events in 2004. These results demonstrate the ability to track hypothetical particles from the beaches, backward in time, to likely source areas. This ability, coupled with a greater frequency of bacteria sampling, may provide insight into changes in bacteria concentrations between source and sink areas.

Pupils' over-reliance on linearity: a scholastic effect?

PubMed

Van Dooren, Wim; De Bock, Dirk; Janssens, Dirk; Verschaffel, Lieven

2007-06-01

From upper elementary education on, children develop a tendency to over-use linearity. Particularly, it is found that many pupils assume that if a figure enlarges k times, the area enlarges k times too. However, most research was conducted with traditional, school-like word problems. This study examines whether pupils also over-use linearity if non-linear problems are embedded in meaningful, authentic performance tasks instead of traditional, school-like word problems, and whether this experience influences later behaviour. Ninety-three sixth graders from two primary schools in Flanders, Belgium. Pupils received a pre-test with traditional word problems. Those who made a linear error on the non-linear area problem were subjected to individual interviews. They received one new non-linear problem, in the S-condition (again a traditional, scholastic word problem), D-condition (the same word problem with a drawing) or P-condition (a meaningful performance-based task). Shortly afterwards, pupils received a post-test, containing again a non-linear word problem. Most pupils from the S-condition displayed linear reasoning during the interview. Offering drawings (D-condition) had a positive effect, but presenting the problem as a performance task (P-condition) was more beneficial. Linear reasoning was nearly absent in the P-condition. Remarkably, at the post-test, most pupils from all three groups again applied linear strategies. Pupils' over-reliance on linearity seems partly elicited by the school-like word problem format of test items. Pupils perform much better if non-linear problems are offered as performance tasks. However, a single experience does not change performances on a comparable word problem test afterwards.

Blood Based Biomarkers of Early Onset Breast Cancer

DTIC Science & Technology

2016-12-01

discretizes the data, and also using logistic elastic net – a form of linear regression - we were unable to build a classifier that could accurately...classifier for differentiating cases from controls off discretized data. The first pass analysis demonstrated a 35 gene signature that differentiated...to the discretized data for mRNA gene signature, the samples used to “train” were also included in the final samples used to “test” the algorithm

A Path Planning and Obstacle Avoidance Hybrid System Using a Connectionist Network

DTIC Science & Technology

1990-06-01

Department lele7 Prfessor of Aerospace Sciences and Mathematical Sciences Houston, Texas June, 1990 Abstract A PATH PLANNING AND OBSTACLE AVOIDANCE HYBRID...See Weiland (1989), Wu (1989), Norwood (1989), Cheatham (1987 & 1989), Adnan (1990), and Regalbuto (1988 & 1990).] Possible applications of this...neuron model’s output can be described mathematically as: Yj(t+ At) =sgn ijXi(t)-O Other non-linearity functions, such as and the sigmoid/ logistics

Tuberculin reactivity and tuberculosis epidemiology in the Pakaanóva (Wari') Indians of Rondônia, south-western Brazilian Amazon.

PubMed

Escobar, A L; Coimbra, C E A; Camacho, L A B; Santos, R V

2004-01-01

To investigate the characteristics of tuberculin skin test reactivity in the Pakaanóva Indians, in Amazonia, Brazil, after revaccination of all study participants with bacille Calmette-Guerin (BCG). The investigation was designed as a post-BCG vaccination purified protein derivative (PPD) survey. Data included PPD readings, age, sex, nutritional status, place of residence, previous tuberculosis, physical examinations and BCG status. Bivariate and multivariate logistic regression analyses were conducted. About 90% (n = 505) of the total population participated. One third (32.1%) of the subjects presented induration > or = 10 mm at 72 h. Induration sizes showed weak linear correlation with age; differences between sexes were not observed. Skin reaction was not associated with nutritional status. Individuals with a history of tuberculosis were six times more likely to test positive. History of tuberculosis, age, and previous BCG vaccination were significantly associated with PPD reactivity in the multivariate analyses. The Pakaanóva showed a high proportion (58.4%) of non-reactors, even with a recent BCG booster. Sex differences in PPD reactivity were either not present or could not be demonstrated. The association between age and PPD reactivity resembles that observed in other Amazonian populations. The authors discuss the potential of PPD testing as a screening tool to enhance tuberculosis detection, especially in indigenous populations in Amazonia with limited access to health services.

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test ofmore » the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.« less

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

NASA Astrophysics Data System (ADS)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

2015-10-01

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

Machine learning techniques for energy optimization in mobile embedded systems

NASA Astrophysics Data System (ADS)

Donohoo, Brad Kyoshi

Mobile smartphones and other portable battery operated embedded systems (PDAs, tablets) are pervasive computing devices that have emerged in recent years as essential instruments for communication, business, and social interactions. While performance, capabilities, and design are all important considerations when purchasing a mobile device, a long battery lifetime is one of the most desirable attributes. Battery technology and capacity has improved over the years, but it still cannot keep pace with the power consumption demands of today's mobile devices. This key limiter has led to a strong research emphasis on extending battery lifetime by minimizing energy consumption, primarily using software optimizations. This thesis presents two strategies that attempt to optimize mobile device energy consumption with negligible impact on user perception and quality of service (QoS). The first strategy proposes an application and user interaction aware middleware framework that takes advantage of user idle time between interaction events of the foreground application to optimize CPU and screen backlight energy consumption. The framework dynamically classifies mobile device applications based on their received interaction patterns, then invokes a number of different power management algorithms to adjust processor frequency and screen backlight levels accordingly. The second strategy proposes the usage of machine learning techniques to learn a user's mobile device usage pattern pertaining to spatiotemporal and device contexts, and then predict energy-optimal data and location interface configurations. By learning where and when a mobile device user uses certain power-hungry interfaces (3G, WiFi, and GPS), the techniques, which include variants of linear discriminant analysis, linear logistic regression, non-linear logistic regression, and k-nearest neighbor, are able to dynamically turn off unnecessary interfaces at runtime in order to save energy.

Analysis of separation test for automatic brake adjuster based on linear radon transformation

NASA Astrophysics Data System (ADS)

Luo, Zai; Jiang, Wensong; Guo, Bin; Fan, Weijun; Lu, Yi

2015-01-01

The linear Radon transformation is applied to extract inflection points for online test system under the noise conditions. The linear Radon transformation has a strong ability of anti-noise and anti-interference by fitting the online test curve in several parts, which makes it easy to handle consecutive inflection points. We applied the linear Radon transformation to the separation test system to solve the separating clearance of automatic brake adjuster. The experimental results show that the feature point extraction error of the gradient maximum optimal method is approximately equal to ±0.100, while the feature point extraction error of linear Radon transformation method can reach to ±0.010, which has a lower error than the former one. In addition, the linear Radon transformation is robust.

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation

PubMed Central

Patterson, Brent R.; Anderson, Morgan L.; Rodgers, Arthur R.; Vander Vennen, Lucas M.; Fryxell, John M.

2017-01-01

Woodland caribou (Rangifer tarandus caribou) in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water) linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon) over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression) at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism–a compensatory functional response to anthropogenic linear feature density resulting in decreased use of natural travel corridors–has negative consequences for the viability of woodland caribou. PMID:29117234

Compensatory selection for roads over natural linear features by wolves in northern Ontario: Implications for caribou conservation.

PubMed

Newton, Erica J; Patterson, Brent R; Anderson, Morgan L; Rodgers, Arthur R; Vander Vennen, Lucas M; Fryxell, John M

2017-01-01

Woodland caribou (Rangifer tarandus caribou) in Ontario are a threatened species that have experienced a substantial retraction of their historic range. Part of their decline has been attributed to increasing densities of anthropogenic linear features such as trails, roads, railways, and hydro lines. These features have been shown to increase the search efficiency and kill rate of wolves. However, it is unclear whether selection for anthropogenic linear features is additive or compensatory to selection for natural (water) linear features which may also be used for travel. We studied the selection of water and anthropogenic linear features by 52 resident wolves (Canis lupus x lycaon) over four years across three study areas in northern Ontario that varied in degrees of forestry activity and human disturbance. We used Euclidean distance-based resource selection functions (mixed-effects logistic regression) at the seasonal range scale with random coefficients for distance to water linear features, primary/secondary roads/railways, and hydro lines, and tertiary roads to estimate the strength of selection for each linear feature and for several habitat types, while accounting for availability of each feature. Next, we investigated the trade-off between selection for anthropogenic and water linear features. Wolves selected both anthropogenic and water linear features; selection for anthropogenic features was stronger than for water during the rendezvous season. Selection for anthropogenic linear features increased with increasing density of these features on the landscape, while selection for natural linear features declined, indicating compensatory selection of anthropogenic linear features. These results have implications for woodland caribou conservation. Prey encounter rates between wolves and caribou seem to be strongly influenced by increasing linear feature densities. This behavioral mechanism-a compensatory functional response to anthropogenic linear feature density resulting in decreased use of natural travel corridors-has negative consequences for the viability of woodland caribou.

Modelling and genetic algorithm based optimisation of inverse supply chain

NASA Astrophysics Data System (ADS)

Bányai, T.

2009-04-01

The design and control of recycling systems of products with environmental risk have been discussed in the world already for a long time. The main reasons to address this subject are the followings: reduction of waste volume, intensification of recycling of materials, closing the loop, use of less resource, reducing environmental risk [1, 2]. The development of recycling systems is based on the integrated solution of technological and logistic resources and know-how [3]. However the financial conditions of recycling systems is partly based on the recovery, disassembly and remanufacturing options of the used products [4, 5, 6], but the investment and operation costs of recycling systems can be characterised with high logistic costs caused by the geographically wide collection system with more collection level and a high number of operation points of the inverse supply chain. The reduction of these costs is a popular area of the logistics researches. These researches include the design and implementation of comprehensive environmental waste and recycling program to suit business strategies (global system), design and supply all equipment for production line collection (external system), design logistics process to suit the economical and ecological requirements (external system) [7]. To the knowledge of the author, there has been no research work on supply chain design problems that purpose is the logistics oriented optimisation of inverse supply chain in the case of non-linear total cost function consisting not only operation costs but also environmental risk cost. The antecedent of this research is, that the author has taken part in some research projects in the field of closed loop economy ("Closing the loop of electr(on)ic products and domestic appliances from product planning to end-of-life technologies), environmental friendly disassembly (Concept for logistical and environmental disassembly technologies) and design of recycling systems of household appliances (Recycling of household appliances with emphasis on reuse options). The purpose of this paper is the presentation of a possible method for avoiding the unnecessary environmental risk and landscape use through unprovoked large supply chain of collection systems of recycling processes. In the first part of the paper the author presents the mathematical model of recycling related collection systems (applied especially for wastes of electric and electronic products) and in the second part of the work a genetic algorithm based optimisation method will be demonstrated, by the aid of which it is possible to determine the optimal structure of the inverse supply chain from the point of view economical, ecological and logistic objective functions. The model of the inverse supply chain is based on a multi-level, hierarchical collection system. In case of this static model it is assumed that technical conditions are permanent. The total costs consist of three parts: total infrastructure costs, total material handling costs and environmental risk costs. The infrastructure-related costs are dependent only on the specific fixed costs and the specific unit costs of the operation points (collection, pre-treatment, treatment, recycling and reuse plants). The costs of warehousing and transportation are represented by the material handling related costs. The most important factors determining the level of environmental risk cost are the number of out of time recycled (treated or reused) products, the number of supply chain objects and the length of transportation routes. The objective function is the minimization of the total cost taking into consideration the constraints. However a lot of research work discussed the design of supply chain [8], but most of them concentrate on linear cost functions. In the case of this model non-linear cost functions were used. The non-linear cost functions and the possible high number of objects of the inverse supply chain leaded to the problem of choosing a possible solution method. By the aid of analytical methods, the problem can not be solved, so a genetic algorithm based heuristic optimisation method was chosen to find the optimal solution. The input parameters of the optimisation are the followings: specific fixed, unit and environmental risk costs of the collection points of the inverse supply chain, specific warehousing and transportation costs and environmental risk costs of transportation. The output parameters are the followings: the number of objects in the different hierarchical levels of the collection system, infrastructure costs, logistics costs and environmental risk costs from used infrastructures, transportation and number of products recycled out of time. The next step of the research work was the application of the above mentioned method. The developed application makes it possible to define the input parameters of the real system, the graphical view of the chosen optimal solution in the case of the given input parameters, graphical view of the cost structure of the optimal solution, determination of the parameters of the algorithm (e.g. number of individuals, operators and termination conditions). The sensibility analysis of the objective function and the test results showed that the structure of the inverse supply chain depends on the proportion of the specific costs. Especially the proportion of the specific environmental risk costs influences the structure of the system and the number of objects at each hierarchical level of the collection system. The sensitivity analysis of the total cost function was performed in three cases. In the first case the effect of the proportion of specific infrastructure and logistics costs were analysed. If the infrastructure costs are significantly lower than the total costs of warehousing and transportation, then almost all objects of the first hierarchical level of the collection (collection directly from the users) were set up. In the other case of the proportion of costs the first level of the collection is not necessary, because it is replaceable by the more expensive transportation directly to the objects of the second or lower hierarchical level. In the second case the effect of the proportion of the logistics and environmental risk costs were analysed. In this case the analysis resulted to the followings: if the logistics costs are significantly higher than the total environmental risk costs, then because of the constant infrastructure costs the preference of logistics operations depends on the proportion of the environmental risk costs caused by of out of time recycled products and transportation. In the third case of the analysis the effect of the proportion of infrastructure and environmental risk costs were examined. If the infrastructure costs are significantly lower than the environmental risk costs, then almost all objects of the first hierarchical level of the collection (collection directly from the users) were set up. In the other case of the proportion of costs the first collection phase will be shifted near to the last hierarchical level of the supply chain to avoid a very high infrastructure set up and operation cost. The advantages of the presented model and solution method can be summarised in the followings: the model makes it possible to decide the structure of the inverse supply chain (which object to open or close); reduces infrastructure cost, especially for supply chain with high specific fixed costs; reduces the environmental risk cost through finding an optimal balance between number of objects of the system and out of time recycled products, reduces the logistics costs through determining the optimal quantitative parameters of material flow operations. The future of this research work is the use of differentiated lead-time, which makes it possible to take into consideration the above mentioned non-linear infrastructure, transportation, warehousing and environmental risk costs in the case of a given product portfolio segmented by lead-time. This publication was supported by the National Office for Research and Technology within the frame of Pázmány Péter programme. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Office for Research and Technology. Literature: [1] H. F. Lund: McGraw-Hill Recycling Handbook. McGraw-Hill. 2000. [2] P. T. Williams: Waste Treatment and Disposal. John Wiley and Sons Ltd. 2005. [3] M. Christopher: Logistics & Supply Chain Management: creating value-adding networks. Pearson Education [4] A. Gungor, S. M. Gupta: Issues in environmentally conscious manufacturing and product recovery: a survey. Computers & Industrial Engineering. Volume 36. Issue 4. 1999. pp. 811-853. [5] H. C. Zhang, T. C. Kuo, H. Lu, S. H. Huang: Environmentally conscious design and manufacturing: A state-of-the-art survey. Journal of Manufacturing Systems. Volume 16. Issue 5. 1997. pp. 352-371. [6] P. Veerakamolmal, S. Gupta: Design for Disassembly, Reuse, and Recycling. Green Electronics/Green Bottom Line. 2000. pp. 69-82. [7] A. Rushton, P. Croucher, P. Baker: The Handbook of Logistics and Distribution Management. Kogan P.page Limited. 2006. [8] H. Stadtler, C. Kilger: Supply Chain Management and Advanced Planning: Concepts, Models, Software, and Case Studies. Springer. 2005.

Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

ERIC Educational Resources Information Center

Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

2014-01-01

This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

Item Vector Plots for the Multidimensional Three-Parameter Logistic Model

ERIC Educational Resources Information Center

Bryant, Damon; Davis, Larry

2011-01-01

This brief technical note describes how to construct item vector plots for dichotomously scored items fitting the multidimensional three-parameter logistic model (M3PLM). As multidimensional item response theory (MIRT) shows promise of being a very useful framework in the test development life cycle, graphical tools that facilitate understanding…

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.

2010-01-01

Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…

Using a Video Game to Teach Supply Chain and Logistics Management

ERIC Educational Resources Information Center

Liu, Chiung-Lin

2017-01-01

This study used OpenTTD, a video game that supports in-depth experiential learning, to evaluate undergraduate students' opinions regarding supply chain and logistics management learning. The 101 undergraduate participants were assigned to either an experimental group or a control group. From the post-test questionnaires, the analytical results…

Label-noise resistant logistic regression for functional data classification with an application to Alzheimer's disease study.

PubMed

Lee, Seokho; Shin, Hyejin; Lee, Sang Han

2016-12-01

Alzheimer's disease (AD) is usually diagnosed by clinicians through cognitive and functional performance test with a potential risk of misdiagnosis. Since the progression of AD is known to cause structural changes in the corpus callosum (CC), the CC thickness can be used as a functional covariate in AD classification problem for a diagnosis. However, misclassified class labels negatively impact the classification performance. Motivated by AD-CC association studies, we propose a logistic regression for functional data classification that is robust to misdiagnosis or label noise. Specifically, our logistic regression model is constructed by adopting individual intercepts to functional logistic regression model. This approach enables to indicate which observations are possibly mislabeled and also lead to a robust and efficient classifier. An effective algorithm using MM algorithm provides simple closed-form update formulas. We test our method using synthetic datasets to demonstrate its superiority over an existing method, and apply it to differentiating patients with AD from healthy normals based on CC from MRI. © 2016, The International Biometric Society.

A logistics evaluation of visual acuity as applied to the Bailey-Lovie chart.

PubMed

Pierscionek, B K; Weale, R A

1999-11-01

To discover whether as a result of the increasing use of the Bailey-Lovie chart some classes of patients may not be affected by the crowding of the smaller test characters, whose spacing is proportional to their size; and to determine acuities with a logistic function so that all of a patient's responses may be utilized. 112 patients were tested both with the original chart and one in which the horizontal distance is kept constant, i.e., the letters are arranged in vertical columns. All of a patient's responses were recorded so that the constants of the logistic function might be determined. No difference was found for very high and very low acuity scores, but, for intermediate ones, the vertical columns yielded acuity ratings increased by some 13%. The use of the logistics function was successful in that the correlation between stimulus and response was between 0.9 and 1 for some 80% of those examined. A constant horizontal spacing may be of advantage to some patients with a conventionally measured visual acuity of approximately 0.9.

Modeling the pressure inactivation of Escherichia coli and Salmonella typhimurium in sapote mamey ( Pouteria sapota (Jacq.) H.E. Moore & Stearn) pulp.

PubMed

Saucedo-Reyes, Daniela; Carrillo-Salazar, José A; Román-Padilla, Lizbeth; Saucedo-Veloz, Crescenciano; Reyes-Santamaría, María I; Ramírez-Gilly, Mariana; Tecante, Alberto

2018-03-01

High hydrostatic pressure inactivation kinetics of Escherichia coli ATCC 25922 and Salmonella enterica subsp. enterica serovar Typhimurium ATCC 14028 ( S. typhimurium) in a low acid mamey pulp at four pressure levels (300, 350, 400, and 450 MPa), different exposure times (0-8 min), and temperature of 25 ± 2℃ were obtained. Survival curves showed deviations from linearity in the form of a tail (upward concavity). The primary models tested were the Weibull model, the modified Gompertz equation, and the biphasic model. The Weibull model gave the best goodness of fit ( R 2 adj  > 0.956, root mean square error < 0.290) in the modeling and the lowest Akaike information criterion value. Exponential-logistic and exponential decay models, and Bigelow-type and an empirical models for b'( P) and n( P) parameters, respectively, were tested as alternative secondary models. The process validation considered the two- and one-step nonlinear regressions for making predictions of the survival fraction; both regression types provided an adequate goodness of fit and the one-step nonlinear regression clearly reduced fitting errors. The best candidate model according to the Akaike theory information, with better accuracy and more reliable predictions was the Weibull model integrated by the exponential-logistic and exponential decay secondary models as a function of time and pressure (two-step procedure) or incorporated as one equation (one-step procedure). Both mathematical expressions were used to determine the t d parameter, where the desired reductions ( 5D) (considering d = 5 ( t 5 ) as the criterion of 5 Log 10 reduction (5 D)) in both microorganisms are attainable at 400 MPa for 5.487 ± 0.488 or 5.950 ± 0.329 min, respectively, for the one- or two-step nonlinear procedure.

A review on prognostic techniques for non-stationary and non-linear rotating systems

NASA Astrophysics Data System (ADS)

Kan, Man Shan; Tan, Andy C. C.; Mathew, Joseph

2015-10-01

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

DQM: Decentralized Quadratically Approximated Alternating Direction Method of Multipliers

NASA Astrophysics Data System (ADS)

Mokhtari, Aryan; Shi, Wei; Ling, Qing; Ribeiro, Alejandro

2016-10-01

This paper considers decentralized consensus optimization problems where nodes of a network have access to different summands of a global objective function. Nodes cooperate to minimize the global objective by exchanging information with neighbors only. A decentralized version of the alternating directions method of multipliers (DADMM) is a common method for solving this category of problems. DADMM exhibits linear convergence rate to the optimal objective but its implementation requires solving a convex optimization problem at each iteration. This can be computationally costly and may result in large overall convergence times. The decentralized quadratically approximated ADMM algorithm (DQM), which minimizes a quadratic approximation of the objective function that DADMM minimizes at each iteration, is proposed here. The consequent reduction in computational time is shown to have minimal effect on convergence properties. Convergence still proceeds at a linear rate with a guaranteed constant that is asymptotically equivalent to the DADMM linear convergence rate constant. Numerical results demonstrate advantages of DQM relative to DADMM and other alternatives in a logistic regression problem.

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Changes in the selection differential exerted on a marine snail during the ontogeny of a predatory shore crab.

PubMed

Pakes, D; Boulding, E G

2010-08-01

Empirical estimates of selection gradients caused by predators are common, yet no one has quantified how these estimates vary with predator ontogeny. We used logistic regression to investigate how selection on gastropod shell thickness changed with predator size. Only small and medium purple shore crabs (Hemigrapsus nudus) exerted a linear selection gradient for increased shell-thickness within a single population of the intertidal snail (Littorina subrotundata). The shape of the fitness function for shell thickness was confirmed to be linear for small and medium crabs but was humped for large male crabs, suggesting no directional selection. A second experiment using two prey species to amplify shell thickness differences established that the selection differential on adult snails decreased linearly as crab size increased. We observed differences in size distribution and sex ratios among three natural shore crab populations that may cause spatial and temporal variation in predator-mediated selection on local snail populations.

Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

PubMed Central

Rosenblum, Michael; van der Laan, Mark J.

2010-01-01

Models, such as logistic regression and Poisson regression models, are often used to estimate treatment effects in randomized trials. These models leverage information in variables collected before randomization, in order to obtain more precise estimates of treatment effects. However, there is the danger that model misspecification will lead to bias. We show that certain easy to compute, model-based estimators are asymptotically unbiased even when the working model used is arbitrarily misspecified. Furthermore, these estimators are locally efficient. As a special case of our main result, we consider a simple Poisson working model containing only main terms; in this case, we prove the maximum likelihood estimate of the coefficient corresponding to the treatment variable is an asymptotically unbiased estimator of the marginal log rate ratio, even when the working model is arbitrarily misspecified. This is the log-linear analog of ANCOVA for linear models. Our results demonstrate one application of targeted maximum likelihood estimation. PMID:20628636

HRCT findings of collagen vascular disease-related interstitial pneumonia (CVD-IP): a comparative study among individual underlying diseases.

PubMed

Tanaka, N; Kunihiro, Y; Kubo, M; Kawano, R; Oishi, K; Ueda, K; Gondo, T

2018-05-29

To identify characteristic high-resolution computed tomography (CT) findings for individual collagen vascular disease (CVD)-related interstitial pneumonias (IPs). The HRCT findings of 187 patients with CVD, including 55 patients with rheumatoid arthritis (RA), 50 with systemic sclerosis (SSc), 46 with polymyositis/dermatomyositis (PM/DM), 15 with mixed connective tissue disease, 11 with primary Sjögren's syndrome, and 10 with systemic lupus erythematosus, were evaluated. Lung parenchymal abnormalities were compared among CVDs using χ 2 test, Kruskal-Wallis test, and multiple logistic regression analysis. A CT-pathology correlation was performed in 23 patients. In RA-IP, honeycombing was identified as the significant indicator based on multiple logistic regression analyses. Traction bronchiectasis (81.8%) was further identified as the most frequent finding based on χ 2 test. In SSc IP, lymph node enlargement and oesophageal dilatation were identified as the indicators based on multiple logistic regression analyses, and ground-glass opacity (GGO) was the most extensive based on Kruskal-Wallis test, which reflects the higher frequency of the pathological nonspecific interstitial pneumonia (NSIP) pattern present in the CT-pathology correlation. In PM/DM IP, airspace consolidation and the absence of honeycombing were identified as the indicators based on multiple logistic regression analyses, and predominance of consolidation over GGO (32.6%) and predominant subpleural distribution of GGO/consolidation (41.3%) were further identified as the most frequent findings based on χ 2 test, which reflects the higher frequency of the pathological NSIP and/or the organising pneumonia patterns present in the CT-pathology correlation. Several characteristic high-resolution CT findings with utility for estimating underlying CVD were identified. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Serum osteocalcin is significantly related to indices of obesity and lipid profile in Malaysian men.

PubMed

Chin, Kok-Yong; Ima-Nirwana, Soelaiman; Mohamed, Isa Naina; Ahmad, Fairus; Ramli, Elvy Suhana Mohd; Aminuddin, Amilia; Ngah, Wan Zurinah Wan

2014-01-01

Recent studies revealed a possible reciprocal relationship between the skeletal system and obesity and lipid metabolism, mediated by osteocalcin, an osteoblast-specific protein. This study aimed to validate the relationship between serum osteocalcin and indices of obesity and lipid parameters in a group of Malaysian men. A total of 373 men from the Malaysian Aging Male Study were included in the analysis. Data on subjects' demography, body mass index (BMI), body fat (BF) mass, waist circumference (WC), serum osteocalcin and fasting lipid levels were collected. Bioelectrical impendence (BIA) method was used to estimate BF. Multiple linear and binary logistic regression analyses were performed to analyze the association between serum osteocalcin and the aforementioned variables, with adjustment for age, ethnicity and BMI. Multiple regression results indicated that weight, BMI, BF mass, BF %, WC were significantly and negatively associated with serum osteocalcin (p < 0.001). There was a significant positive association between serum osteocalcin and high density lipoprotein (HDL) cholesterol (p = 0.032). Binary logistic results indicated that subjects with low serum osteocalcin level were more likely to be associated with high BMI (obese and overweight), high BF%, high WC and low HDL cholesterol (p < 0.05). Subjects with high osteocalcin level also demonstrated high total cholesterol level (p < 0.05) but this association was probably driven by high HDL level. These variables were not associated with serum C-terminal of telopeptide crosslinks in the subjects (p > 0.05). Serum osteocalcin is associated with indices of obesity and HDL level in men. These relationships should be validated by a longitudinal study, with comprehensive hormone profile testing.

Datamining approaches for modeling tumor control probability.

PubMed

Naqa, Issam El; Deasy, Joseph O; Mu, Yi; Huang, Ellen; Hope, Andrew J; Lindsay, Patricia E; Apte, Aditya; Alaly, James; Bradley, Jeffrey D

2010-11-01

Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs=0.68 on leave-one-out testing compared to logistic regression (rs=0.4), Poisson-based TCP (rs=0.33), and cell kill equivalent uniform dose model (rs=0.17). The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications.

The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes

PubMed Central

Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

2018-01-01

INTRODUCTION: Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. AIM: The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. METHODS: This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. RESULTS: The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). CONCLUSION: Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour. PMID:29731945

Dedicated magnetic resonance imaging in the radiotherapy clinic.

PubMed

Karlsson, Mikael; Karlsson, Magnus G; Nyholm, Tufve; Amies, Christopher; Zackrisson, Björn

2009-06-01

To introduce a novel technology arrangement in an integrated environment and outline the logistics model needed to incorporate dedicated magnetic resonance (MR) imaging in the radiotherapy workflow. An initial attempt was made to analyze the value and feasibility of MR-only imaging compared to computed tomography (CT) imaging, testing the assumption that MR is a better choice for target and healthy tissue delineation in radiotherapy. A 1.5-T MR unit with a 70-cm-bore size was installed close to a linear accelerator, and a special trolley was developed for transporting patients who were fixated in advance between the MR unit and the accelerator. New MR-based workflow procedures were developed and evaluated. MR-only treatment planning has been facilitated, thus avoiding all registration errors between CT and MR scans, but several new aspects of MR imaging must be considered. Electron density information must be obtained by other methods. Generation of digitally reconstructed radiographs (DRR) for x-ray setup verification is not straight forward, and reliable corrections of geometrical distortions must be applied. The feasibility of MR imaging virtual simulation has been demonstrated, but a key challenge to overcome is correct determination of the skeleton, which is often needed for the traditional approach of beam modeling. The trolley solution allows for a highly precise setup for soft tissue tumors without the invasive handling of radiopaque markers. The new logistics model with an integrated MR unit is efficient and will allow for improved tumor definition and geometrical precision without a significant loss of dosimetric accuracy. The most significant development needed is improved bone imaging.

40 CFR Appendix B to Part 75 - Quality Assurance and Quality Control Procedures

Code of Federal Regulations, 2012 CFR

2012-07-01

... Systems 1.2.1Calibration Error Test and Linearity Check Procedures Keep a written record of the procedures used for daily calibration error tests and linearity checks (e.g., how gases are to be injected..., and when calibration adjustments should be made). Identify any calibration error test and linearity...

40 CFR Appendix B to Part 75 - Quality Assurance and Quality Control Procedures

Code of Federal Regulations, 2013 CFR

2013-07-01

... Systems 1.2.1Calibration Error Test and Linearity Check Procedures Keep a written record of the procedures used for daily calibration error tests and linearity checks (e.g., how gases are to be injected..., and when calibration adjustments should be made). Identify any calibration error test and linearity...

On the efficiency of the image encryption and decryption by using logistic-sine chaotic system and logistic-tent chaotic system

NASA Astrophysics Data System (ADS)

Chiun, Lee Chia; Mandangan, Arif; Daud, Muhamad Azlan; Hussin, Che Haziqah Che

2017-04-01

We may secure the content of text, audio, image and video during their transmission from one party to another party via an open channel such as the internet by using cryptograph. Logistic-Sine System (LSS) is a combination on two 1D chaotic maps which are Logistic Map and Sine Map. By applying the LSS into cryptography, the image encryption and decryption can be performed. This study is focusing on the performance test of the image encryption and decryption processes by using the LSS. For comparison purpose, we compare the performance of the encryption and decryption by using two different chaotic systems, which are the LSS and Logistic-Tent System (LTS). The result shows that system with LSS is less efficient than LTS in term of encryption time but both systems have similar efficiency in term of decryption time.

Operation CASTLE. Report of the Manager Santa Fe Operations. Extracted Version.

DTIC Science & Technology

Nuclear explosion testing, *Test facilities, *Management planning and control, Pacific Ocean, Eniwetok Atoll, Bikini Atoll, Marshall Islands , Organizations, Construction, Operation, Management, Logistics support, Costs

Naval Research Logistics Quarterly. Volume 28, Number 4,

DTIC Science & Technology

1981-12-01

Fan [31 and an observation by Meijerink and van der Vorst [181 guarantee that after pivoting on any diagonal element of a diagonally dominant M- matrix...Science, 3, 255-269 (1957). 1181 Meijerink, J. and H. Van der Vorst, "An Iterative Solution Method for Linear Systems of which the Coefficient Matrix Is a...Hee, K., A. Hordijk and J. Van der Wal, "Successive Approximations for Convergent Dynamic Programming," in Markov Decision Theory, H. Tijms and J

Statistical Methods for Quality Control of Steel Coils Manufacturing Process using Generalized Linear Models

NASA Astrophysics Data System (ADS)

García-Díaz, J. Carlos

2009-11-01

Fault detection and diagnosis is an important problem in process engineering. Process equipments are subject to malfunctions during operation. Galvanized steel is a value added product, furnishing effective performance by combining the corrosion resistance of zinc with the strength and formability of steel. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing and the increasingly stringent quality requirements in automotive industry has also demanded ongoing efforts in process control to make the process more robust. When faults occur, they change the relationship among these observed variables. This work compares different statistical regression models proposed in the literature for estimating the quality of galvanized steel coils on the basis of short time histories. Data for 26 batches were available. Five variables were selected for monitoring the process: the steel strip velocity, four bath temperatures and bath level. The entire data consisting of 48 galvanized steel coils was divided into sets. The first training data set was 25 conforming coils and the second data set was 23 nonconforming coils. Logistic regression is a modeling tool in which the dependent variable is categorical. In most applications, the dependent variable is binary. The results show that the logistic generalized linear models do provide good estimates of quality coils and can be useful for quality control in manufacturing process.

Long-Term Effect of Exposure to a Friend's Adolescent Childbirth on Fertility, Education, and Earnings.

PubMed

Kapinos, Kandice A; Yakusheva, Olga

2016-09-01

To examine the long-term effect of a female adolescent's exposure to a peer's childbirth on fertility, schooling, and earnings. Estimating causal peer effects in fertility is challenging because the exposure variable (peer pregnancy and childbirth) is nonrandomly assigned. Miscarriages in early pregnancy occur spontaneously in a significant proportion of pregnancies and, therefore, create a natural experiment within which the causal effect of childbirth can be examined. This exploratory study compared adjusted fertility, educational, and labor market outcomes of female adolescents whose adolescent pregnant friend gave birth to female adolescents whose pregnant friend miscarried. Longitudinal data from the National Longitudinal Study of Adolescent Health were analyzed using logistic, ordinal logistic, linear, and log-linear regressions. Females whose adolescent pregnant friends gave birth (instead of miscarried) had decreased adolescent sexual activity, pregnancy, and teen childbearing and increased educational attainment, but there were no significant long-term effects on total fertility or differences in labor market outcomes, relative to females whose pregnant adolescent friend miscarried. Adolescent females appear to learn vicariously from teen childbearing experiences of their friends, resulting in delayed childbearing and higher educational attainment. Interventions that expose adolescents to the reality of teen motherhood may be an effective way of reducing the rates of teen childbearing and improving schooling. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Prevalence and correlates of cognitive impairment in kidney transplant recipients.

PubMed

Gupta, Aditi; Mahnken, Jonathan D; Johnson, David K; Thomas, Tashra S; Subramaniam, Dipti; Polshak, Tyler; Gani, Imran; John Chen, G; Burns, Jeffrey M; Sarnak, Mark J

2017-05-12

There is a high prevalence of cognitive impairment in dialysis patients. The prevalence of cognitive impairment after kidney transplantation is unknown. Study Design: Cross-sectional study. Single center study of prevalent kidney transplant recipients from a transplant clinic in a large academic center. Assessment of cognition using the Montreal Cognitive Assessment (MoCA). Demographic and clinical variables associated with cognitive impairment were also examined. Outcomes and Measurements: a) Prevalence of cognitive impairment defined by a MoCA score of <26. b) Multivariable linear and logistic regression to examine the association of demographic and clinical factors with cognitive impairment. Data from 226 patients were analyzed. Mean (SD) age was 54 (13.4) years, 73% were white, 60% were male, 37% had diabetes, 58% had an education level of college or above, and the mean (SD) time since kidney transplant was 3.4 (4.1) years. The prevalence of cognitive impairment was 58.0%. Multivariable linear regression demonstrated that older age, male gender and absence of diabetes were associated with lower MoCA scores (p < 0.01 for all). Estimated glomerular filtration rate (eGFR) was not associated with level of cognition. The logistic regression analysis confirmed the association of older age with cognitive impairment. Cognitive impairment is common in prevalent kidney transplant recipients, at a younger age compared to general population, and is associated with certain demographic variables, but not level of eGFR.

Human papillomavirus prevalence, viral load and pre-cancerous lesions of the cervix in women initiating highly active antiretroviral therapy in South Africa: a cross-sectional study.

PubMed

Moodley, Jennifer R; Constant, Deborah; Hoffman, Margaret; Salimo, Anna; Allan, Bruce; Rybicki, Ed; Hitzeroth, Inga; Williamson, Anna-Lise

2009-08-07

Cervical cancer and infection with human immunodeficiency virus (HIV) are both important public health problems in South Africa (SA). The aim of this study was to determine the prevalence of cervical squamous intraepithelial lesions (SILs), high-risk human papillomavirus (HR-HPV), HPV viral load and HPV genotypes in HIV positive women initiating anti-retroviral (ARV) therapy. A cross-sectional survey was conducted at an anti-retroviral (ARV) treatment clinic in Cape Town, SA in 2007. Cervical specimens were taken for cytological analysis and HPV testing. The Digene Hybrid Capture 2 (HC2) test was used to detect HR-HPV. Relative light units (RLU) were used as a measure of HPV viral load. HPV types were determined using the Roche Linear Array HPV Genotyping test. Crude associations with abnormal cytology were tested and multiple logistic regression was used to determine independent risk factors for abnormal cytology. The median age of the 109 participants was 31 years, the median CD4 count was 125/mm3, 66.3% had an abnormal Pap smear, the HR-HPV prevalence was 78.9% (Digene), the median HPV viral load was 181.1 RLU (HC2 positive samples only) and 78.4% had multiple genotypes. Among women with abnormal smears the most prevalent HR-HPV types were HPV types 16, 58 and 51, all with a prevalence of 28.5%. On univariate analysis HR-HPV, multiple HPV types and HPV viral load were significantly associated with the presence of low and high-grade SILs (LSIL/HSIL). The multivariate logistic regression showed that HPV viral load was associated with an increased odds of LSIL/HSIL, odds ratio of 10.7 (95% CI 2.0 - 57.7) for those that were HC2 positive and had a viral load of 181.1 RLU. Women initiating ARVs have a high prevalence of abnormal Pap smears and HR-HPV. Our results underscore the need for locally relevant, rigorous screening protocols for the increasing numbers of women accessing ARV therapy so that the benefits of ARVs are not partially offset by an excess risk in cervical cancer.

Genetic prediction of type 2 diabetes using deep neural network.

PubMed

Kim, J; Kim, J; Kwak, M J; Bajaj, M

2018-04-01

Type 2 diabetes (T2DM) has strong heritability but genetic models to explain heritability have been challenging. We tested deep neural network (DNN) to predict T2DM using the nested case-control study of Nurses' Health Study (3326 females, 45.6% T2DM) and Health Professionals Follow-up Study (2502 males, 46.5% T2DM). We selected 96, 214, 399, and 678 single-nucleotide polymorphism (SNPs) through Fisher's exact test and L1-penalized logistic regression. We split each dataset randomly in 4:1 to train prediction models and test their performance. DNN and logistic regressions showed better area under the curve (AUC) of ROC curves than the clinical model when 399 or more SNPs included. DNN was superior than logistic regressions in AUC with 399 or more SNPs in male and 678 SNPs in female. Addition of clinical factors consistently increased AUC of DNN but failed to improve logistic regressions with 214 or more SNPs. In conclusion, we show that DNN can be a versatile tool to predict T2DM incorporating large numbers of SNPs and clinical information. Limitations include a relatively small number of the subjects mostly of European ethnicity. Further studies are warranted to confirm and improve performance of genetic prediction models using DNN in different ethnic groups. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Accuracy of Bayes and Logistic Regression Subscale Probabilities for Educational and Certification Tests

ERIC Educational Resources Information Center

Rudner, Lawrence

2016-01-01

In the machine learning literature, it is commonly accepted as fact that as calibration sample sizes increase, Naïve Bayes classifiers initially outperform Logistic Regression classifiers in terms of classification accuracy. Applied to subtests from an on-line final examination and from a highly regarded certification examination, this study shows…

School Exits in the Milwaukee Parental Choice Program: Evidence of a Marketplace?

ERIC Educational Resources Information Center

Ford, Michael

2011-01-01

This article examines whether the large number of school exits from the Milwaukee school voucher program is evidence of a marketplace. Two logistic regression and multinomial logistic regression models tested the relation between the inability to draw large numbers of voucher students and the ability for a private school to remain viable. Data on…

Physical activity after myocardial infarction: is it related to mental health?

PubMed

Rius-Ottenheim, Nathaly; Geleijnse, Johanna M; Kromhout, Daan; van der Mast, Roos C; Zitman, Frans G; Giltay, Erik J

2013-06-01

Physical inactivity and poor mental wellbeing are associated with poorer prognoses in patients with cardiovascular disease. We aimed to analyse the cross-sectional and prospective associations between physical activity and mental wellbeing in patients with a history of myocardial infarction. Longitudinal, observational study. We investigated 600 older subjects with a history of myocardial infarction (age range 60-80 years) who participated in the Alpha Omega Trial (AOT). They were tested twice at baseline and at 40 months follow-up for physical activity - with the Physical Activity Scale for the Elderly (PASE); depressive symptoms - with the Geriatric Depression Scale (GDS-15); and dispositional optimism - with the Life Orientation Test (LOT-R). Linear (multilevel) and logistic regression analyses were used to examine cross-sectional and longitudinal associations. Physical activity was cross-sectionally associated with depressive symptoms (adjusted beta = -0.143; p = 0.001), but not with dispositional optimism (adjusted beta = 0.074; p = 0.07). We found a synchrony of change between physical activity and depressive symptoms (adjusted beta = -0.155; p < 0.001), but not with dispositional optimism (adjusted beta = 0.049; p = 0.24). Baseline physical activity did not predict depressive symptoms at 40 months follow-up. Concordant inverse associations were observed for (changes) in physical activity and depressive symptoms. Physical activity did not predict depressive symptoms or low optimism.

[Central blood pressure and vascular damage].

PubMed

Pérez-Lahiguera, Francisco; Rodilla, Enrique; Costa, José Antonio; Pascual, José María

2015-07-20

The aim of this study was to assess the relationship between central blood pressure and vascular damage. This cross-sectional study involved 393 never treated hypertensive patients (166 women). Clinical blood pressure (BP), 24h blood pressure (BP24h) and central blood pressure (CBP) were measured. Vascular organ damage (VOD) was assessed by calculating the albumin/creatinine ratio (ACR), wave pulse pressure velocity and echocardiographic left ventricular mass index (LVMI). Patients with VOD had higher values of BP, BP24h, and CBP than patients without ACR. When comparing several systolic BP, systolic BP24h had a higher linear correlation with CBP (Z Steiger test: 2.26; P=.02) and LVMI (Z Steiger test: 3.23; P=.01) than PAC. In a multiple regression analysis corrected by age, sex and metabolic syndrome, all pressures were related with VOD but systolic BP24h showed the highest correlation. In a logistic regression analysis, having the highest tercile of systolic BP24h was the stronger predictor of VOD (multivariate odds ratio: 3.4; CI 95%: 2.5-5.5, P=.001). CBP does not have more correlation with VOD than other measurements of peripheral BP. Systolic BP24h is the BP measurement that best predicts VOD. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

Future orientation and suicide ideation and attempts in depressed adults ages 50 and over.

PubMed

Hirsch, Jameson K; Duberstein, Paul R; Conner, Kenneth R; Heisel, Marnin J; Beckman, Anthony; Franus, Nathan; Conwell, Yeates

2006-09-01

The objective of this study was to test the hypothesis that future orientation is associated with lower levels of suicide ideation and lower likelihood of suicide attempt in a sample of patients in treatment for major depression. Two hundred two participants (116 female, 57%) ages 50-88 years were recruited from inpatient and outpatient settings. All were diagnosed with major depression using a structured diagnostic interview. Suicide ideation was assessed with the Scale for Suicide Ideation (both current and worst point ratings), and a measure of future orientation was created to assess future expectancies. The authors predicted that greater future orientation would be associated with less current and worst point suicide ideation, and would distinguish current and lifetime suicide attempters from nonattempters. Hypotheses were tested using multivariate logistic regression and linear regression analyses that accounted for age, gender, hopelessness, and depression. As hypothesized, higher future orientation scores were associated with lower current suicidal ideation, less intense suicidal ideation at its worst point, and lower probability of a history of attempted suicide after accounting for covariates. Future orientation was not associated with current attempt status. Future orientation holds promise as a cognitive variable associated with decreased suicide risk; a better understanding of its putative protective role is needed. Treatments designed to enhance future orientation might decrease suicide risk.

The role of family and community involvement in the development and implementation of school nutrition and physical activity policy.

PubMed

Kehm, Rebecca; Davey, Cynthia S; Nanney, Marilyn S

2015-02-01

Although there are several evidence-based recommendations directed at improving nutrition and physical activity standards in schools, these guidelines have not been uniformly adopted throughout the United States. Consequently, research is needed to identify facilitators promoting schools to implement these recommendations. Therefore, this study analyzed the 2008 School Health Profiles Principal Survey (Profiles) to explore the role of family and community involvement in school nutrition and physical activity standards. Survey data on nutrition and physical activity policies, as well as family and community involvement, were available for 28 states, representing 6732 secondary schools. One-factor analysis of variance (ANOVA), 2-sample t-tests, Pearson's chi-square tests, and multiple logistic and linear regression models were employed in this analysis. Family and community involvement were associated with schools more frequently utilizing healthy eating strategies and offering students healthier food options. Further, involvement was associated with greater support for physical education staff and more intramural sports opportunities for students. Though family and community involvement have the potential to have a positive influence on school nutrition and physical activity policies and practices, involvement remains low in schools. Increased efforts are needed to encourage collaboration among schools, families, and communities to ensure the highest health standards for all students. © 2015, American School Health Association.

Life-long protein malnutrition in the rat (Rattus norvegicus) results in altered patterns of craniofacial growth and smaller individuals

PubMed Central

Lobe, Shannon L; Bernstein, Marica C; German, Rebecca Z

2006-01-01

Dietary protein is a limiting factor in mammalian growth, significantly affecting the non-linear trajectories of skeletal growth. Young females may be particularly vulnerable to protein malnutrition if the restriction is not lifted before they become reproductive. With such early malnutrition, limited amino acids would be partitioned between two physiological objectives, successful reproduction vs. continued growth. Thus, the consequences of protein malnutrition could affect more than one generation. However, few studies have quantified these cross-generational effects. Our objective was to test for differences in skeletal growth in a second generation of malnourished rats compared with rats malnourished only post-weaning, the first generation and with controls. In this longitudinal study we modelled the growth of 22 craniofacial measurements with the logistic Gompertz equation, and tested for differences in the equation's parameters among the diet groups. The female offspring of post-weaning malnourished dams did not catch up in size to the first generation or to controls, although certain aspects of their craniofacial skeleton were less affected than others. The second generation's growth trajectories resembled the longer and slower growth of the first malnourished generation. There was a complex interaction between developmental processes and early nutritional environment, which affected variation of adult size. PMID:16761979

Snacks With Nutrition Labels: Tastiness Perception, Healthiness Perception, and Willingness to Pay by Norwegian Adolescents.

PubMed

Wang, Qing; Oostindjer, Marije; Amdam, Gro V; Egelandsdal, Bjørg

2016-02-01

Consumers tend to have the perception that healthy equals less tasty. This study aimed to identify whether information provided by the Keyhole symbol, a widely used front-of-package symbol in Nordic countries to indicate nutritional content, and percent daily values (%DVs) affect Norwegian adolescents' perception of the healthiness of snacks and their intention to buy them. Two tasks were used to evaluate adolescents' perception of snacks with the Keyhole symbol: with %DVs or with no nutrition label. A third task was used to test their abilities to use %DVs (pairwise selections). A survey obtained personal attributes. A total of 566 Norwegian adolescents. Taste perception, health perception, and ability to use %DVs. Linear mixed models and logistic models that tested effects of labels and personal attributes on main outcome measures. The Keyhole symbol increased health perception without influencing taste perception of snacks. Norwegian adolescents had limited abilities to use information from the %DVs correctly to identify healthier foods. Norwegian adolescents had a positive perception of the Keyhole symbols. Keyhole symbols as a simple, heuristic front-of-package label have potential as an information strategy that may influence self-efficacy in promoting healthy snack choices among adolescents. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Health status of radiation exposed residents living near the Semipalatinsk Nuclear Test Site based on health assessment by interview.

PubMed

Hirabayashi, Kyoko; Kawano, Noriyuki; Ohtaki, Megu; Harada, Yuka; Harada, Hironori; Muldagaliyev, Talgat; Apsalikov, Kazbek; Hoshi, Masaharu

2008-03-01

The purpose of the present paper is to examine the aftereffects of radiation exposure on residents of villages near the Semipalatinsk Nuclear Test Site (SNTS) in Kazakhstan. Our Hiroshima University (Japan) research team began field research in 2002 by means of health assessments conducted via interviews. We focus on persons who responded to questions concerning their medical conditions and symptoms. In this paper, we summarize and analyze, using multiple linear logistic regression analysis, the answers obtained by questionnaire survey. The results show: (1) 31% of the residents reported that they felt bad or were in very poor health. (2) Residents living in villages having higher radiation levels were more likely to report having poor or very poor health, minor complaints such as loss of sleep, headaches, nighttime sweating and swollen arms or legs, and the need for nursing care in performing activities of daily living. (3) Symptoms reported by over 40% of the respondents included high blood pressure, heart disease and arthralgia/ lower back pain/ arthritis. Our results suggest that radiation exposure in the Semipalatinsk area is one of the causes of poor health in general among residents. There is also a possibility that radiation exposure has influenced the incidence of some specific medical conditions.

Development of a Statistical Model for Forecasting Episodes of Visibility Degradation in the Denver Metropolitan Area.

NASA Astrophysics Data System (ADS)

Reddy, P. J.; Barbarick, D. E.; Osterburg, R. D.

1995-03-01

In 1990, the State of Colorado implemented a visibility standard of 0.076 km1 of beta extinction for the Denver metropolitan area. Meteorologists with Colorado's Air Pollution Control Division forecast high pollution days associated with visibility impairment as well as those due to high levels of the federal criteria pollutants. Visibility forecasts are made from a few hours up to about 26 h in advance of the period of interest. Here we discuss the key microscale, mesoscale, and synoptic-scale features associated with episodes of visibility impairment. Data from special studies, case studies, and the 22 NOAA Program for Regional Observing and Forecasting Services mesonet sites have been invaluable in identifying patterns associated with extremes in visibility conditions. A preliminary statistical forecast model has been developed using variables that represent many of these patterns. Six variables were selected from an initial pool of 27 to be used in a model based on linear logistic regression. These six variables include forecast measures of snow cover, surface pressures and a surface pressure gradient in eastern Colorado, relative humidity, and 500-mb ridge position. The initial testing of the model has been encouraging. The model correctly predicted 76% of the good visibility days and 67% of the poor visibility days for a test set of 171 days.

[Impact of level of physical activity on healthcare utilization among Korean adults].

PubMed

Kim, Jiyun; Park, Seungmi

2012-04-01

This study was done to identify the impact of physical activity on healthcare utilization among Korean adults. Drawing from the 2008 Korean National Health and Nutrition Examination Survey (NHANES IV-2), data from 6,521 adults who completed the Health Interview and Health Behavior Surveys were analyzed. Association between physical activity and healthcare utilization was tested using the χ²-test. Multiple logistic regression analysis was used to calculate the odds ratios of using outpatient and inpatient healthcare for different levels of physical activity after adjusting for predisposing, enabling, and need factors. A generalized linear model applying a negative binomial distribution was used to determine how the level of physical activity was related to use of outpatient and inpatient healthcare. Physically active participants were 16% less likely to use outpatient healthcare (OR, 0.84; 95% CI, 0.74-0.97) and 23% less likely to use inpatient healthcare (OR, 0.77; 95% CI, 0.63-0.93) than physically inactive participants. Levels of outpatient and inpatient healthcare use decreased as levels of physical activity increased, after adjusting for relevant factors. An independent association between being physically active and lower healthcare utilization was ascertained among Korean adults indicating a need to develop nursing intervention programs that encourage regular physical activity.

Evaluation of trade-offs in costs and environmental impacts for returnable packaging implementation

NASA Astrophysics Data System (ADS)

Jarupan, Lerpong; Kamarthi, Sagar V.; Gupta, Surendra M.

2004-02-01

The main thrust of returnable packaging these days is to provide logistical services through transportation and distribution of products and be environmentally friendly. Returnable packaging and reverse logistics concepts have converged to mitigate the adverse effect of packaging materials entering the solid waste stream. Returnable packaging must be designed by considering the trade-offs between costs and environmental impact to satisfy manufacturers and environmentalists alike. The cost of returnable packaging entails such items as materials, manufacturing, collection, storage and disposal. Environmental impacts are explicitly linked with solid waste, air pollution, and water pollution. This paper presents a multi-criteria evaluation technique to assist decision-makers for evaluating the trade-offs in costs and environmental impact during the returnable packaging design process. The proposed evaluation technique involves a combination of multiple objective integer linear programming and analytic hierarchy process. A numerical example is used to illustrate the methodology.

Quantitative Study on Corrosion of Steel Strands Based on Self-Magnetic Flux Leakage.

PubMed

Xia, Runchuan; Zhou, Jianting; Zhang, Hong; Liao, Leng; Zhao, Ruiqiang; Zhang, Zeyu

2018-05-02

This paper proposed a new computing method to quantitatively and non-destructively determine the corrosion of steel strands by analyzing the self-magnetic flux leakage (SMFL) signals from them. The magnetic dipole model and three growth models (Logistic model, Exponential model, and Linear model) were proposed to theoretically analyze the characteristic value of SMFL. Then, the experimental study on the corrosion detection by the magnetic sensor was carried out. The setup of the magnetic scanning device and signal collection method were also introduced. The results show that the Logistic Growth model is verified as the optimal model for calculating the magnetic field with good fitting effects. Combined with the experimental data analysis, the amplitudes of the calculated values ( B xL ( x,z ) curves) agree with the measured values in general. This method provides significant application prospects for the evaluation of the corrosion and the residual bearing capacity of steel strand.

Analytical solution of Luedeking-Piret equation for a batch fermentation obeying Monod growth kinetics.

PubMed

Garnier, Alain; Gaillet, Bruno

2015-12-01

Not so many fermentation mathematical models allow analytical solutions of batch process dynamics. The most widely used is the combination of the logistic microbial growth kinetics with Luedeking-Piret bioproduct synthesis relation. However, the logistic equation is principally based on formalistic similarities and only fits a limited range of fermentation types. In this article, we have developed an analytical solution for the combination of Monod growth kinetics with Luedeking-Piret relation, which can be identified by linear regression and used to simulate batch fermentation evolution. Two classical examples are used to show the quality of fit and the simplicity of the method proposed. A solution for the combination of Haldane substrate-limited growth model combined with Luedeking-Piret relation is also provided. These models could prove useful for the analysis of fermentation data in industry as well as academia. © 2015 Wiley Periodicals, Inc.

Optimising reverse logistics network to support policy-making in the case of Electrical and Electronic Equipment.

PubMed

Achillas, Ch; Vlachokostas, Ch; Aidonis, D; Moussiopoulos, N; Iakovou, E; Banias, G

2010-12-01

Due to the rapid growth of Waste Electrical and Electronic Equipment (WEEE) volumes, as well as the hazardousness of obsolete electr(on)ic goods, this type of waste is now recognised as a priority stream in the developed countries. Policy-making related to the development of the necessary infrastructure and the coordination of all relevant stakeholders is crucial for the efficient management and viability of individually collected waste. This paper presents a decision support tool for policy-makers and regulators to optimise electr(on)ic products' reverse logistics network. To that effect, a Mixed Integer Linear Programming mathematical model is formulated taking into account existing infrastructure of collection points and recycling facilities. The applicability of the developed model is demonstrated employing a real-world case study for the Region of Central Macedonia, Greece. The paper concludes with presenting relevant obtained managerial insights. Copyright © 2010 Elsevier Ltd. All rights reserved.

Neural networks: What non-linearity to choose

NASA Technical Reports Server (NTRS)

Kreinovich, Vladik YA.; Quintana, Chris

1991-01-01

Neural networks are now one of the most successful learning formalisms. Neurons transform inputs (x(sub 1),...,x(sub n)) into an output f(w(sub 1)x(sub 1) + ... + w(sub n)x(sub n)), where f is a non-linear function and w, are adjustable weights. What f to choose? Usually the logistic function is chosen, but sometimes the use of different functions improves the practical efficiency of the network. The problem of choosing f as a mathematical optimization problem is formulated and solved under different optimality criteria. As a result, a list of functions f that are optimal under these criteria are determined. This list includes both the functions that were empirically proved to be the best for some problems, and some new functions that may be worth trying.

[Research on the methods for multi-class kernel CSP-based feature extraction].

PubMed

Wang, Jinjia; Zhang, Lingzhi; Hu, Bei

2012-04-01

To relax the presumption of strictly linear patterns in the common spatial patterns (CSP), we studied the kernel CSP (KCSP). A new multi-class KCSP (MKCSP) approach was proposed in this paper, which combines the kernel approach with multi-class CSP technique. In this approach, we used kernel spatial patterns for each class against all others, and extracted signal components specific to one condition from EEG data sets of multiple conditions. Then we performed classification using the Logistic linear classifier. Brain computer interface (BCI) competition III_3a was used in the experiment. Through the experiment, it can be proved that this approach could decompose the raw EEG singles into spatial patterns extracted from multi-class of single trial EEG, and could obtain good classification results.

4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

PubMed Central

Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

2008-01-01

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

Neuropsychological tests for predicting cognitive decline in older adults

PubMed Central

Baerresen, Kimberly M; Miller, Karen J; Hanson, Eric R; Miller, Justin S; Dye, Richelin V; Hartman, Richard E; Vermeersch, David; Small, Gary W

2015-01-01

Summary Aim To determine neuropsychological tests likely to predict cognitive decline. Methods A sample of nonconverters (n = 106) was compared with those who declined in cognitive status (n = 24). Significant univariate logistic regression prediction models were used to create multivariate logistic regression models to predict decline based on initial neuropsychological testing. Results Rey–Osterrieth Complex Figure Test (RCFT) Retention predicted conversion to mild cognitive impairment (MCI) while baseline Buschke Delay predicted conversion to Alzheimer’s disease (AD). Due to group sample size differences, additional analyses were conducted using a subsample of demographically matched nonconverters. Analyses indicated RCFT Retention predicted conversion to MCI and AD, and Buschke Delay predicted conversion to AD. Conclusion Results suggest RCFT Retention and Buschke Delay may be useful in predicting cognitive decline. PMID:26107318

Linear Equating for the NEAT Design: Parameter Substitution Models and Chained Linear Relationship Models

ERIC Educational Resources Information Center

Kane, Michael T.; Mroch, Andrew A.; Suh, Youngsuk; Ripkey, Douglas R.

2009-01-01

This paper analyzes five linear equating models for the "nonequivalent groups with anchor test" (NEAT) design with internal anchors (i.e., the anchor test is part of the full test). The analysis employs a two-dimensional framework. The first dimension contrasts two general approaches to developing the equating relationship. Under a "parameter…

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

Assessing the Validity of Self-Rated Health with the Short Physical Performance Battery: A Cross-Sectional Analysis of the International Mobility in Aging Study

PubMed Central

Belanger, Emmanuelle; Zunzunegui, Maria–Victoria; Phillips, Susan; Ylli, Alban; Guralnik, Jack

2016-01-01

Objective The aim of this study was to explore the validity of self-rated health across different populations of older adults, when compared to the Short Physical Performance Battery. Design Cross-sectional analysis of the International Mobility in Aging Study. Setting Five locations: Saint-Hyacinthe and Kingston (Canada), Tirana (Albania), Manizales (Colombia), and Natal (Brazil). Participants Older adults between 65 and 74 years old (n = 1,995). Methods The Short Physical Performance Battery (SPPB) was used to measure physical performance. Self-rated health was assessed with one single five-point question. Linear trends between SPPB scores and self-rated health were tested separately for men and women at each of the five international study sites. Poor physical performance (independent variable) (SPPB less than 8) was used in logistic regression models of self-rated health (dependent variable), adjusting for potential covariates. All analyses were stratified by gender and site of origin. Results A significant linear association was found between the mean scores of the Short Physical Performance Battery and ordinal categories of self-rated health across research sites and gender groups. After extensive control for objective physical and mental health indicators and socio-demographic variables, these graded associations became non-significant in some research sites. Conclusion These findings further confirm the validity of SRH as a measure of overall health status in older adults. PMID:27089219

Impact of Dental Disorders and its Influence on Self Esteem Levels among Adolescents.

PubMed

Kaur, Puneet; Singh, Simarpreet; Mathur, Anmol; Makkar, Diljot Kaur; Aggarwal, Vikram Pal; Batra, Manu; Sharma, Anshika; Goyal, Nikita

2017-04-01

Self esteem is more of a psychological concept therefore, even the common dental disorders like dental trauma, tooth loss and untreated carious lesions may affect the self esteem thus influencing the quality of life. This study aims to assess the impact of dental disorders among the adolescents on their self esteem level. The present cross-sectional study was conducted among 10 to 17 years adolescents. In order to obtain a representative sample, multistage sampling technique was used and sample was selected based on Probability Proportional to Enrolment size (PPE). Oral health assessment was carried out using WHO type III examination and self esteem was estimated using the Rosenberg Self Esteem Scale score (RSES). The descriptive and inferential analysis of the data was done by using IBM SPSS software. Logistic and linear regression analysis was executed to test the individual association of different independent clinical variables with self esteem. Total sample of 1140 adolescents with mean age of 14.95 ±2.08 and RSES of 27.09 ±3.12 were considered. Stepwise multiple linear regression analysis was applied and best predictors in relation to RSES in the descending order were Dental Health Component (DHC), Aesthetic Component (AC), dental decay {(aesthetic zone), (masticatory zone)}, tooth loss {(aesthetic zone), (masticatory zone)} and anterior fracture of tooth. It was found that various dental disorders like malocclusion, anterior traumatic tooth, tooth loss and untreated decay causes a profound impact on aesthetics and psychosocial behaviour of adolescents, thus affecting their self esteem.

Interactive influences of neighborhood and individual socioeconomic status on alcohol consumption and problems.

PubMed

Mulia, Nina; Karriker-Jaffe, Katherine J

2012-01-01

To assess cross-level interactions between neighborhood and individual socioeconomic status (SES) on alcohol consumption and problems, and investigate three possible explanations for such interactions, including the double jeopardy, status inconsistency and relative deprivation hypotheses. Data from the 2000 and 2005 US National Alcohol Surveys were linked to the 2000 US Census to define respondent census tracts as disadvantaged, middle-class and advantaged. Risk drinking (consumption exceeding national guidelines), monthly drunkenness and alcohol problems were examined among low-, middle- and high-SES past-year drinkers (n = 8728). Gender-stratified, multiple logistic regression models were employed, and for outcomes with a significant omnibus F-test, linear contrasts were used to interpret interactions. Cross-level SES interactions observed for men indicated that residence in advantaged neighborhoods was associated with markedly elevated odds of risk drinking and drunkenness for low-SES men. Linear contrasts further revealed a nearly 5-fold increased risk for alcohol problems among these men, relative to middle-SES and high-SES men also living in advantaged neighborhoods. Among women, neighborhood disadvantage was related to increased risk for alcohol problems, but there were no significant SES interactions. These findings did not support theories of double jeopardy and status inconsistency. Consistent with the relative deprivation hypothesis, findings highlight alcohol-related health risks among low-SES men living in affluent neighborhoods. Future research should assess whether this pattern extends to other health risk behaviors, investigate causal mechanisms and consider how gender may influence these.

Japanese Experiment Module arrival

NASA Image and Video Library

2007-03-29

Several components for delivery to the International Space Station sit in test stands inside the Space Station Processing Facility highbay. To the right, from back to front, are the Japanese Experiment Module, the Raffaello multi-purpose logistics module, and the European Space Agency's Columbus scientific research module. To the left in front is the starboard truss segment S5. Behind it is the test stand that will hold the Experiment Logistics Module Pressurized Section for the Japanese Experiment Module. The logistics module is one of the components of the Japanese Experiment Module or JEM, also known as Kibo, which means "hope" in Japanese. Kibo comprises six components: two research facilities -- the Pressurized Module and Exposed Facility; a Logistics Module attached to each of them; a Remote Manipulator System; and an Inter-Orbit Communication System unit. Kibo also has a scientific airlock through which experiments are transferred and exposed to the external environment of space. Kibo is Japan's first human space facility and its primary contribution to the station. Kibo will enhance the unique research capabilities of the orbiting complex by providing an additional environment in which astronauts can conduct science experiments. The various components of JEM will be assembled in space over the course of three Space Shuttle missions. The first of those three missions, STS-123, will carry the Experiment Logistics Module Pressurized Section aboard the Space Shuttle Endeavour, targeted for launch in 2007.

Imparting Motion to a Test Object Such as a Motor Vehicle in a Controlled Fashion

NASA Technical Reports Server (NTRS)

Southward, Stephen C. (Inventor); Reubush, Chandler (Inventor); Pittman, Bryan (Inventor); Roehrig, Kurt (Inventor); Gerard, Doug (Inventor)

2014-01-01

An apparatus imparts motion to a test object such as a motor vehicle in a controlled fashion. A base has mounted on it a linear electromagnetic motor having a first end and a second end, the first end being connected to the base. A pneumatic cylinder and piston combination have a first end and a second end, the first end connected to the base so that the pneumatic cylinder and piston combination is generally parallel with the linear electromagnetic motor. The second ends of the linear electromagnetic motor and pneumatic cylinder and piston combination being commonly linked to a mount for the test object. A control system for the linear electromagnetic motor and pneumatic cylinder and piston combination drives the pneumatic cylinder and piston combination to support a substantial static load of the test object and the linear electromagnetic motor to impart controlled motion to the test object.

Beyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders.

PubMed

Kupek, Emil

2006-03-15

Structural equation modelling (SEM) has been increasingly used in medical statistics for solving a system of related regression equations. However, a great obstacle for its wider use has been its difficulty in handling categorical variables within the framework of generalised linear models. A large data set with a known structure among two related outcomes and three independent variables was generated to investigate the use of Yule's transformation of odds ratio (OR) into Q-metric by (OR-1)/(OR+1) to approximate Pearson's correlation coefficients between binary variables whose covariance structure can be further analysed by SEM. Percent of correctly classified events and non-events was compared with the classification obtained by logistic regression. The performance of SEM based on Q-metric was also checked on a small (N = 100) random sample of the data generated and on a real data set. SEM successfully recovered the generated model structure. SEM of real data suggested a significant influence of a latent confounding variable which would have not been detectable by standard logistic regression. SEM classification performance was broadly similar to that of the logistic regression. The analysis of binary data can be greatly enhanced by Yule's transformation of odds ratios into estimated correlation matrix that can be further analysed by SEM. The interpretation of results is aided by expressing them as odds ratios which are the most frequently used measure of effect in medical statistics.

Linear test bed. Volume 1: Test bed no. 1. [aerospike test bed with segmented combustor

NASA Technical Reports Server (NTRS)

1972-01-01

The Linear Test Bed program was to design, fabricate, and evaluation test an advanced aerospike test bed which employed the segmented combustor concept. The system is designated as a linear aerospike system and consists of a thrust chamber assembly, a power package, and a thrust frame. It was designed as an experimental system to demonstrate the feasibility of the linear aerospike-segmented combustor concept. The overall dimensions are 120 inches long by 120 inches wide by 96 inches in height. The propellants are liquid oxygen/liquid hydrogen. The system was designed to operate at 1200-psia chamber pressure, at a mixture ratio of 5.5. At the design conditions, the sea level thrust is 200,000 pounds. The complete program including concept selection, design, fabrication, component test, system test, supporting analysis and posttest hardware inspection is described.

Biomass Stoves and Lens Opacity and Cataract in Nepalese Women

PubMed Central

Pokhrel, Amod K.; Bates, Michael N.; Shrestha, Sachet P.; Bailey, Ian L.; DiMartino, Robert B.; Smith, Kirk R.; Joshi, N. D.

2014-01-01

Purpose Cataract is the most prevalent cause of blindness in Nepal. Several epidemiologic studies have associated cataracts with use of biomass cookstoves. These studies, however, have had limitations, including potential control selection bias and limited adjustment for possible confounding. This study, in Pokhara city, in an area of Nepal where biomass cookstoves are widely used without direct venting of the smoke to the outdoors, focuses on pre-clinical measures of opacity, while avoiding selection bias and taking into account comprehensive data on potential confounding factors Methods Using a cross-sectional study design, severity of lenticular damage, judged on the LOCS III scales, was investigated in females (n=143), aged 20-65 years, without previously diagnosed cataract. Linear and logistic regression analyses were used to examine the relationships with stove type and length of use. Clinically significant cataract, used in the logistic regression models, was defined as a LOCS III score > 2. Results Using gas cookstoves as the reference group, logistic regression analysis for nuclear cataract showed the evidence of relationships with stove type: for biomass stoves, the odds ratio (OR) was 2.58 (95% confidence interval [CI]: 1.22-5.46) and, for kerosene stoves, the OR was 5.18 (95% CI: 0.88-30.38). Similar results were found for nuclear color (LOCS III score > 2), but no association was found with cortical cataracts. Supporting a relationship between biomass stoves and nuclear cataract was a trend with years of exposure to biomass cookstoves (p=0.01). Linear regression analyses did not show clear evidence of an association between lenticular damage and stove types. Biomass fuel used for heating was not associated with any form of opacity. Conclusions This study provides support for associations of biomass and kerosene cookstoves with nuclear opacity and change in nuclear color. The novel associations with kerosene cookstove use deserve further investigation. PMID:23400024

Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards.

PubMed

Churpek, Matthew M; Yuen, Trevor C; Winslow, Christopher; Meltzer, David O; Kattan, Michael W; Edelson, Dana P

2016-02-01

Machine learning methods are flexible prediction algorithms that may be more accurate than conventional regression. We compared the accuracy of different techniques for detecting clinical deterioration on the wards in a large, multicenter database. Observational cohort study. Five hospitals, from November 2008 until January 2013. Hospitalized ward patients None Demographic variables, laboratory values, and vital signs were utilized in a discrete-time survival analysis framework to predict the combined outcome of cardiac arrest, intensive care unit transfer, or death. Two logistic regression models (one using linear predictor terms and a second utilizing restricted cubic splines) were compared to several different machine learning methods. The models were derived in the first 60% of the data by date and then validated in the next 40%. For model derivation, each event time window was matched to a non-event window. All models were compared to each other and to the Modified Early Warning score, a commonly cited early warning score, using the area under the receiver operating characteristic curve (AUC). A total of 269,999 patients were admitted, and 424 cardiac arrests, 13,188 intensive care unit transfers, and 2,840 deaths occurred in the study. In the validation dataset, the random forest model was the most accurate model (AUC, 0.80 [95% CI, 0.80-0.80]). The logistic regression model with spline predictors was more accurate than the model utilizing linear predictors (AUC, 0.77 vs 0.74; p < 0.01), and all models were more accurate than the MEWS (AUC, 0.70 [95% CI, 0.70-0.70]). In this multicenter study, we found that several machine learning methods more accurately predicted clinical deterioration than logistic regression. Use of detection algorithms derived from these techniques may result in improved identification of critically ill patients on the wards.

Association between metabolic syndrome and intravesical prostatic protrusion in patients with benign prostatic enlargement and lower urinary tract symptoms (MIPS Study).

PubMed

Russo, Giorgio I; Regis, Federica; Spatafora, Pietro; Frizzi, Jacopo; Urzì, Daniele; Cimino, Sebastiano; Serni, Sergio; Carini, Marco; Gacci, Mauro; Morgia, Giuseppe

2018-05-01

To investigate the association between metabolic syndrome (MetS) and morphological features of benign prostatic enlargement (BPE), including total prostate volume (TPV), transitional zone volume (TZV) and intravesical prostatic protrusion (IPP). Between January 2015 and January 2017, 224 consecutive men aged >50 years presenting with lower urinary tract symptoms (LUTS) suggestive of BPE were recruited to this multicentre cross-sectional study. MetS was defined according to International Diabetes Federation criteria. Multivariate linear and logistic regression models were performed to verify factors associated with IPP, TZV and TPV. Patients with MetS were observed to have a significant increase in IPP (P < 0.01), TPV (P < 0.01) and TZV (P = 0.02). On linear regression analysis, adjusted for age and metabolic factors of MetS, we found that high-density lipoprotein (HDL) cholesterol was negatively associated with IPP (r = -0.17), TPV (r = -0.19) and TZV (r = -0.17), while hypertension was positively associated with IPP (r = 0.16), TPV (r = 0.19) and TZV (r = 0.16). On multivariate logistic regression analysis adjusted for age and factors of MetS, hypertension (categorical; odds ratio [OR] 2.95), HDL cholesterol (OR 0.94) and triglycerides (OR 1.01) were independent predictors of TPV ≥ 40 mL. We also found that HDL cholesterol (OR 0.86), hypertension (OR 2.0) and waist circumference (OR 1.09) were significantly associated with TZV ≥ 20 mL. On age-adjusted logistic regression analysis, MetS was significantly associated with IPP ≥ 10 mm (OR 34.0; P < 0.01), TZV ≥ 20 mL (OR 4.40; P < 0.01) and TPV ≥ 40 mL (OR 5.89; P = 0.03). We found an association between MetS and BPE, demonstrating a relationship with IPP. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Multiple Intelligence Scores of Science Stream Students and Their Relation with Reading Competency in Malaysian University English Test (MUET)

ERIC Educational Resources Information Center

Razak, Norizan Abdul; Zaini, Nuramirah

2014-01-01

Many researches have shown that different approach needed in analysing linear and non-linear reading comprehension texts and different cognitive skills are required. This research attempts to discover the relationship between Science Stream students' reading competency on linear and non-linear texts in Malaysian University English Test (MUET) with…

Quality Control Review of the Dixon Hughes Goodman LLP FY 2014 Single Audit of Logistics Management Institute

DTIC Science & Technology

2016-09-29

independent, relevant, and timely oversight of the Department of Defense that supports the warfighter; promotes accountability , integrity, and...compliance testing for the allowable costs/cost principles compliance requirement to ensure the review of indirect costs is adequately performed...consulting services in logistics, acquisition and financial management, infrastructure management, information management, organizational improvement, and

Asymptotic Properties of Induced Maximum Likelihood Estimates of Nonlinear Models for Item Response Variables: The Finite-Generic-Item-Pool Case.

ERIC Educational Resources Information Center

Jones, Douglas H.

The progress of modern mental test theory depends very much on the techniques of maximum likelihood estimation, and many popular applications make use of likelihoods induced by logistic item response models. While, in reality, item responses are nonreplicate within a single examinee and the logistic models are only ideal, practitioners make…

Ability Estimation and Item Calibration Using the One and Three Parameter Logistic Models: A Comparative Study. Research Report 77-1.

ERIC Educational Resources Information Center

Reckase, Mark D.

Latent trait model calibration procedures were used on data obtained from a group testing program. The one-parameter model of Wright and Panchapakesan and the three-parameter logistic model of Wingersky, Wood, and Lord were selected for comparison. These models and their corresponding estimation procedures were compared, using actual and simulated…

Modification of the Mantel-Haenszel and Logistic Regression DIF Procedures to Incorporate the SIBTEST Regression Correction

ERIC Educational Resources Information Center

DeMars, Christine E.

2009-01-01

The Mantel-Haenszel (MH) and logistic regression (LR) differential item functioning (DIF) procedures have inflated Type I error rates when there are large mean group differences, short tests, and large sample sizes.When there are large group differences in mean score, groups matched on the observed number-correct score differ on true score,…

An Evaluation of a Markov Chain Monte Carlo Method for the Two-Parameter Logistic Model.

ERIC Educational Resources Information Center

Kim, Seock-Ho; Cohen, Allan S.

The accuracy of the Markov Chain Monte Carlo (MCMC) procedure Gibbs sampling was considered for estimation of item parameters of the two-parameter logistic model. Data for the Law School Admission Test (LSAT) Section 6 were analyzed to illustrate the MCMC procedure. In addition, simulated data sets were analyzed using the MCMC, marginal Bayesian…

A Generalized Logistic Regression Procedure to Detect Differential Item Functioning among Multiple Groups

ERIC Educational Resources Information Center

Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul

2011-01-01

We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, workers confirm the Multi-Purpose Logistics Module Donatello is safely in place on a work stand. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello, is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

NASA Image and Video Library

2004-02-13

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, workers confirm the Multi-Purpose Logistics Module Donatello is safely in place on a work stand. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello, is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, the Multi-Purpose Logistics Module Donatello is slowly lowered toward a work stand. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

NASA Image and Video Library

2004-02-13

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, the Multi-Purpose Logistics Module Donatello is slowly lowered toward a work stand. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

KENNEDY SPACE CENTER, FLA. - All three Multi-Purpose Logistics Modules are on the floor of the Space Station Processing Facility. This is the first time the three - Leonardo, Raffaello and Donatello -- have been in one location. Donatello has been stored in the Operations and Checkout Building since its arrival at KSC and was brought into the SSPF for routine testing. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

NASA Image and Video Library

2004-02-18

KENNEDY SPACE CENTER, FLA. - All three Multi-Purpose Logistics Modules are on the floor of the Space Station Processing Facility. This is the first time the three - Leonardo, Raffaello and Donatello -- have been in one location. Donatello has been stored in the Operations and Checkout Building since its arrival at KSC and was brought into the SSPF for routine testing. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

KENNEDY SPACE CENTER, FLA. - The Multi-Purpose Logistics Module Donatello is moved away from the payload canister in the Space Station Processing Facility. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

NASA Image and Video Library

2004-02-13

KENNEDY SPACE CENTER, FLA. - The Multi-Purpose Logistics Module Donatello is moved away from the payload canister in the Space Station Processing Facility. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, workers help the Multi-Purpose Logistics Module Donatello settle onto a work stand. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello, is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

NASA Image and Video Library

2004-02-13

KENNEDY SPACE CENTER, FLA. - In the Space Station Processing Facility, workers help the Multi-Purpose Logistics Module Donatello settle onto a work stand. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello, is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

KENNEDY SPACE CENTER, FLA. - The Multi-Purpose Logistics Module Donatello is suspended by cables over the payload canister in the Space Station Processing Facility. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

NASA Image and Video Library

2004-02-13

KENNEDY SPACE CENTER, FLA. - The Multi-Purpose Logistics Module Donatello is suspended by cables over the payload canister in the Space Station Processing Facility. Previously housed in the Operations and Checkout Building, Donatello was brought into the SSPF for routine testing. This is the first time all three MPLMs (Donatello, Raffaello and Leonardo) are in the SSPF. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. The third MPLM, Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

KENNEDY SPACE CENTER, FLA. - This view reveals all three Multi-Purpose Logistics Modules on the floor of the Space Station Processing Facility. This is the first time all three - Leonardo, Raffaello and Donatello -- have been in one location. Donatello has been stored in the Operations and Checkout Building since its arrival at KSC and was brought into the SSPF for routine testing. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

NASA Image and Video Library

2004-02-18

KENNEDY SPACE CENTER, FLA. - This view reveals all three Multi-Purpose Logistics Modules on the floor of the Space Station Processing Facility. This is the first time all three - Leonardo, Raffaello and Donatello -- have been in one location. Donatello has been stored in the Operations and Checkout Building since its arrival at KSC and was brought into the SSPF for routine testing. The MPLMs were built by the Italian Space Agency, to serve as reusable logistics carriers and the primary delivery system to resupply and return station cargo requiring a pressurized environment. Raffaello is scheduled to fly on Space Shuttle Atlantis on mission STS-114.

Predictors and Neuropsychiatric Profile of Nucleus Basalis of Meynert Degeneration in Parkinson Disease

DTIC Science & Technology

2017-10-01

baseline were available for 228 PD subjects. In a logistic regression model adjusted for age and sex , Ch4 density was associated with lower risk of...events, there were no significant differences in age or sex (p>0.05). PD subjects with 2 or more psychotic events had significantly lower baseline Ch4...Aim 1 and 2 include use of linear regression models to adjust for age, sex , and other significant covariates. Aim 3 is a cross-sectional controlled

An introduction to g methods.

PubMed

Naimi, Ashley I; Cole, Stephen R; Kennedy, Edward H

2017-04-01

Robins' generalized methods (g methods) provide consistent estimates of contrasts (e.g. differences, ratios) of potential outcomes under a less restrictive set of identification conditions than do standard regression methods (e.g. linear, logistic, Cox regression). Uptake of g methods by epidemiologists has been hampered by limitations in understanding both conceptual and technical details. We present a simple worked example that illustrates basic concepts, while minimizing technical complications. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Empirical research on coordination evaluation and sustainable development mechanism of regional logistics and new-type urbanization: a panel data analysis from 2000 to 2015 for Liaoning Province in China.

PubMed

Sun, Qiang

2017-06-01

As the largest developing country in the world, China has witnessed fast-paced urbanization over the past three decades with rapid economic growth. In fact, urbanization has been not only shown to promote economic growth and improve the livelihood of people but also can increase demands of regional logistics. Therefore, a better understanding of the relationship between urbanization and regional logistics is important for China's future sustainable development. The development of urban residential area and heterogeneous, modern society as well regional logistics are running two abreast. The regional logistics can promote the development of new-type urbanization jointly by promoting industrial concentration and logistics demand, enhancing the residents' quality of life and improving the infrastructure and logistics technology. In this paper, the index system and evaluation model for evaluating the development of regional logistics and the new-type urbanization are constructed. Further, the econometric analysis is utilized such as correlation analysis, co-integration test, and error correction model to explore relationships of the new-type urbanization development and regional logistics development in Liaoning Province. The results showed that there was a long-term stable equilibrium relationship between the new-type urbanization and regional logistics. The findings have important implications for Chinese policymakers that on the path towards a sustainable urbanization and regional reverse, this must be taken into consideration. The paper concludes providing some strategies that might be helpful to the policymakers in formulating development policies for sustainable urbanization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gearhart, Jared Lee; Adair, Kristin Lynn; Durfee, Justin David.

When developing linear programming models, issues such as budget limitations, customer requirements, or licensing may preclude the use of commercial linear programming solvers. In such cases, one option is to use an open-source linear programming solver. A survey of linear programming tools was conducted to identify potential open-source solvers. From this survey, four open-source solvers were tested using a collection of linear programming test problems and the results were compared to IBM ILOG CPLEX Optimizer (CPLEX) [1], an industry standard. The solvers considered were: COIN-OR Linear Programming (CLP) [2], [3], GNU Linear Programming Kit (GLPK) [4], lp_solve [5] and Modularmore » In-core Nonlinear Optimization System (MINOS) [6]. As no open-source solver outperforms CPLEX, this study demonstrates the power of commercial linear programming software. CLP was found to be the top performing open-source solver considered in terms of capability and speed. GLPK also performed well but cannot match the speed of CLP or CPLEX. lp_solve and MINOS were considerably slower and encountered issues when solving several test problems.« less

Operations Nougat and Sun Beam. Organizational, operational, funding, and logistic summary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1985-09-01

This report covers the organizational, operational, funding, and logistic portions of the DoD-DASA effort at the Nevada Test Site during Operations Nougat and Sun Beam. Operations included Shots Hard Hat, Marshmallow, Danny Boy, Johnie Boy, Small Boy, Little Feller I and II, and the Vela-Uniform Program. The field activities started in November 1961 and ended in September 1962. Appendixes A through G contain shot and meteorological data, copies of statements of authority and agreements, information on reporting procedures, and a list of all reports resulting from both the Nevada and Pacific test operations conducted during 1962. The reports on themore » Pacific tests are listed as a convenience to readers interested in related projects in Operation Dominic.« less

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

NASA Astrophysics Data System (ADS)

Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

2014-12-01

Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

Statistical classification of drug incidents due to look-alike sound-alike mix-ups.

PubMed

Wong, Zoie Shui Yee

2016-06-01

It has been recognised that medication names that look or sound similar are a cause of medication errors. This study builds statistical classifiers for identifying medication incidents due to look-alike sound-alike mix-ups. A total of 227 patient safety incident advisories related to medication were obtained from the Canadian Patient Safety Institute's Global Patient Safety Alerts system. Eight feature selection strategies based on frequent terms, frequent drug terms and constituent terms were performed. Statistical text classifiers based on logistic regression, support vector machines with linear, polynomial, radial-basis and sigmoid kernels and decision tree were trained and tested. The models developed achieved an average accuracy of above 0.8 across all the model settings. The receiver operating characteristic curves indicated the classifiers performed reasonably well. The results obtained in this study suggest that statistical text classification can be a feasible method for identifying medication incidents due to look-alike sound-alike mix-ups based on a database of advisories from Global Patient Safety Alerts. © The Author(s) 2014.

The parenting attitudes and the stress of mothers predict the asthmatic severity of their children: a prospective study.

PubMed

Nagano, Jun; Kakuta, Chikage; Motomura, Chikako; Odajima, Hiroshi; Sudo, Nobuyuki; Nishima, Sankei; Kubo, Chiharu

2010-10-07

To examine relationships between a mother's stress-related conditions and parenting attitudes and their children's asthmatic status. 274 mothers of an asthmatic child 2 to 12 years old completed a questionnaire including questions about their chronic stress/coping behaviors (the "Stress Inventory"), parenting attitudes (the "Ta-ken Diagnostic Test for Parent-Child Relationship, Parent Form"), and their children's disease status. One year later, a follow-up questionnaire was mailed to the mothers that included questions on the child's disease status. 223 mothers (81%) responded to the follow-up survey. After controlling for non-psychosocial factors including disease severity at baseline, multiple linear regression analysis followed by multiple logistic regression analysis found chronic irritation/anger and emotional suppression to be aggravating factors for children aged < 7 years; for children aged 7 and over, the mothers' egocentric behavior was a mitigating factor while interference was an aggravating factor. Different types of parental stress/coping behaviors and parenting styles may differently predict their children's asthmatic status, and such associations may change as children grow.

Media Exposure and Genetic Literacy Skills to Evaluate Angelina Jolie's Decision for Prophylactic Mastectomy.

PubMed

Abrams, Leah R; Koehly, Laura M; Hooker, Gillian W; Paquin, Ryan S; Capella, Joseph N; McBride, Colleen M

2016-01-01

To examine public preparedness to evaluate and respond to Angelina Jolie's well-publicized decision to have a prophylactic mastectomy. A consumer panel (n = 1,008) completed an online survey in November 2013, reporting exposure to Jolie's story, confidence applying genomic knowledge to evaluate her decision, and ability to interpret provided genetic risk information (genetic literacy skills). Linear and logistic regressions tested mediating/moderating models of these factors in association with opinions regarding mastectomies. Confidence with genomics was associated with increased genetic literacy skills and increased media exposure, with a significant interaction between the two. Confidence was also associated with favoring mastectomies for women with BRCA mutations, mediating the relationship with media exposure. Respondents were more likely to form opinions about mastectomies if they had high genetic literacy skills. These findings suggest that having higher genetic literacy skills may increase the public's ability to form opinions about clinical applications of genomic discovery. However, repeated media exposure to high-profile stories may artificially inflate confidence among those with low genetic literacy. © 2016 S. Karger AG, Basel.

[Study on application of SVM in prediction of coronary heart disease].

PubMed

Zhu, Yue; Wu, Jianghua; Fang, Ying

2013-12-01

Base on the data of blood pressure, plasma lipid, Glu and UA by physical test, Support Vector Machine (SVM) was applied to identify coronary heart disease (CHD) in patients and non-CHD individuals in south China population for guide of further prevention and treatment of the disease. Firstly, the SVM classifier was built using radial basis kernel function, liner kernel function and polynomial kernel function, respectively. Secondly, the SVM penalty factor C and kernel parameter sigma were optimized by particle swarm optimization (PSO) and then employed to diagnose and predict the CHD. By comparison with those from artificial neural network with the back propagation (BP) model, linear discriminant analysis, logistic regression method and non-optimized SVM, the overall results of our calculation demonstrated that the classification performance of optimized RBF-SVM model could be superior to other classifier algorithm with higher accuracy rate, sensitivity and specificity, which were 94.51%, 92.31% and 96.67%, respectively. So, it is well concluded that SVM could be used as a valid method for assisting diagnosis of CHD.

Common side closure type, but not stapler brand or oversewing, influences side-to-side anastomotic leak rates.

PubMed

Fleetwood, V A; Gross, K N; Alex, G C; Cortina, C S; Smolevitz, J B; Sarvepalli, S; Bakhsh, S R; Poirier, J; Myers, J A; Singer, M A; Orkin, B A

2017-03-01

Anastomotic leak (AL) increases costs and cancer recurrence. Studies show decreased AL with side-to-side stapled anastomosis (SSA), but none identify risk factors within SSAs. We hypothesized that stapler characteristics and closure technique of the common enterotomy affect AL rates. Retrospective review of bowel SSAs was performed. Data included stapler brand, staple line oversewing, and closure method (handsewn, HC; linear stapler [Barcelona technique], BT; transverse stapler, TX). Primary endpoint was AL. Statistical analysis included Fisher's test and logistic regression. 463 patients were identified, 58.5% BT, 21.2% HC, and 20.3% TX. Covidien staplers comprised 74.9%, Ethicon 18.1%. There were no differences between stapler types (Covidien 5.8%, Ethicon 6.0%). However, AL rates varied by common side closure (BT 3.7% vs. TX 10.6%, p = 0.017), remaining significant on multivariate analysis. Closure method of the common side impacts AL rates. Barcelona technique has fewer leaks than transverse stapled closure. Further prospective evaluation is recommended. Copyright © 2017. Published by Elsevier Inc.

Impact of hospital transfer on surgical outcomes of intestinal atresia.

PubMed

Erickson, T; Vana, P G; Blanco, B A; Brownlee, S A; Paddock, H N; Kuo, P C; Kothari, A N

2017-03-01

Examine effects of hospital transfer into a quaternary care center on surgical outcomes of intestinal atresia. Children <1 yo principally diagnosed with intestinal atresia were identified using the Kids' Inpatient Database (2012). Exposure variable was patient transfer status. Outcomes measured were inpatient mortality, hospital length of stay (LOS) and discharge status. Linearized standard errors, design-based F tests, and multivariable logistic regression were performed. 1672 weighted discharges represented a national cohort. The highest income group and those with private insurance had significantly lower odds of transfer (OR:0.53 and 0.74, p < 0.05). Rural patients had significantly higher transfer rates (OR: 2.73, p < 0.05). Multivariate analysis revealed no difference in mortality (OR:0.71, p = 0.464) or non-home discharge (OR: 0.79, p = 0.166), but showed prolonged LOS (OR:1.79, p < 0.05) amongst transferred patients. Significant differences in hospital LOS and treatment access reveal a potential healthcare gap. Post-acute care resources should be improved for transferred patients. Copyright © 2016 Elsevier Inc. All rights reserved.

Prognostic scores in oesophageal or gastric variceal bleeding.

PubMed

Ohmann, C; Stöltzing, H; Wins, L; Busch, E; Thon, K

1990-05-01

Numerous scoring systems have been developed for the prediction of outcome of variceal bleeding; however, only a few have been evaluated adequately. The object of this study was to improve the classical Child-Pugh score (CPS) and to test other scores from the literature. Patients (n = 82) with endoscopically confirmed variceal bleeding and long-term sclerotherapy were included in the study. Linear logistic regression (LR) was applied to different sets of prognostic variables with regard to 30-day mortality. In addition, scores from the literature were evaluated on the data set. Performance was measured by the accuracy and receiver-operating characteristic curves. The application of LR to all five CPS variables (accuracy, 80%) was superior to the classical CPS (70%). LR with selection from the CPS variables or from other sets of variables resulted in no improvement. Compared with CPS only three scores from the literature, mainly based on subsets of the CPS variables, showed an improved accuracy. It is concluded that CPS is still a good scoring system; however, it can be improved by statistical analysis using the same variables.

Socio-Cognitive Determinants of the Mammography Screening Uptake among Iranian Women

PubMed

Mirzaei-Alavijeh, Mehdi; Ghorbani, Parvaneh; Jalilian, Farzad

2018-05-26

Background: Mammography screening uptake is the most effective method in breast cancer screening. The aim of this study was to determine the determinants related to mammography screening uptake among Iranian women based on the theory of planned behavior. Materials and Methods: This cross-sectional study was conducted among 408 women who referred to health centers in Kermanshah city, the western of Iran, during 2016. Participants filled out a self-administered questionnaire. Data were analyzed by SPSS version 21 using Pearson correlation, linear and logistic regression statistical tests at 95% significant level. Results: The mean age of participants was 39.61 years [SD: 8.28], ranged from 30 to 60 years. Almost 13% of the participants had already mammography screening uptake at least once. Perceived behavioral control (OR=1.229) and behavioral intention (OR=1.283) were the more influential predictors on mammography screening uptake. Conclusions: Based on result, it seems increase perceived behavior control toward mammography screening uptake may be usefulness in promotion of mammography screening uptake among Iranian women. Creative Commons Attribution License

[Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study].

PubMed

Wang, D Z; Wang, C; Shen, C F; Zhang, Y; Zhang, H; Song, G D; Xue, X D; Xu, Z L; Zhang, S; Jiang, G H

2017-05-10

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis, and the results were compared. Based on actual population, CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P value

Quantitative Approach to Failure Mode and Effect Analysis for Linear Accelerator Quality Assurance

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Daniel, Jennifer C., E-mail: jennifer.odaniel@duke.edu; Yin, Fang-Fang

Purpose: To determine clinic-specific linear accelerator quality assurance (QA) TG-142 test frequencies, to maximize physicist time efficiency and patient treatment quality. Methods and Materials: A novel quantitative approach to failure mode and effect analysis is proposed. Nine linear accelerator-years of QA records provided data on failure occurrence rates. The severity of test failure was modeled by introducing corresponding errors into head and neck intensity modulated radiation therapy treatment plans. The relative risk of daily linear accelerator QA was calculated as a function of frequency of test performance. Results: Although the failure severity was greatest for daily imaging QA (imaging vsmore » treatment isocenter and imaging positioning/repositioning), the failure occurrence rate was greatest for output and laser testing. The composite ranking results suggest that performing output and lasers tests daily, imaging versus treatment isocenter and imaging positioning/repositioning tests weekly, and optical distance indicator and jaws versus light field tests biweekly would be acceptable for non-stereotactic radiosurgery/stereotactic body radiation therapy linear accelerators. Conclusions: Failure mode and effect analysis is a useful tool to determine the relative importance of QA tests from TG-142. Because there are practical time limitations on how many QA tests can be performed, this analysis highlights which tests are the most important and suggests the frequency of testing based on each test's risk priority number.« less

Can a toxin gene NAAT be used to predict toxin EIA and the severity of Clostridium difficile infection?

PubMed

Garvey, Mark I; Bradley, Craig W; Wilkinson, Martyn A C; Holden, Elisabeth

2017-01-01

Diagnosis of C. difficile infection (CDI) is controversial because of the many laboratory methods available and their lack of ability to distinguish between carriage, mild or severe disease. Here we describe whether a low C. difficile toxin B nucleic acid amplification test (NAAT) cycle threshold (CT) can predict toxin EIA, CDI severity and mortality. A three-stage algorithm was employed for CDI testing, comprising a screening test for glutamate dehydrogenase (GDH), followed by a NAAT, then a toxin enzyme immunoassay (EIA). All diarrhoeal samples positive for GDH and NAAT between 2012 and 2016 were analysed. The performance of the NAAT CT value as a classifier of toxin EIA outcome was analysed using a ROC curve; patient mortality was compared to CTs and toxin EIA via linear regression models. A CT value ≤26 was associated with ≥72% toxin EIA positivity; applying a logistic regression model we demonstrated an association between low CT values and toxin EIA positivity. A CT value of ≤26 was significantly associated ( p  = 0.0262) with increased one month mortality, severe cases of CDI or failure of first line treatment. The ROC curve probabilities demonstrated a CT cut off value of 26.6. Here we demonstrate that a CT ≤26 indicates more severe CDI and is associated with higher mortality. Samples with a low CT value are often toxin EIA positive, questioning the need for this additional EIA test. A CT ≤26 could be used to assess the potential for severity of CDI and guide patient treatment.

Childhood conditions and current physical performance among non-institutionalized individuals aged 50+ in Israel.

PubMed

Weinstein, Galit

2016-12-01

Adverse socioeconomic conditions in childhood have been previously linked with high risk of various health conditions. However, the association with future physical function has been less studied. Hand grip strength and chair-rising time are objective measures of physical capability indicating current and future health outcomes. The aim of this study was to test the hypothesis that perceived socio-economic status in childhood is related to current measures of physical function, among Israeli participants of the Survey of Health, Ageing and Retirement in Europe project. The study included 2300 participants aged 50 years or older (mean age 68 ± 10; 56 % women). Generalized linear regression models were used to examine the associations of childhood wealth and number of books in residence with grip strength and time to complete five rises from a chair. Logistic regression models were used to assess the relationships between the early life conditions and the ability to perform the physical tests. Adjustment was made for current income or household wealth, and for demographic, anthropometric, health, and life-style measures. Being wealthy and having a large number of books at home in childhood was associated with a stronger hand grip and a better chair-rise test performance. These associations were more robust in women compared to men, and persisted after adjustment for potential covariates. In addition, childhood wealth and number of books were associated with lower risk of being unable to perform the tests. Thus, early-life programming may contribute to physical function indicators in mid- and late-life.

Association of TRPV4 gene polymorphisms with chronic obstructive pulmonary disease.

PubMed

Zhu, Guohua; Gulsvik, Amund; Bakke, Per; Ghatta, Srinivas; Anderson, Wayne; Lomas, David A; Silverman, Edwin K; Pillai, Sreekumar G

2009-06-01

Chronic obstructive pulmonary disease (COPD) is characterized by airway epithelial damage, bronchoconstriction, parenchymal destruction and mucus hypersecretion. Upon activation by a broad range of stimuli, transient receptor potential vanilloid 4 (TRPV4) functions to control airway epithelial cell volume and epithelial and endothelial permeability; it also triggers bronchial smooth muscle contraction and participates in autoregulation of mucociliary transport. These functions of TRPV4 may be important for the regulation of COPD pathogenesis, so TRPV4 is a candidate gene for COPD. We genotyped 20 single nucleotide polymorphisms (SNPs) in TRPV4, and tested qualitative COPD and quantitative FEV(1) and FEV(1)/(F)VC phenotypes in two independent large populations. The family population had 606 pedigrees including 1891 individuals, and the case-control sample included 953 COPD cases and 956 controls. Family-based association tests were performed in the family data. Logistic regression and linear models were used in the case-control data to replicate the association results. In the family data, seven out of 20 SNPs tested were associated with COPD (2.5 x 10(-4) < or = P < or = 0.04) and six SNPs were associated with FEV(1)/VC (0.02 < or = P < or = 0.03) from family-based association tests (PBAT) analysis. Four out of the seven SNPs associated with COPD demonstrated replicated associations with the same effect directions in the case-control population (0.02 < or = P < or = 0.03). Significant haplotype associations supported the results of single SNP analyses. Thus, polymorphisms in the TRPV4 gene are associated with COPD.

Xerostomia relates to the degree of asthma control.

PubMed

Alcázar Navarrete, Bernardino; Gómez-Moreno, Gerardo; Aguilar-Salvatierra, Antonio; Guardia, Javier; Romero Palacios, Pedro José

2015-04-01

Few studies have assessed the relationships between xerostomia and the use of inhaled corticosteroids (ICS). The main objective of this study was to investigate the prevalence of xerostomia in a respiratory outpatient clinic and its relationship with bronchial asthma and ICS use. A cross-sectional observational study of patients recruited in an outpatient setting divided them according to previous diagnoses of bronchial asthma. Data about pulmonary function, concomitant medication, medical comorbidities, Xerostomia Inventory test (XI test), and the degree of asthma control by ACT (asthma control test) were collected for each patient. A linear regression model was applied, using the XI score as dependent variable and the ACT score as independent variable. The 57 patients were divided into asthmatics (40 patients, 70.2%) and control group without asthma (17, 29.8%). The prevalence of xerostomia was 87.7% (50 patients), with no differences between the study groups or current dose of ICS. In the asthmatic group, patients with uncontrolled asthma had worse XI scores than those with partially or totally controlled asthma (30.43 ± 8.71 vs. 24.92 ± 8.08; P < 0.05). In a logistic regression model, the XI test was significantly associated to ACT scores with a moderately strong correlation (r = 0.55; P = 0.005) after adjusting for the current daily dose of ICS. Xerostomia is a common symptom in the ambulatory setting. There is a moderate relationship between the degree of asthma control and the severity of xerostomia. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

NASA Astrophysics Data System (ADS)

Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

2016-12-01

This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC) that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test's distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

Logistics Reduction and Repurposing Technology for Long Duration Space Missions

NASA Technical Reports Server (NTRS)

Broyan, James Lee, Jr.; Chu, Andrew; Ewert, Michael K.

2014-01-01

One of NASA's Advanced Exploration Systems (AES) projects is the Logistics Reduction and Repurposing (LRR) project, which has the goal of reducing logistics resupply items through direct and indirect means. Various technologies under development in the project will reduce the launch mass of consumables and their packaging, enable reuse and repurposing of items, and make logistics tracking more efficient. Repurposing also reduces the trash burden onboard spacecraft and indirectly reduces launch mass by one manifest item having two purposes rather than two manifest items each having only one purpose. This paper provides the status of each of the LRR technologies in their third year of development under AES. Advanced clothing systems (ACSs) are being developed to enable clothing to be worn longer, directly reducing launch mass. ACS has completed a ground exercise clothing study in preparation for an International Space Station technology demonstration in 2014. Development of launch packaging containers and other items that can be repurposed on-orbit as part of habitation outfitting has resulted in a logistics-to-living (L2L) concept. L2L has fabricated and evaluated several multi-purpose cargo transfer bags for potential reuse on-orbit. Autonomous logistics management is using radio frequency identification (RFID) to track items and thus reduce crew time for logistics functions. An RFID dense reader prototype is under construction and plans for integrated testing are being made. A heat melt compactor (HMC) second generation unit for processing trash into compact and stable tiles is nearing completion. The HMC prototype compaction chamber has been completed and system development testing is under way. Research has been conducted on the conversion of trash-to-gas (TtG) for high levels of volume reduction and for use in propulsion systems. A steam reformation system was selected for further system definition of the TtG technology.

Use of generalized ordered logistic regression for the analysis of multidrug resistance data.

PubMed

Agga, Getahun E; Scott, H Morgan

2015-10-01

Statistical analysis of antimicrobial resistance data largely focuses on individual antimicrobial's binary outcome (susceptible or resistant). However, bacteria are becoming increasingly multidrug resistant (MDR). Statistical analysis of MDR data is mostly descriptive often with tabular or graphical presentations. Here we report the applicability of generalized ordinal logistic regression model for the analysis of MDR data. A total of 1,152 Escherichia coli, isolated from the feces of weaned pigs experimentally supplemented with chlortetracycline (CTC) and copper, were tested for susceptibilities against 15 antimicrobials and were binary classified into resistant or susceptible. The 15 antimicrobial agents tested were grouped into eight different antimicrobial classes. We defined MDR as the number of antimicrobial classes to which E. coli isolates were resistant ranging from 0 to 8. Proportionality of the odds assumption of the ordinal logistic regression model was violated only for the effect of treatment period (pre-treatment, during-treatment and post-treatment); but not for the effect of CTC or copper supplementation. Subsequently, a partially constrained generalized ordinal logistic model was built that allows for the effect of treatment period to vary while constraining the effects of treatment (CTC and copper supplementation) to be constant across the levels of MDR classes. Copper (Proportional Odds Ratio [Prop OR]=1.03; 95% CI=0.73-1.47) and CTC (Prop OR=1.1; 95% CI=0.78-1.56) supplementation were not significantly associated with the level of MDR adjusted for the effect of treatment period. MDR generally declined over the trial period. In conclusion, generalized ordered logistic regression can be used for the analysis of ordinal data such as MDR data when the proportionality assumptions for ordered logistic regression are violated. Published by Elsevier B.V.

Evidence for deterministic chaos in aperiodic oscillations of acute lymphoblastic leukemia cells in long-term culture

NASA Astrophysics Data System (ADS)

Lambrou, George I.; Chatziioannou, Aristotelis; Vlahopoulos, Spiros; Moschovi, Maria; Chrousos, George P.

Biological systems are dynamic and possess properties that depend on two key elements: initial conditions and the response of the system over time. Conceptualizing this on tumor models will influence conclusions drawn with regard to disease initiation and progression. Alterations in initial conditions dynamically reshape the properties of proliferating tumor cells. The present work aims to test the hypothesis of Wolfrom et al., that proliferation shows evidence for deterministic chaos in a manner such that subtle differences in the initial conditions give rise to non-linear response behavior of the system. Their hypothesis, tested on adherent Fao rat hepatoma cells, provides evidence that these cells manifest aperiodic oscillations in their proliferation rate. We have tested this hypothesis with some modifications to the proposed experimental setup. We have used the acute lymphoblastic leukemia cell line CCRF-CEM, as it provides an excellent substrate for modeling proliferation dynamics. Measurements were taken at time points varying from 24h to 48h, extending the assayed populations beyond that of previous published reports that dealt with the complex dynamic behavior of animal cell populations. We conducted flow cytometry studies to examine the apoptotic and necrotic rate of the system, as well as DNA content changes of the cells over time. The cells exhibited a proliferation rate of nonlinear nature, as this rate presented oscillatory behavior. The obtained data have been fit in known models of growth, such as logistic and Gompertzian growth.

Medical homes versus individual practice in primary care: impact on health care expenditures.

PubMed

Perelman, Julian; Roch, Isabelle; Heymans, Isabelle; Moureaux, Catherine; Lagasse, Raphael; Annemans, Lieven; Closon, Marie-Christine

2013-08-01

The medical home (MH) model has prompted increasing attention given its potential to improve quality of care while reducing health expenditures. We compare overall and specific health care expenditures in Belgium, from the third-party payer perspective (compulsory social insurance), between patients treated at individual practices (IP) and at MHs. We compare the sociodemographic profile of MH and IP users. This is a retrospective study using public insurance claims data. Generalized linear models estimate the impact on health expenditures of being treated at a MH versus IP, controlling for individual, and area-based sociodemographic characteristics. The choice of primary care setting is modeled using logistic regressions. A random sample of 43,678 persons followed during the year 2004. Third-party payer expenditures for primary care, secondary care consultations, pharmaceuticals, laboratory tests, acute and long-term inpatient care. Overall third-party payer expenditures do not differ significantly between MH and IP users (€+27). Third-party payer primary care expenditures are higher for MH than for IP users (€+129), but this difference is offset by lower expenditures for secondary care consultations (€-11), drugs (€-40), laboratory tests (€-5) and acute and long-term inpatient care (€-53). MHs attract younger and more underprivileged populations. MHs induce a shift in expenditures from secondary care, drugs, and laboratory tests to primary care, while treating a less economically favored population. Combined with positive results regarding quality, MH structures are a promising way to tackle the challenges of primary care.

Machine learning search for variable stars

NASA Astrophysics Data System (ADS)

Pashchenko, Ilya N.; Sokolovsky, Kirill V.; Gavras, Panagiotis

2018-04-01

Photometric variability detection is often considered as a hypothesis testing problem: an object is variable if the null hypothesis that its brightness is constant can be ruled out given the measurements and their uncertainties. The practical applicability of this approach is limited by uncorrected systematic errors. We propose a new variability detection technique sensitive to a wide range of variability types while being robust to outliers and underestimated measurement uncertainties. We consider variability detection as a classification problem that can be approached with machine learning. Logistic Regression (LR), Support Vector Machines (SVM), k Nearest Neighbours (kNN), Neural Nets (NN), Random Forests (RF), and Stochastic Gradient Boosting classifier (SGB) are applied to 18 features (variability indices) quantifying scatter and/or correlation between points in a light curve. We use a subset of Optical Gravitational Lensing Experiment phase two (OGLE-II) Large Magellanic Cloud (LMC) photometry (30 265 light curves) that was searched for variability using traditional methods (168 known variable objects) as the training set and then apply the NN to a new test set of 31 798 OGLE-II LMC light curves. Among 205 candidates selected in the test set, 178 are real variables, while 13 low-amplitude variables are new discoveries. The machine learning classifiers considered are found to be more efficient (select more variables and fewer false candidates) compared to traditional techniques using individual variability indices or their linear combination. The NN, SGB, SVM, and RF show a higher efficiency compared to LR and kNN.

Prevalence and risk factors for latent tuberculosis infection among healthcare workers in Nampula Central Hospital, Mozambique.

PubMed

Belo, Celso; Naidoo, Saloshni

2017-06-08

Healthcare workers in high tuberculosis burdened countries are occupationally exposed to the tuberculosis disease with uncomplicated and complicated tuberculosis on the increase among them. Most of them acquire Mycobacterium tuberculosis but do not progress to the active disease - latent tuberculosis infection. The objective of this study was to assess the prevalence and risk factors associated with latent tuberculosis infection among healthcare workers in Nampula Central Hospital, Mozambique. This cross-sectional study of healthcare workers was conducted between 2014 and 2015. Participants (n = 209) were administered a questionnaire on demographics and occupational tuberculosis exposure and had a tuberculin skin test administered. Multivariate linear and logistic regression tested for associations between independent variables and dependent outcomes (tuberculin skin test induration and latent tuberculosis infection status). The prevalence of latent tuberculosis infection was 34.4%. Latent tuberculosis infection was highest in those working for more than eight years (39.3%), those who had no BCG vaccination (39.6%) and were immunocompromised (78.1%). Being immunocompromised was significantly associated with latent tuberculosis infection (OR 5.97 [95% CI 1.89; 18.87]). Positive but non-significant associations occurred with working in the medical domain (OR 1.02 [95% CI 0.17; 6.37]), length of employment > eight years (OR 1.97 [95% CI 0.70; 5.53]) and occupational contact with tuberculosis patients (OR 1.24 [95% CI 0.47; 3.27]). Personal and occupational factors were positively associated with latent tuberculosis infection among healthcare workers in Mozambique.

Nutritional status and HIV in rural South African children.

PubMed

Kimani-Murage, Elizabeth W; Norris, Shane A; Pettifor, John M; Tollman, Stephen M; Klipstein-Grobusch, Kerstin; Gómez-Olivé, Xavier F; Dunger, David B; Kahn, Kathleen

2011-03-25

Achieving the Millennium Development Goals that aim to reduce malnutrition and child mortality depends in part on the ability of governments/policymakers to address nutritional status of children in general and those infected or affected by HIV/AIDS in particular. This study describes HIV prevalence in children, patterns of malnutrition by HIV status and determinants of nutritional status. The study involved 671 children aged 12-59 months living in the Agincourt sub-district, rural South Africa in 2007. Anthropometric measurements were taken and HIV testing with disclosure was done using two rapid tests. Z-scores were generated using WHO 2006 standards as indicators of nutritional status. Linear and logistic regression analyses were conducted to establish the determinants of child nutritional status. Prevalence of malnutrition, particularly stunting (18%), was high in the overall sample of children. HIV prevalence in this age group was 4.4% (95% CI: 2.79 to 5.97). HIV positive children had significantly poorer nutritional outcomes than their HIV negative counterparts. Besides HIV status, other significant determinants of nutritional outcomes included age of the child, birth weight, maternal age, age of household head, and area of residence. This study documents poor nutritional status among children aged 12-59 months in rural South Africa. HIV is an independent modifiable risk factor for poor nutritional outcomes and makes a significant contribution to nutritional outcomes at the individual level. Early paediatric HIV testing of exposed or at risk children, followed by appropriate health care for infected children, may improve their nutritional status and survival.

Impact of breastfeeding on the intelligence quotient of eight-year-old children.

PubMed

Fonseca, Ana L M; Albernaz, Elaine P; Kaufmann, Cristina C; Neves, Ivana H; Figueiredo, Vera L M de

2013-01-01

This study aimed to determine the influence of breastfeeding on the intellectual capacity of children from a cohort in a developing country, with a control for the main confounding factors. A prospective cohort study was performed including all infants born in the hospitals of a medium-size city, and a random sample of these newborns was monitored at 30, 90, and 180 days of life, and at age 8 years. Several aspects of breastfeeding were assessed in the follow-up and, at 8 years, general intellectual capacity was assessed through the Raven's Colored Progressive Matrices test. The statistical analyses used Student's t-test, ANOVA, and linear regression and logistics, considering p-values less than 0.05 as statistically significant associations. At age 8 years, 560 children were assessed with Raven's Colored Progressive Matrices test. The average score was 22.56 points, with a standard deviation of 5.93. The difference in the averages found between the breastfed and non-breastfed groups at six months of age was 1.33 (p=0.008). Mother's and child's skin color, social and economic class, maternal education and smoking, and breastfeeding at six months of age (p=0.007) were still associated with the outcome. Children that were breastfed for six months or more had better performance in the general intellectual assessment, even after adjusting for the main confounding factors. Copyright © 2013 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Declining trends in alcohol consumption among Swedish youth-does the theory of collectivity of drinking cultures apply?

PubMed

Raninen, Jonas; Livingston, Michael; Leifman, Håkan

2014-11-01

To analyse trends in alcohol consumption among young people in Sweden between 2004 and 2012, to test whether the theory of collectivity of drinking cultures is valid for a population of young people and to investigate the impact of an increasing proportion of abstainers on the overall per capita trends. Data were drawn from an annual survey of a nationally representative sample of students in year 11 (17-18 years old). The data covered 9 years and the total sample comprised 36,141 students. Changes in the overall per capita consumption were tested using linear regression on log-transformed data, and changes in abstention rates were tested using logistic regression. The analyses were then continued by calculating average consumption in deciles. Alcohol consumption among year 11 students declined significantly among both boys and girls between 2004 and 2012. These changes were reflected at all levels of consumption, and the same results were found when abstainers were excluded from the analyses. The increasing proportion of abstainers had a minimal effect on the overall decline in consumption; rather, this was driven by a decline in consumption among the heaviest drinkers. The theory of collectivity of drinking cultures seems valid for understanding changes in alcohol consumption among Swedish year 11 students. No support was found for a polarization of alcohol consumption in this nationally representative sample. © The Author 2014. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Linear Ion Traps in Space: The Mars Organic Molecule Analyzer (MOMA) Instrument and Beyond

NASA Astrophysics Data System (ADS)

Arevalo, Ricardo; Brinckerhoff, William; Mahaffy, Paul; van Amerom, Friso; Danell, Ryan; Pinnick, Veronica; Li, Xiang; Hovmand, Lars; Getty, Stephanie; Grubisic, Andrej; Goesmann, Fred; Cottin, Hervé

2015-11-01

Historically, quadrupole mass spectrometer (QMS) instruments have been used to explore a wide survey of planetary targets in our solar system, from Venus (Pioneer Venus) to Saturn (Cassini-Huygens). However, linear ion trap (LIT) mass spectrometers have found a niche as smaller, versatile alternatives to traditional quadrupole analyzers.The core astrobiological experiment of ESA’s ExoMars Program is the Mars Organic Molecule Analyzer (MOMA) onboard the ExoMars 2018 rover. The MOMA instrument is centered on a linear (or 2-D) ion trap mass spectrometer. As opposed to 3-D traps, LIT-based instruments accommodate two symmetrical ion injection pathways, enabling two complementary ion sources to be used. In the case of MOMA, these two analytical approaches are laser desorption mass spectrometry (LDMS) at Mars ambient pressures, and traditional gas chromatography mass spectrometry (GCMS). The LIT analyzer employed by MOMA also offers: higher ion capacity compared to a 3-D trap of the same volume; redundant detection subassemblies for extended lifetime; and, a link to heritage QMS designs and assembly logistics. The MOMA engineering test unit (ETU) has demonstrated the detection of organics in the presence of wt.%-levels of perchlorate, effective ion enhancement via stored waveform inverse Fourier transform (SWIFT), and derivation of structural information through tandem mass spectrometry (MS/MS).A more progressive linear ion trap mass spectrometer (LITMS), funded by the NASA ROSES MatISSE Program, is being developed at NASA GSFC and promises to augment the capabilities of the MOMA instrument by way of: an expanded mass range (i.e., 20 - 2000 Da); detection of both positive and negative ions; spatially resolved (<1 mm) characterization of individual rock core layers; and, evolved gas analysis and GCMS with pyrolysis up to 1300° C (enabling breakdown of refractory phases). The Advanced Resolution Organic Molecule Analyzer (AROMA) instrument, being developed through NASA PICASSO and ESA Research and Development Programs, combines a highly capable LIT front end (a la LITMS) with a high-resolution OrbitrapTM (a la CosmOrbitrap) mass analyzer to enable disambiguation of complex molecular signals in organic-rich targets.

Further investigations of the W-test for pairwise epistasis testing.

PubMed

Howey, Richard; Cordell, Heather J

2017-01-01

Background: In a recent paper, a novel W-test for pairwise epistasis testing was proposed that appeared, in computer simulations, to have higher power than competing alternatives. Application to genome-wide bipolar data detected significant epistasis between SNPs in genes of relevant biological function. Network analysis indicated that the implicated genes formed two separate interaction networks, each containing genes highly related to autism and neurodegenerative disorders. Methods: Here we investigate further the properties and performance of the W-test via theoretical evaluation, computer simulations and application to real data. Results: We demonstrate that, for common variants, the W-test is closely related to several existing tests of association allowing for interaction, including logistic regression on 8 degrees of freedom, although logistic regression can show inflated type I error for low minor allele frequencies,  whereas the W-test shows good/conservative type I error control. Although in some situations the W-test can show higher power, logistic regression is not limited to tests on 8 degrees of freedom but can instead be tailored to impose greater structure on the assumed alternative hypothesis, offering a power advantage when the imposed structure matches the true structure. Conclusions: The W-test is a potentially useful method for testing for association - without necessarily implying interaction - between genetic variants disease, particularly when one or more of the genetic variants are rare. For common variants, the advantages of the W-test are less clear, and, indeed, there are situations where existing methods perform better. In our investigations, we further uncover a number of problems with the practical implementation and application of the W-test (to bipolar disorder) previously described, apparently due to inadequate use of standard data quality-control procedures. This observation leads us to urge caution in interpretation of the previously-presented results, most of which we consider are highly likely to be artefacts.

Reducing Mission Logistics with Multipurpose Cargo Transfer Bags

NASA Technical Reports Server (NTRS)

Baccus, Shelley; Broyan, James Lee, Jr.; Borrego, Melissa

2016-01-01

The Logistics Reduction (LR) project within Advanced Exploration Systems (AES) is tasked with reducing logistical mass and repurposing logistical items. Multipurpose Cargo Transfer Bags (MCTB) have been designed such that they can serve the same purpose as a Cargo Transfer Bag (CTB), the common logistics carrying bag for the International Space Station (ISS). After use as a cargo carrier, a regular CTB becomes trash, whereas the MCTB can be unfolded into a flat panel for reuse. Concepts and potential benefits for various MCTB applications will be discussed including partitions, crew quarters, solar radiation storm shelters, acoustic blankets, and forward osmosis water processing. Acoustic MCTBs are currently in use on ISS to reduce the noise generated by the T2 treadmill, which reaches the hazard limit at high speeds. The development of the AMCTB included identification of keep-out zones, acoustic properties, deployment considerations, and structural testing. Features developed for these considerations are applicable to MCTBs for all crew outfitting applications.

Multipurpose Cargo Transfer Bags fro Reducing Exploration Mission Logistics

NASA Technical Reports Server (NTRS)

Baccus, Shelley; Broyan, James Lee, Jr.; Borrego, Melissa

2016-01-01

The Logistics Reduction (LR) project within the Advanced Exploration Systems (AES) division is tasked with reducing logistical mass and repurposing logistical items. Multipurpose Cargo Transfer Bags (MCTB) have been designed such that they can serve the same purpose as a Cargo Transfer Bag (CTB), the common logistics carrying bag for the International Space Station (ISS). After use as a cargo carrier, a regular CTB becomes trash, whereas the MCTB can be unfolded into a flat panel for reuse. Concepts and potential benefits for various MCTB applications will be discussed including partitions, crew quarters, solar radiation storm shelters, acoustic blankets, and forward osmosis water processing. Acoustic MCTBs are currently in use on ISS to reduce the noise generated by the T2 treadmill, which reaches the hazard limit at high speeds. The development of the AMCTB included identification of keep out zones, acoustic properties, deployment considerations, and structural testing. Features developed for these considerations are applicable to MCTBs for all crew outfitting applications.

Comparative decision models for anticipating shortage of food grain production in India

NASA Astrophysics Data System (ADS)

Chattopadhyay, Manojit; Mitra, Subrata Kumar

2018-01-01

This paper attempts to predict food shortages in advance from the analysis of rainfall during the monsoon months along with other inputs used for crop production, such as land used for cereal production, percentage of area covered under irrigation and fertiliser use. We used six binary classification data mining models viz., logistic regression, Multilayer Perceptron, kernel lab-Support Vector Machines, linear discriminant analysis, quadratic discriminant analysis and k-Nearest Neighbors Network, and found that linear discriminant analysis and kernel lab-Support Vector Machines are equally suitable for predicting per capita food shortage with 89.69 % accuracy in overall prediction and 92.06 % accuracy in predicting food shortage ( true negative rate). Advance information of food shortage can help policy makers to take remedial measures in order to prevent devastating consequences arising out of food non-availability.

HIV testing among MSM in Bogotá, Colombia: The role of structural and individual characteristics

PubMed Central

Reisen, Carol A.; Zea, Maria Cecilia; Bianchi, Fernanda T.; Poppen, Paul J.; del Río González, Ana Maria; Romero, Rodrigo A. Aguayo; Pérez, Carolin

2014-01-01

This study used mixed methods to examine characteristics related to HIV testing among men who have sex with men (MSM) in Bogotá, Colombia. A sample of 890 MSM responded to a computerized quantitative survey. Follow-up qualitative data included 20 in-depth interviews with MSM and 12 key informant interviews. Hierarchical logistic set regression indicated that sequential sets of variables reflecting demographic characteristics, insurance coverage, risk appraisal, and social context each added to the explanation of HIV testing. Follow-up logistic regression showed that individuals who were older, had higher income, paid for their own insurance, had had a sexually transmitted infection, knew more people living with HIV, and had greater social support were more likely to have been tested for HIV at least once. Qualitative findings provided details of personal and structural barriers to testing, as well as interrelationships among these factors. Recommendations to increase HIV testing among Colombian MSM are offered. PMID:25068180

Efficient logistic regression designs under an imperfect population identifier.

PubMed

Albert, Paul S; Liu, Aiyi; Nansel, Tonja

2014-03-01

Motivated by actual study designs, this article considers efficient logistic regression designs where the population is identified with a binary test that is subject to diagnostic error. We consider the case where the imperfect test is obtained on all participants, while the gold standard test is measured on a small chosen subsample. Under maximum-likelihood estimation, we evaluate the optimal design in terms of sample selection as well as verification. We show that there may be substantial efficiency gains by choosing a small percentage of individuals who test negative on the imperfect test for inclusion in the sample (e.g., verifying 90% test-positive cases). We also show that a two-stage design may be a good practical alternative to a fixed design in some situations. Under optimal and nearly optimal designs, we compare maximum-likelihood and semi-parametric efficient estimators under correct and misspecified models with simulations. The methodology is illustrated with an analysis from a diabetes behavioral intervention trial. © 2013, The International Biometric Society.

Role of NDI in ABDR Assessment, Equipment & Logistics

DTIC Science & Technology

2010-05-01

RTO-EN-AVT-156 6 - 1 Role of NDI in ABDR Assessment, Equipment & Logistics Capt. (Dr.) Ferdinando Dolce Italian Air Force – Flight Test...showing results of NDT techniques applied on composite material structures. 1 . INTRODUCTION Damage assessment is one of the most important step...cured laminates applications (figure 1 ). Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of

It's Easy To Be Wise after the Event: Concepts for Redesigning an Educational System on Logistics Derived from Reflecting Its Development and Use.

ERIC Educational Resources Information Center

Neumann, Gaby; Ziems, Dietrich; Hopner, Christian

This paper introduces a multimedia-based educational system on logistics developed at the University of Magdeburg (Germany), reports on development and implementation of the prototype, and discusses ideas for redesign. The system was tested, used, and evaluated at the university and within a European network of 24 universities, colleges, and…

Use of Robust z in Detecting Unstable Items in Item Response Theory Models

ERIC Educational Resources Information Center

Huynh, Huynh; Meyer, Patrick

2010-01-01

The first part of this paper describes the use of the robust z[subscript R] statistic to link test forms using the Rasch (or one-parameter logistic) model. The procedure is then extended to the two-parameter and three-parameter logistic and two-parameter partial credit (2PPC) models. A real set of data was used to illustrate the extension. The…

HIV-associated cognitive performance and psychomotor impairment in a Thai cohort on long-term cART.

PubMed

Do, Tanya C; Kerr, Stephen J; Avihingsanon, Anchalee; Suksawek, Saowaluk; Klungkang, Supalak; Channgam, Taweesak; Odermatt, Christoph C; Maek-A-Nantawat, Wirach; Ruxtungtham, Kiat; Ananworanich, Jintanat; Valcour, Victor; Reiss, Peter; Wit, Ferdinand W

2018-01-01

To assess cognitive performance and psychomotor impairment in an HIV-positive cohort, well-suppressed on combination antiretroviral therapy (cART), in an Asian resource-limited setting. Cross-sectional sociodemographic and cognitive data were collected in 329 HIV-positive and 510 HIV-negative participants. Cognitive performance was assessed using the International HIV Dementia Scale (IHDS), Montreal Cognitive Assessment (MoCA), WAIS-III Digit Symbol, Trail Making A, and Grooved Pegboard (both hands). Psychomotor test scores in the HIV-positive participants were converted to Z-scores using scores of the HIV-negative participants as normative data. Psychomotor impairment was defined as performance on two tests more than 1 standard deviation (SD) from controls or more than 2 SD on one test. Multivariate linear and logistic regression analyses were used to investigate associations between HIV and non-HIV-related covariates and poorer cognitive performance and psychomotor impairment. HIV-positive participants, mean age 45 (SD 7.69) years received cART for a median of 12.1 years (interquartile range [IQR] 9.1-14.4). Median CD4 cell count was 563 cells/mm 3 (IQR 435-725), and 92.77% had plasma HIV RNA <40 copies/mL. The adjusted mean differences between HIV-positive versus HIV-negative cohorts indicated significantly inferior cognitive performance (tests all P <0.001) with increasing age and lower income, independently associated. Psychomotor impairment was found ( P <0.02) in all tests except the Grooved Pegboard non-dominant hand ( P =0.48). Psychomotor impairment prevalence was 43% in the HIV-positive cohort, associated with male gender and lower income. In this study, in individuals with viral suppression rates >90% on long-term cART, we found that inferior cognitive performance and psychomotor impairment were primarily associated with non-HIV-related factors.

The SLS Stages Intertank Structural Test Assembly (STA) arrives at MSFC

NASA Image and Video Library

2018-03-06

The SLS Stages Intertank Structural Test Assembly (STA) is rolling off the NASA Pegasus Barge at the MSFC Dock enroute to the MSFC 4619 Load Test Annex test facility for qualification testing. Members of MSFC Logistics Office and Move Team members gather for last minute instructions and safety briefing before off-loading STA hardware.

Comparison of futility monitoring guidelines using completed phase III oncology trials.

PubMed

Zhang, Qiang; Freidlin, Boris; Korn, Edward L; Halabi, Susan; Mandrekar, Sumithra; Dignam, James J

2017-02-01

Futility (inefficacy) interim monitoring is an important component in the conduct of phase III clinical trials, especially in life-threatening diseases. Desirable futility monitoring guidelines allow timely stopping if the new therapy is harmful or if it is unlikely to demonstrate to be sufficiently effective if the trial were to continue to its final analysis. There are a number of analytical approaches that are used to construct futility monitoring boundaries. The most common approaches are based on conditional power, sequential testing of the alternative hypothesis, or sequential confidence intervals. The resulting futility boundaries vary considerably with respect to the level of evidence required for recommending stopping the study. We evaluate the performance of commonly used methods using event histories from completed phase III clinical trials of the Radiation Therapy Oncology Group, Cancer and Leukemia Group B, and North Central Cancer Treatment Group. We considered published superiority phase III trials with survival endpoints initiated after 1990. There are 52 studies available for this analysis from different disease sites. Total sample size and maximum number of events (statistical information) for each study were calculated using protocol-specified effect size, type I and type II error rates. In addition to the common futility approaches, we considered a recently proposed linear inefficacy boundary approach with an early harm look followed by several lack-of-efficacy analyses. For each futility approach, interim test statistics were generated for three schedules with different analysis frequency, and early stopping was recommended if the interim result crossed a futility stopping boundary. For trials not demonstrating superiority, the impact of each rule is summarized as savings on sample size, study duration, and information time scales. For negative studies, our results show that the futility approaches based on testing the alternative hypothesis and repeated confidence interval rules yielded less savings (compared to the other two rules). These boundaries are too conservative, especially during the first half of the study (<50% of information). The conditional power rules are too aggressive during the second half of the study (>50% of information) and may stop a trial even when there is a clinically meaningful treatment effect. The linear inefficacy boundary with three or more interim analyses provided the best results. For positive studies, we demonstrated that none of the futility rules would have stopped the trials. The linear inefficacy boundary futility approach is attractive from statistical, clinical, and logistical standpoints in clinical trials evaluating new anti-cancer agents.

Jackknife Variance Estimator for Two Sample Linear Rank Statistics

DTIC Science & Technology

1988-11-01

Accesion For - - ,NTIS GPA&I "TIC TAB Unann c, nc .. [d Keywords: strong consistency; linear rank test’ influence function . i , at L By S- )Distribut...reverse if necessary and identify by block number) FIELD IGROUP SUB-GROUP Strong consistency; linear rank test; influence function . 19. ABSTRACT

Performance Testing of a High Temperature Linear Alternator for Stirling Convertors

NASA Technical Reports Server (NTRS)

Metscher, Jonathan; Geng, Steven

2016-01-01

The NASA Glenn Research Center has conducted performance testing of a high temperature linear alternator (HTLA) in support of Stirling power convertor development for potential future Radioisotope Power Systems (RPS). The high temperature linear alternator is a modified version of that used in Sunpowers Advanced Stirling Convertor (ASC), and is capable of operation at temperatures up to 200 C. Increasing the temperature capability of the linear alternator could expand the mission space of future Stirling RPS designs. High temperature Neodymium-Iron-Boron (Nd-Fe-B) magnets were selected for the HTLA application, and were fully characterized and tested prior to uses. Higher temperature epoxy for alternator assembly was also selected and tested for thermal stability and strength. A characterization test was performed on the HTLA to measure its performance at various amplitudes, loads, and temperatures. HTLA endurance testing at 200 C is currently underway.

Performance Testing of a High Temperature Linear Alternator for Stirling Convertors

NASA Technical Reports Server (NTRS)

Metscher, Jonathan F.; Geng, Steven M.

2016-01-01

The NASA Glenn Research Center has conducted performance testing of a high temperature linear alternator (HTLA) in support of Stirling power convertor development for potential future Radioisotope Power Systems (RPS). The high temperature linear alternator is a modified version of that used in Sunpower's Advanced Stirling Convertor (ASC), and is capable of operation at temperatures up to 200 deg. Increasing the temperature capability of the linear alternator could expand the mission set of future Stirling RPS designs. High temperature Neodymium-Iron-Boron (Nd-Fe-B) magnets were selected for the HTLA application, and were fully characterized and tested prior to use. Higher temperature epoxy for alternator assembly was also selected and tested for thermal stability and strength. A characterization test was performed on the HTLA to measure its performance at various amplitudes, loads, and temperatures. HTLA endurance testing at 200 deg is currently underway.

A Review of Models for Computer-Based Testing. Research Report 2011-12

ERIC Educational Resources Information Center

Luecht, Richard M.; Sireci, Stephen G.

2011-01-01

Over the past four decades, there has been incremental growth in computer-based testing (CBT) as a viable alternative to paper-and-pencil testing. However, the transition to CBT is neither easy nor inexpensive. As Drasgow, Luecht, and Bennett (2006) noted, many design engineering, test development, operations/logistics, and psychometric changes…

Android platform based smartphones for a logistical remote association repair framework.

PubMed

Lien, Shao-Fan; Wang, Chun-Chieh; Su, Juhng-Perng; Chen, Hong-Ming; Wu, Chein-Hsing

2014-06-25

The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use.

Overview of NASA Magnet and Linear Alternator Research Efforts

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Schwarze, Gene E.; Nieda, Janis M.

2005-01-01

The Department of Energy, Lockheed Martin, Stirling Technology Company, and NASA Glenn Research Center are developing a high-efficiency, 110 watt Stirling Radioisotope Generator (SRG110) for NASA Space Science missions. NASA Glenn is conducting in-house research on rare earth permanent magnets and on linear alternators to assist in developing a free-piston Stirling convertor for the SRG110 and for developing advanced technology. The permanent magnet research efforts include magnet characterization, short-term magnet aging tests, and long-term magnet aging tests. Linear alternator research efforts have begun just recently at GRC with the characterization of a moving iron type linear alternator using GRC's alternator test rig. This paper reports on the progress and future plans of GRC's magnet and linear alternator research efforts.