Alternative High School Students: Prevalence and Correlates of Overweight

ERIC Educational Resources Information Center

Kubik, Martha Y.; Davey, Cynthia; Fulkerson, Jayne A.; Sirard, John; Story, Mary; Arcan, Chrisa

2009-01-01

Objective: To determine prevalence and correlates of overweight among adolescents attending alternative high schools (AHS). Methods: AHS students (n=145) from 6 schools completed surveys and anthropometric measures. Cross-sectional associations were assessed using mixed model multivariate logistic regression. Results: Among students, 42% were…

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data

PubMed Central

Su, Li; Farewell, Vernon T

2013-01-01

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally. PMID:24201470

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.

Comparison of four methods for deriving hospital standardised mortality ratios from a single hierarchical logistic regression model.

PubMed

Mohammed, Mohammed A; Manktelow, Bradley N; Hofer, Timothy P

2016-04-01

There is interest in deriving case-mix adjusted standardised mortality ratios so that comparisons between healthcare providers, such as hospitals, can be undertaken in the controversial belief that variability in standardised mortality ratios reflects quality of care. Typically standardised mortality ratios are derived using a fixed effects logistic regression model, without a hospital term in the model. This fails to account for the hierarchical structure of the data - patients nested within hospitals - and so a hierarchical logistic regression model is more appropriate. However, four methods have been advocated for deriving standardised mortality ratios from a hierarchical logistic regression model, but their agreement is not known and neither do we know which is to be preferred. We found significant differences between the four types of standardised mortality ratios because they reflect a range of underlying conceptual issues. The most subtle issue is the distinction between asking how an average patient fares in different hospitals versus how patients at a given hospital fare at an average hospital. Since the answers to these questions are not the same and since the choice between these two approaches is not obvious, the extent to which profiling hospitals on mortality can be undertaken safely and reliably, without resolving these methodological issues, remains questionable. © The Author(s) 2012.

A corrected formulation for marginal inference derived from two-part mixed models for longitudinal semi-continuous data.

PubMed

Tom, Brian Dm; Su, Li; Farewell, Vernon T

2016-10-01

For semi-continuous data which are a mixture of true zeros and continuously distributed positive values, the use of two-part mixed models provides a convenient modelling framework. However, deriving population-averaged (marginal) effects from such models is not always straightforward. Su et al. presented a model that provided convenient estimation of marginal effects for the logistic component of the two-part model but the specification of marginal effects for the continuous part of the model presented in that paper was based on an incorrect formulation. We present a corrected formulation and additionally explore the use of the two-part model for inferences on the overall marginal mean, which may be of more practical relevance in our application and more generally. © The Author(s) 2013.

Do Mixed-Flora Preoperative Urine Cultures Matter?

PubMed

Polin, Michael R; Kawasaki, Amie; Amundsen, Cindy L; Weidner, Alison C; Siddiqui, Nazema Y

2017-06-01

To determine whether mixed-flora preoperative urine cultures, as compared with no-growth preoperative urine cultures, are associated with a higher prevalence of postoperative urinary tract infections (UTIs). This was a retrospective cohort study. Women who underwent urogynecologic surgery were included if their preoperative clean-catch urine culture result was mixed flora or no growth. Women were excluded if they received postoperative antibiotics for reasons other than treatment of a UTI. Women were divided into two cohorts based on preoperative urine culture results-mixed flora or no growth; the prevalence of postoperative UTI was compared between cohorts. Baseline characteristics were compared using χ 2 or Student t tests. A logistic regression analysis then was performed. We included 282 women who were predominantly postmenopausal, white, and overweight. There were many concomitant procedures; 46% underwent a midurethral sling procedure and 68% underwent pelvic organ prolapse surgery. Preoperative urine cultures resulted as mixed flora in 192 (68%) and no growth in 90 (32%) patients. Overall, 14% were treated for a UTI postoperatively. There was no difference in the proportion of patients treated for a postoperative UTI between the two cohorts (25 mixed flora vs 13 no growth, P = 0.77). These results remained when controlling for potentially confounding variables in a logistic regression model (adjusted odds ratio 0.92, 95% confidence interval 0.43-1.96). In women with mixed-flora compared with no-growth preoperative urine cultures, there were no differences in the prevalence of postoperative UTI. The clinical practice of interpreting mixed-flora cultures as negative is appropriate.

Inspection logistics planning for multi-stage production systems with applications to semiconductor fabrication lines

NASA Astrophysics Data System (ADS)

Chen, Kyle Dakai

Since the market for semiconductor products has become more lucrative and competitive, research into improving yields for semiconductor fabrication lines has lately received a tremendous amount of attention. One of the most critical tasks in achieving such yield improvements is to plan the in-line inspection sampling efficiently so that any potential yield problems can be detected early and eliminated quickly. We formulate a multi-stage inspection planning model based on configurations in actual semiconductor fabrication lines, specifically taking into account both the capacity constraint and the congestion effects at the inspection station. We propose a new mixed First-Come-First-Serve (FCFS) and Last-Come-First-Serve (LCFS) discipline for serving the inspection samples to expedite the detection of potential yield problems. Employing this mixed FCFS and LCFS discipline, we derive approximate expressions for the queueing delays in yield problem detection time and develop near-optimal algorithms to obtain the inspection logistics planning policies. We also investigate the queueing performance with this mixed type of service discipline under different assumptions and configurations. In addition, we conduct numerical tests and generate managerial insights based on input data from actual semiconductor fabrication lines. To the best of our knowledge, this research is novel in developing, for the first time in the literature, near-optimal results for inspection logistics planning in multi-stage production systems with congestion effects explicitly considered.

Comparing colon cancer outcomes: The impact of low hospital case volume and case-mix adjustment.

PubMed

Fischer, C; Lingsma, H F; van Leersum, N; Tollenaar, R A E M; Wouters, M W; Steyerberg, E W

2015-08-01

When comparing performance across hospitals it is essential to consider the noise caused by low hospital case volume and to perform adequate case-mix adjustment. We aimed to quantify the role of noise and case-mix adjustment on standardized postoperative mortality and anastomotic leakage (AL) rates. We studied 13,120 patients who underwent colon cancer resection in 85 Dutch hospitals. We addressed differences between hospitals in postoperative mortality and AL, using fixed (ignoring noise) and random effects (incorporating noise) logistic regression models with general and additional, disease specific, case-mix adjustment. Adding disease specific variables improved the performance of the case-mix adjustment models for postoperative mortality (c-statistic increased from 0.77 to 0.81). The overall variation in standardized mortality ratios was similar, but some individual hospitals changed considerably. For the standardized AL rates the performance of the adjustment models was poor (c-statistic 0.59 and 0.60) and overall variation was small. Most of the observed variation between hospitals was actually noise. Noise had a larger effect on hospital performance than extended case-mix adjustment, although some individual hospital outcome rates were affected by more detailed case-mix adjustment. To compare outcomes between hospitals it is crucial to consider noise due to low hospital case volume with a random effects model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gene set differential analysis of time course expression profiles via sparse estimation in functional logistic model with application to time-dependent biomarker detection.

PubMed

Kayano, Mitsunori; Matsui, Hidetoshi; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2016-04-01

High-throughput time course expression profiles have been available in the last decade due to developments in measurement techniques and devices. Functional data analysis, which treats smoothed curves instead of originally observed discrete data, is effective for the time course expression profiles in terms of dimension reduction, robustness, and applicability to data measured at small and irregularly spaced time points. However, the statistical method of differential analysis for time course expression profiles has not been well established. We propose a functional logistic model based on elastic net regularization (F-Logistic) in order to identify the genes with dynamic alterations in case/control study. We employ a mixed model as a smoothing method to obtain functional data; then F-Logistic is applied to time course profiles measured at small and irregularly spaced time points. We evaluate the performance of F-Logistic in comparison with another functional data approach, i.e. functional ANOVA test (F-ANOVA), by applying the methods to real and synthetic time course data sets. The real data sets consist of the time course gene expression profiles for long-term effects of recombinant interferon β on disease progression in multiple sclerosis. F-Logistic distinguishes dynamic alterations, which cannot be found by competitive approaches such as F-ANOVA, in case/control study based on time course expression profiles. F-Logistic is effective for time-dependent biomarker detection, diagnosis, and therapy. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Dysglycemia, Glycemic Variability, and Outcome After Cardiac Arrest and Temperature Management at 33°C and 36°C.

PubMed

Borgquist, Ola; Wise, Matt P; Nielsen, Niklas; Al-Subaie, Nawaf; Cranshaw, Julius; Cronberg, Tobias; Glover, Guy; Hassager, Christian; Kjaergaard, Jesper; Kuiper, Michael; Smid, Ondrej; Walden, Andrew; Friberg, Hans

2017-08-01

Dysglycemia and glycemic variability are associated with poor outcomes in critically ill patients. Targeted temperature management alters blood glucose homeostasis. We investigated the association between blood glucose concentrations and glycemic variability and the neurologic outcomes of patients randomized to targeted temperature management at 33°C or 36°C after cardiac arrest. Post hoc analysis of the multicenter TTM-trial. Primary outcome of this analysis was neurologic outcome after 6 months, referred to as "Cerebral Performance Category." Thirty-six sites in Europe and Australia. All 939 patients with out-of-hospital cardiac arrest of presumed cardiac cause that had been included in the TTM-trial. Targeted temperature management at 33°C or 36°C. Nonparametric tests as well as multiple logistic regression and mixed effects logistic regression models were used. Median glucose concentrations on hospital admission differed significantly between Cerebral Performance Category outcomes (p < 0.0001). Hyper- and hypoglycemia were associated with poor neurologic outcome (p = 0.001 and p = 0.054). In the multiple logistic regression models, the median glycemic level was an independent predictor of poor Cerebral Performance Category (Cerebral Performance Category, 3-5) with an odds ratio (OR) of 1.13 in the adjusted model (p = 0.008; 95% CI, 1.03-1.24). It was also a predictor in the mixed model, which served as a sensitivity analysis to adjust for the multiple time points. The proportion of hyperglycemia was higher in the 33°C group compared with the 36°C group. Higher blood glucose levels at admission and during the first 36 hours, and higher glycemic variability, were associated with poor neurologic outcome and death. More patients in the 33°C treatment arm had hyperglycemia.

Associations between Responsible Beverage Service Laws and Binge Drinking and Alcohol-Impaired Driving

ERIC Educational Resources Information Center

Linde, Ann C.; Toomey, Traci L.; Wolfson, Julian; Lenk, Kathleen M.; Jones-Webb, Rhonda; Erickson, Darin J.

2016-01-01

We explored potential associations between the strength of state Responsible Beverage Service (RBS) laws and self-reported binge drinking and alcohol-impaired driving in the U.S. A multi-level logistic mixed-effects model was used, adjusting for potential confounders. Analyses were conducted on the overall BRFSS sample and drinkers only. Seven…

Multicriteria Cost Assessment and Logistics Modeling for Military Humanitarian Assistance and Disaster Relief Aerial Delivery Operations

DTIC Science & Technology

2015-03-01

vulnerable people will have access to this airdropped consumable aid (since nobody 1 is necessarily coordinating the distribution on the ground... VBA ) platforms (see Appendix B). In particular, we used GAMS v.23.9.3 with IBM ILOG CPLEX 12.4.0.1 to solve the stochastic, mixed-integer weighted...goal programming model, and we used Excel/ VBA to create an auto- matic, user-friendly interface with the decision maker for model input and analysis of

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

Physician-based activity counseling: intervention effects on mediators of motivational readiness for physical activity.

PubMed

Pinto, B M; Lynn, H; Marcus, B H; DePue, J; Goldstein, M G

2001-01-01

In theory-based interventions for behavior change, there is a need to examine the effects of interventions on the underlying theoretical constructs and the mediating role of such constructs. These two questions are addressed in the Physically Active for Life study, a randomized trial of physician-based exercise counseling for older adults. Three hundred fifty-five patients participated (intervention n = 181, control n = 174; mean age = 65.6 years). The underlying theories used were the Transtheoretical Model, Social Cognitive Theory and the constructs of decisional balance (benefits and barriers), self-efficacy, and behavioral and cognitive processes of change. Motivational readiness for physical activity and related constructs were assessed at baseline, 6 weeks, and 8 months. Linear or logistic mixed effects models were used to examine intervention effects on the constructs, and logistic mixed effects models were used for mediator analyses. At 6 weeks, the intervention had significant effects on decisional balance, self-efficacy, and behavioral processes, but these effects were not maintained at 8 months. At 6 weeks, only decisional balance and behavioral processes were identified as mediators of motivational readiness outcomes. Results suggest that interventions of greater intensity and duration may be needed for sustained changes in mediators and motivational readiness for physical activity among older adults.

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.

Synergistic effect of pulsed electric fields and CocoanOX 12% on the inactivation kinetics of Bacillus cereus in a mixed beverage of liquid whole egg and skim milk.

PubMed

Pina-Pérez, M C; Silva-Angulo, A B; Rodrigo, D; Martínez-López, A

2009-04-15

With a view to extending the shelf-life and enhancing the safety of liquid whole egg/skim milk (LWE-SM) mixed beverages, a study was conducted with Bacillus cereus vegetative cells inoculated in skim milk (SM) and LWE-SM beverages, with or without antimicrobial cocoa powder. The beverages were treated with Pulsed Electric Field (PEF) technology and then stored at 5 degrees C for 15 days. The kinetic results were modeled with the Bigelow model, Weibull distribution function, modified Gompertz equation, and Log-logistic models. Maximum inactivation registered a reduction of around 3 log cycles at 40 kV/cm, 360 micros, 20 degrees C in both the SM and LWE-SM beverages. By contrast, in the beverages supplemented with the aforementioned antimicrobial compound, higher inactivation levels were obtained under the same treatment conditions, reaching a 3.30 log(10) cycle reduction. The model affording the best fit for all four beverages was the four-parameter Log-logistic model. After 15 days of storage, the antimicrobial compound lowered Bacillus cereus survival rates in the samples supplemented with CocoanOX 12% by a 4 log cycle reduction, as compared to the untreated samples without CocoanOX 12%. This could indicate that the PEF-antimicrobial combination has a synergistic effect on the bacterial cells under study, increasing their sensitivity to subsequent refrigerated storage.

Kinetic models for batch ethanol production from sweet sorghum juice under normal and high gravity fermentations: Logistic and modified Gompertz models.

PubMed

Phukoetphim, Niphaphat; Salakkam, Apilak; Laopaiboon, Pattana; Laopaiboon, Lakkana

2017-02-10

The aim of this study was to model batch ethanol production from sweet sorghum juice (SSJ), under normal gravity (NG, 160g/L of total sugar) and high gravity (HG, 240g/L of total sugar) conditions with and without nutrient supplementation (9g/L of yeast extract), by Saccharomyces cerevisiae NP 01. Growth and ethanol production increased with increasing initial sugar concentration, and the addition of yeast extract enhanced both cell growth and ethanol production. From the results, either logistic or a modified Gompertz equation could be used to describe yeast growth, depending on information required. Furthermore, the modified Gompertz model was suitable for modeling ethanol production. Both the models fitted the data very well with coefficients of determination exceeding 0.98. The results clearly showed that these models can be employed in the development of ethanol production processes using SSJ under both NG and HG conditions. The models were also shown to be applicable to other ethanol fermentation systems employing pure and mixed sugars as carbon sources. Copyright © 2016 Elsevier B.V. All rights reserved.

Multilevel mixed effects parametric survival models using adaptive Gauss-Hermite quadrature with application to recurrent events and individual participant data meta-analysis.

PubMed

Crowther, Michael J; Look, Maxime P; Riley, Richard D

2014-09-28

Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods. Copyright © 2014 John Wiley & Sons, Ltd.

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed Central

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-01-01

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. PMID:28952708

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-09-27

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. Creative Commons Attribution License

A comparison of three random effects approaches to analyze repeated bounded outcome scores with an application in a stroke revalidation study.

PubMed

Molas, Marek; Lesaffre, Emmanuel

2008-12-30

Discrete bounded outcome scores (BOS), i.e. discrete measurements that are restricted on a finite interval, often occur in practice. Examples are compliance measures, quality of life measures, etc. In this paper we examine three related random effects approaches to analyze longitudinal studies with a BOS as response: (1) a linear mixed effects (LM) model applied to a logistic transformed modified BOS; (2) a model assuming that the discrete BOS is a coarsened version of a latent random variable, which after a logistic-normal transformation, satisfies an LM model; and (3) a random effects probit model. We consider also the extension whereby the variability of the BOS is allowed to depend on covariates. The methods are contrasted using a simulation study and on a longitudinal project, which documents stroke rehabilitation in four European countries using measures of motor and functional recovery. Copyright 2008 John Wiley & Sons, Ltd.

Dynamic trends in cardiac surgery: why the logistic EuroSCORE is no longer suitable for contemporary cardiac surgery and implications for future risk models

PubMed Central

Hickey, Graeme L.; Grant, Stuart W.; Murphy, Gavin J.; Bhabra, Moninder; Pagano, Domenico; McAllister, Katherine; Buchan, Iain; Bridgewater, Ben

2013-01-01

OBJECTIVES Progressive loss of calibration of the original EuroSCORE models has necessitated the introduction of the EuroSCORE II model. Poor model calibration has important implications for clinical decision-making and risk adjustment of governance analyses. The objective of this study was to explore the reasons for the calibration drift of the logistic EuroSCORE. METHODS Data from the Society for Cardiothoracic Surgery in Great Britain and Ireland database were analysed for procedures performed at all National Health Service and some private hospitals in England and Wales between April 2001 and March 2011. The primary outcome was in-hospital mortality. EuroSCORE risk factors, overall model calibration and discrimination were assessed over time. RESULTS A total of 317 292 procedures were included. Over the study period, mean age at surgery increased from 64.6 to 67.2 years. The proportion of procedures that were isolated coronary artery bypass grafts decreased from 67.5 to 51.2%. In-hospital mortality fell from 4.1 to 2.8%, but the mean logistic EuroSCORE increased from 5.6 to 7.6%. The logistic EuroSCORE remained a good discriminant throughout the study period (area under the receiver-operating characteristic curve between 0.79 and 0.85), but calibration (observed-to-expected mortality ratio) fell from 0.76 to 0.37. Inadequate adjustment for decreasing baseline risk affected calibration considerably. DISCUSSIONS Patient risk factors and case-mix in adult cardiac surgery change dynamically over time. Models like the EuroSCORE that are developed using a ‘snapshot’ of data in time do not account for this and can subsequently lose calibration. It is therefore important to regularly revalidate clinical prediction models. PMID:23152436

An analysis of the adoption of managerial innovation: cost accounting systems in hospitals.

PubMed

Glandon, G L; Counte, M A

1995-11-01

The adoption of new medical technologies has received significant attention in the hospital industry, in part, because of its observed relation to hospital cost increases. However, few comprehensive studies exist regarding the adoption of non-medical technologies in the hospital setting. This paper develops and tests a model of the adoption of a managerial innovation, new to the hospital industry, that of cost accounting systems based upon standard costs. The conceptual model hypothesizes that four organizational context factors (size, complexity, ownership and slack resources) and two environmental factors (payor mix and interorganizational dependency) influence hospital adoption of cost accounting systems. Based on responses to a mail survey of hospitals in the Chicago area and AHA annual survey information for 1986, a sample of 92 hospitals was analyzed. Greater hospital size, complexity, slack resources, and interorganizational dependency all were associated with adoption. Payor mix had no significant influence and the hospital ownership variables had a mixed influence. The logistic regression model was significant overall and explained over 15% of the variance in the adoption decision.

Retrospective analysis of Bluetongue farm risk profile definition, based on biology, farm management practices and climatic data.

PubMed

Cappai, Stefano; Loi, Federica; Coccollone, Annamaria; Contu, Marino; Capece, Paolo; Fiori, Michele; Canu, Simona; Foxi, Cipriano; Rolesu, Sandro

2018-07-01

Bluetongue (BT) is a vector-borne disease transmitted by species of Culicoides midges (Diptera: Ceratopogonidae). Many studies have contributed to clarifying various aspects of its aetiology, epidemiology and vector dynamic; however, BT remains a disease of epidemiological and economic importance that affects ruminants worldwide. Since 2000, the Sardinia region has been the most affected area of the Mediterranean basin. The region is characterised by wide pastoral areas for sheep and represents the most likely candidate region for the study of Bluetongue virus (BTV) distribution and prevalence in Italy. Furthermore, specific information on the farm level and epidemiological studies needs to be provided to increase the knowledge on the disease's spread and to provide valid mitigation strategies in Sardinia. This study conducted a punctual investigation into the spatial patterns of BTV transmission to define a risk profile for all Sardinian farmsby using a logistic multilevel mixed model that take into account agro-meteorological aspects, as well as farm characteristics and management. Data about animal density (i.e. sheep, goats and cattle), vaccination, previous outbreaks, altitude, land use, rainfall, evapotranspiration, water surface, and farm management practices (i.e. use of repellents, treatment against insect vectors, storage of animals in shelter overnight, cleaning, presence of mud and manure) were collected for 12,277 farms for the years 2011-2015. The logistic multilevel mixed model showed the fundamental role of climatic factors in disease development and the protective role of good management, vaccination, outbreak in the previous year and altitude. Regional BTV risk maps were developed, based on the predictor values of logistic model results, and updated every 10 days. These maps were used to identify, 20 days in advance, the areas at highest risk. The risk farm profile, as defined by the model, would provide specific information about the role of each factor for all Sardinian institutions involved in devising BT prevention and control strategies. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

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.

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

Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model.

PubMed

Steven Ernest, C; Nyberg, Joakim; Karlsson, Mats O; Hooker, Andrew C

2014-12-01

D-optimal designs for discrete-type responses have been derived using generalized linear mixed models, simulation based methods and analytical approximations for computing the fisher information matrix (FIM) of non-linear mixed effect models with homogeneous probabilities over time. In this work, D-optimal designs using an analytical approximation of the FIM for a dichotomous, non-homogeneous, Markov-chain phase advanced sleep non-linear mixed effect model was investigated. The non-linear mixed effect model consisted of transition probabilities of dichotomous sleep data estimated as logistic functions using piecewise linear functions. Theoretical linear and nonlinear dose effects were added to the transition probabilities to modify the probability of being in either sleep stage. D-optimal designs were computed by determining an analytical approximation the FIM for each Markov component (one where the previous state was awake and another where the previous state was asleep). Each Markov component FIM was weighted either equally or by the average probability of response being awake or asleep over the night and summed to derive the total FIM (FIM(total)). The reference designs were placebo, 0.1, 1-, 6-, 10- and 20-mg dosing for a 2- to 6-way crossover study in six dosing groups. Optimized design variables were dose and number of subjects in each dose group. The designs were validated using stochastic simulation/re-estimation (SSE). Contrary to expectations, the predicted parameter uncertainty obtained via FIM(total) was larger than the uncertainty in parameter estimates computed by SSE. Nevertheless, the D-optimal designs decreased the uncertainty of parameter estimates relative to the reference designs. Additionally, the improvement for the D-optimal designs were more pronounced using SSE than predicted via FIM(total). Through the use of an approximate analytic solution and weighting schemes, the FIM(total) for a non-homogeneous, dichotomous Markov-chain phase advanced sleep model was computed and provided more efficient trial designs and increased nonlinear mixed-effects modeling parameter precision.

Performance of the score systems Acute Physiology and Chronic Health Evaluation II and III at an interdisciplinary intensive care unit, after customization

PubMed Central

Markgraf, Rainer; Deutschinoff, Gerd; Pientka, Ludger; Scholten, Theo; Lorenz, Cristoph

2001-01-01

Background: Mortality predictions calculated using scoring scales are often not accurate in populations other than those in which the scales were developed because of differences in case-mix. The present study investigates the effect of first-level customization, using a logistic regression technique, on discrimination and calibration of the Acute Physiology and Chronic Health Evaluation (APACHE) II and III scales. Method: Probabilities of hospital death for patients were estimated by applying APACHE II and III and comparing these with observed outcomes. Using the split sample technique, a customized model to predict outcome was developed by logistic regression. The overall goodness-of-fit of the original and the customized models was assessed. Results: Of 3383 consecutive intensive care unit (ICU) admissions over 3 years, 2795 patients could be analyzed, and were split randomly into development and validation samples. The discriminative powers of APACHE II and III were unchanged by customization (areas under the receiver operating characteristic [ROC] curve 0.82 and 0.85, respectively). Hosmer-Lemeshow goodness-of-fit tests showed good calibration for APACHE II, but insufficient calibration for APACHE III. Customization improved calibration for both models, with a good fit for APACHE III as well. However, fit was different for various subgroups. Conclusions: The overall goodness-of-fit of APACHE III mortality prediction was improved significantly by customization, but uniformity of fit in different subgroups was not achieved. Therefore, application of the customized model provides no advantage, because differences in case-mix still limit comparisons of quality of care. PMID:11178223

Evaluating the benefits of digital pathology implementation: Time savings in laboratory logistics.

PubMed

Baidoshvili, Alexi; Bucur, Anca; van Leeuwen, Jasper; van der Laak, Jeroen; Kluin, Philip; van Diest, Paul J

2018-06-20

The benefits of digital pathology for workflow improvement and thereby cost savings in pathology, at least partly outweighing investment costs, are increasingly recognized. Successful implementations in a variety of scenarios start to demonstrate cost benefits of digital pathology for both research and routine diagnostics, contributing to a sound business case encouraging further adoption. To further support new adopters, there is still a need for detailed assessment of the impact this technology has on the relevant pathology workflows with emphasis on time saving. To assess the impact of digital pathology adoption on logistic laboratory tasks (i.e. not including pathologists' time for diagnosis making) in LabPON, a large regional pathology laboratory in The Netherlands. To quantify the benefits of digitization we analyzed the differences between the traditional analog and new digital workflows, carried out detailed measurements of all relevant steps in key analog and digital processes, and compared time spent. We modeled and assessed the logistic savings in five workflows: (1) Routine diagnosis, (2) Multi-disciplinary meeting, (3) External revision requests, (4) Extra stainings and (5) External consultation. On average over 19 working hours were saved on a typical day by working digitally, with the highest savings in routine diagnosis and multi-disciplinary meeting workflows. By working digitally, a significant amount of time could be saved in a large regional pathology lab with a typical case mix. We also present the data in each workflow per task and concrete logistic steps to allow extrapolation to the context and case mix of other laboratories. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Identifying the optimal segmentors for mass classification in mammograms

NASA Astrophysics Data System (ADS)

Zhang, Yu; Tomuro, Noriko; Furst, Jacob; Raicu, Daniela S.

2015-03-01

In this paper, we present the results of our investigation on identifying the optimal segmentor(s) from an ensemble of weak segmentors, used in a Computer-Aided Diagnosis (CADx) system which classifies suspicious masses in mammograms as benign or malignant. This is an extension of our previous work, where we used various parameter settings of image enhancement techniques to each suspicious mass (region of interest (ROI)) to obtain several enhanced images, then applied segmentation to each image to obtain several contours of a given mass. Each segmentation in this ensemble is essentially a "weak segmentor" because no single segmentation can produce the optimal result for all images. Then after shape features are computed from the segmented contours, the final classification model was built using logistic regression. The work in this paper focuses on identifying the optimal segmentor(s) from an ensemble mix of weak segmentors. For our purpose, optimal segmentors are those in the ensemble mix which contribute the most to the overall classification rather than the ones that produced high precision segmentation. To measure the segmentors' contribution, we examined weights on the features in the derived logistic regression model and computed the average feature weight for each segmentor. The result showed that, while in general the segmentors with higher segmentation success rates had higher feature weights, some segmentors with lower segmentation rates had high classification feature weights as well.

Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

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.

Perceived Risk of Burglary and Fear of Crime: Individual- and Country-Level Mixed Modeling.

PubMed

Chon, Don Soo; Wilson, Mary

2016-02-01

Given the scarcity of prior studies, the current research introduced country-level variables, along with individual-level ones, to test how they are related to an individual's perceived risk of burglary (PRB) and fear of crime (FC), separately, by using mixed-level logistic regression analyses. The analyses of 104,218 individuals, residing in 50 countries, showed that country-level poverty was positively associated with FC only. However, individual-level variables, such as prior property crime victimization and female gender, had consistently positive relationships with both PRB and FC. However, age group and socioeconomic status were inconsistent between those two models, suggesting that PRB and FC are two different concepts. Finally, no significant difference in the pattern of PRB and FC was found between a highly developed group of countries and a less developed one. © The Author(s) 2014.

Safety analysis of urban signalized intersections under mixed traffic.

PubMed

S, Anjana; M V L R, Anjaneyulu

2015-02-01

This study examined the crash causative factors of signalized intersections under mixed traffic using advanced statistical models. Hierarchical Poisson regression and logistic regression models were developed to predict the crash frequency and severity of signalized intersection approaches. The prediction models helped to develop general safety countermeasures for signalized intersections. The study shows that exclusive left turn lanes and countdown timers are beneficial for improving the safety of signalized intersections. Safety is also influenced by the presence of a surveillance camera, green time, median width, traffic volume, and proportion of two wheelers in the traffic stream. The factors that influence the severity of crashes were also identified in this study. As a practical application, the safe values of deviation of green time provided from design green time, with varying traffic volume, is presented in this study. This is a useful tool for setting the appropriate green time for a signalized intersection approach with variations in the traffic volume. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessment of eight HPV vaccination programs implemented in lowest income countries.

PubMed

Ladner, Joël; Besson, Marie-Hélène; Hampshire, Rachel; Tapert, Lisa; Chirenje, Mike; Saba, Joseph

2012-05-23

Cervix cancer, preventable, continues to be the third most common cancer in women worldwide, especially in lowest income countries. Prophylactic HPV vaccination should help to reduce the morbidity and mortality associated with cervical cancer. The purpose of the study was to describe the results of and key concerns in eight HPV vaccination programs conducted in seven lowest income countries through the Gardasil Access Program (GAP). The GAP provides free HPV vaccine to organizations and institutions in lowest income countries. The HPV vaccination programs were entirely developed, implemented and managed by local institutions. Institutions submitted application forms with institution characteristics, target population, communication delivery strategies. After completion of the vaccination campaign (3 doses), institutions provided a final project report with data on doses administered and vaccination models. Two indicators were calculated, the program vaccination coverage and adherence. Qualitative data were also collected in the following areas: government and community involvement; communication, and sensitization; training and logistics resources, and challenges. A total of eight programs were implemented in seven countries. The eight programs initially targeted a total of 87,580 girls, of which 76,983 received the full 3-dose vaccine course, with mean program vaccination coverage of 87.8%; the mean adherence between the first and third doses of vaccine was 90.9%. Three programs used school-based delivery models, 2 used health facility-based models, and 3 used mixed models that included schools and health facilities. Models that included school-based vaccination were most effective at reaching girls aged 9-13 years. Mixed models comprising school and health facility-based vaccination had better overall performance compared with models using just one of the methods. Increased rates of program coverage and adherence were positively correlated with the number of vaccination sites. Qualitative key insights from the school models showed a high level of coordination and logistics to facilitate vaccination administration, a lower risk of girls being lost to follow-up and vaccinations conducted within the academic year limit the number of girls lost to follow-up. Mixed models that incorporate both schools and health facilities appear to be the most effective at delivering HPV vaccine. This study provides lessons for development of public health programs and policies as countries go forward in national decision-making for HPV vaccination.

Assessment of eight HPV vaccination programs implemented in lowest income countries

PubMed Central

2012-01-01

Background Cervix cancer, preventable, continues to be the third most common cancer in women worldwide, especially in lowest income countries. Prophylactic HPV vaccination should help to reduce the morbidity and mortality associated with cervical cancer. The purpose of the study was to describe the results of and key concerns in eight HPV vaccination programs conducted in seven lowest income countries through the Gardasil Access Program (GAP). Methods The GAP provides free HPV vaccine to organizations and institutions in lowest income countries. The HPV vaccination programs were entirely developed, implemented and managed by local institutions. Institutions submitted application forms with institution characteristics, target population, communication delivery strategies. After completion of the vaccination campaign (3 doses), institutions provided a final project report with data on doses administered and vaccination models. Two indicators were calculated, the program vaccination coverage and adherence. Qualitative data were also collected in the following areas: government and community involvement; communication, and sensitization; training and logistics resources, and challenges. Results A total of eight programs were implemented in seven countries. The eight programs initially targeted a total of 87,580 girls, of which 76,983 received the full 3-dose vaccine course, with mean program vaccination coverage of 87.8%; the mean adherence between the first and third doses of vaccine was 90.9%. Three programs used school-based delivery models, 2 used health facility-based models, and 3 used mixed models that included schools and health facilities. Models that included school-based vaccination were most effective at reaching girls aged 9-13 years. Mixed models comprising school and health facility-based vaccination had better overall performance compared with models using just one of the methods. Increased rates of program coverage and adherence were positively correlated with the number of vaccination sites. Qualitative key insights from the school models showed a high level of coordination and logistics to facilitate vaccination administration, a lower risk of girls being lost to follow-up and vaccinations conducted within the academic year limit the number of girls lost to follow-up. Conclusion Mixed models that incorporate both schools and health facilities appear to be the most effective at delivering HPV vaccine. This study provides lessons for development of public health programs and policies as countries go forward in national decision-making for HPV vaccination. PMID:22621342

Medicaid payment rates, case-mix reimbursement, and nursing home staffing--1996-2004.

PubMed

Feng, Zhanlian; Grabowski, David C; Intrator, Orna; Zinn, Jacqueline; Mor, Vincent

2008-01-01

We examined the impact of state Medicaid payment rates and case-mix reimbursement on direct care staffing levels in US nursing homes. We used a recent time series of national nursing home data from the Online Survey Certification and Reporting system for 1996-2004, merged with annual state Medicaid payment rates and case-mix reimbursement information. A 5-category response measure of total staffing levels was defined according to expert recommended thresholds, and examined in a multinomial logistic regression model. Facility fixed-effects models were estimated separately for Registered Nurse (RN), Licensed Practical Nurse (LPN), and Certified Nurse Aide (CNA) staffing levels measured as average hours per resident day. Higher Medicaid payment rates were associated with increases in total staffing levels to meet a higher recommended threshold. However, these gains in overall staffing were accompanied by a reduction of RN staffing and an increase in both LPN and CNA staffing levels. Under case-mix reimbursement, the likelihood of nursing homes achieving higher recommended staffing thresholds decreased, as did levels of professional staffing. Independent of the effects of state, market, and facility characteristics, there was a significant downward trend in RN staffing and an upward trend in both LPN and CNA staffing. Although overall staffing may increase in response to more generous Medicaid reimbursement, it may not translate into improvements in the skill mix of staff. Adjusting for reimbursement levels and resident acuity, total staffing has not increased after the implementation of case-mix reimbursement.

Logistics system design for biomass-to-bioenergy industry with multiple types of feedstocks.

PubMed

Zhu, Xiaoyan; Yao, Qingzhu

2011-12-01

It is technologically possible for a biorefinery to use a variety of biomass as feedstock including native perennial grasses (e.g., switchgrass) and agricultural residues (e.g., corn stalk and wheat straw). Incorporating the distinct characteristics of various types of biomass feedstocks and taking into account their interaction in supplying the bioenergy production, this paper proposed a multi-commodity network flow model to design the logistics system for a multiple-feedstock biomass-to-bioenergy industry. The model was formulated as a mixed integer linear programming, determining the locations of warehouses, the size of harvesting team, the types and amounts of biomass harvested/purchased, stored, and processed in each month, the transportation of biomass in the system, and so on. This paper demonstrated the advantages of using multiple types of biomass feedstocks by comparing with the case of using a single feedstock (switchgrass) and analyzed the relationship of the supply capacity of biomass feedstocks to the output and cost of biofuel. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling recall memory for emotional objects in Alzheimer's disease.

PubMed

Sundstrøm, Martin

2011-07-01

To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p < .003). EM was not found for recognition in AD patients due to a ceiling effect. Healthy older adults scored overall higher in recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p < .014) and object status (p < .0001) as gift or non-gift. Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

Self-declared stock ownership and association with positive trial outcome in randomized controlled trials with binary outcomes published in general medical journals: a cross-sectional study.

PubMed

Falk Delgado, Alberto; Falk Delgado, Anna

2017-07-26

Describe the prevalence and types of conflicts of interest (COI) in published randomized controlled trials (RCTs) in general medical journals with a binary primary outcome and assess the association between conflicts of interest and favorable outcome. Parallel-group RCTs with a binary primary outcome published in three general medical journals during 2013-2015 were identified. COI type, funding source, and outcome were extracted. Binomial logistic regression model was performed to assess association between COI and funding source with outcome. A total of 509 consecutive parallel-group RCTs were included in the study. COI was reported in 74% in mixed funded RCTs and in 99% in for-profit funded RCTs. Stock ownership was reported in none of the non-profit RCTs, in 7% of mixed funded RCTs, and in 50% of for-profit funded RCTs. Mixed-funded RCTs had employees from the funding company in 11% and for-profit RCTs in 76%. Multivariable logistic regression revealed that stock ownership in the funding company among any of the authors was associated with a favorable outcome (odds ratio = 3.53; 95% confidence interval = 1.59-7.86; p < 0.01). COI in for-profit funded RCTs is extensive, because the factors related to COI are not fully independent, a multivariable analysis should be cautiously interpreted. However, after multivariable adjustment only stock ownership from the funding company among authors is associated with a favorable outcome.

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.

An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

PubMed Central

Zhang, Dezhi; Li, Shuangyan

2014-01-01

This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209

An optimal hierarchical decision model for a regional logistics network with environmental impact consideration.

PubMed

Zhang, Dezhi; Li, Shuangyan; Qin, Jin

2014-01-01

This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

The role of gender in a smoking cessation intervention: a cluster randomized clinical trial.

PubMed

Puente, Diana; Cabezas, Carmen; Rodriguez-Blanco, Teresa; Fernández-Alonso, Carmen; Cebrian, Tránsito; Torrecilla, Miguel; Clemente, Lourdes; Martín, Carlos

2011-05-23

The prevalence of smoking in Spain is high in both men and women. The aim of our study was to evaluate the role of gender in the effectiveness of a specific smoking cessation intervention conducted in Spain. This study was a secondary analysis of a cluster randomized clinical trial in which the randomization unit was the Basic Care Unit (family physician and nurse who care for the same group of patients). The intervention consisted of a six-month period of implementing the recommendations of a Clinical Practice Guideline. A total of 2,937 current smokers at 82 Primary Care Centers in 13 different regions of Spain were included (2003-2005). The success rate was measured by a six-month continued abstinence rate at the one-year follow-up. A logistic mixed-effects regression model, taking Basic Care Units as random-effect parameter, was performed in order to analyze gender as a predictor of smoking cessation. At the one-year follow-up, the six-month continuous abstinence quit rate was 9.4% in men and 8.5% in women (p = 0.400). The logistic mixed-effects regression model showed that women did not have a higher odds of being an ex-smoker than men after the analysis was adjusted for confounders (OR adjusted = 0.9, 95% CI = 0.7-1.2). Gender does not appear to be a predictor of smoking cessation at the one-year follow-up in individuals presenting at Primary Care Centers. CLINICALTRIALS.GOV IDENTIFIER: NCT00125905.

Expert Design Advisor

DTIC Science & Technology

1990-10-01

to economic, technological, spatial or logistic concerns, or involve training, man-machine interfaces, or integration into existing systems. Once the...probabilistic reasoning, mixed analysis- and simulation-oriented, mixed computation- and communication-oriented, nonpreemptive static priority...scheduling base, nonrandomized, preemptive static priority scheduling base, randomized, simulation-oriented, and static scheduling base. The selection of both

A novel approach to mixing qualitative and quantitative methods in HIV and STI prevention research.

PubMed

Penman-Aguilar, Ana; Macaluso, Maurizio; Peacock, Nadine; Snead, M Christine; Posner, Samuel F

2014-04-01

Mixed-method designs are increasingly used in sexually transmitted infection (STI) and HIV prevention research. The authors designed a mixedmethod approach and applied it to estimate and evaluate a predictor of continued female condom use (6+ uses, among those who used it at least once) in a 6-month prospective cohort study. The analysis included 402 women who received an intervention promoting use of female and male condoms for STI prevention and completed monthly quantitative surveys; 33 also completed a semistructured qualitative interview. The authors identified a qualitative theme (couples' female condom enjoyment [CFCE]), applied discriminant analysis techniques to estimate CFCE for all participants, and added CFCE to a multivariable logistic regression model of continued female condom use. CFCE related to comfort, naturalness, pleasure, feeling protected, playfulness, ease of use, intimacy, and feeling in control of protection. CFCE was associated with continued female condom use (adjusted odds ratio: 2.8, 95% confidence interval: 1.4-5.6) and significantly improved model fit (p < .001). CFCE predicted continued female condom use. Mixed-method approaches for "scaling up" qualitative findings from small samples to larger numbers of participants can benefit HIV and STI prevention research.

Developing a cross-docking network design model under uncertain environment

NASA Astrophysics Data System (ADS)

Seyedhoseini, S. M.; Rashid, Reza; Teimoury, E.

2015-06-01

Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time. Paying attention to these concerns, and importance of the congestion in cross docks, we present a mixed-integer model to optimize the location and design of cross docks at the same time to minimize the total transportation and operating costs. The model combines queuing theory for design aspects, for that matter, we consider a network of cross docks and customers where two M/M/c queues have been represented to describe operations of indoor trucks and outdoor trucks in each cross dock. To prepare a perfect illustration for performance of the model, a real case also has been examined that indicated effectiveness of the proposed model.

Developing a risk stratification tool for audit of outcome after surgery for head and neck squamous cell carcinoma.

PubMed

Tighe, David F; Thomas, Alan J; Sassoon, Isabel; Kinsman, Robin; McGurk, Mark

2017-07-01

Patients treated surgically for head and neck squamous cell carcinoma (HNSCC) represent a heterogeneous group. Adjusting for patient case mix and complexity of surgery is essential if reporting outcomes represent surgical performance and quality of care. A case note audit totaling 1075 patients receiving 1218 operations done for HNSCC in 4 cancer networks was completed. Logistic regression, decision tree analysis, an artificial neural network, and Naïve Bayes Classifier were used to adjust for patient case-mix using pertinent preoperative variables. Thirty-day complication rates varied widely (34%-51%; P < .015) between units. The predictive models allowed risk stratification. The artificial neural network demonstrated the best predictive performance (area under the curve [AUC] 0.85). Early postoperative complications are a measurable outcome that can be used to benchmark surgical performance and quality of care. Surgical outcome reporting in national clinical audits should be taking account of the patient case mix. © 2017 Wiley Periodicals, Inc.

U.S. Citizen Children of Undocumented Parents: The Link Between State Immigration Policy and the Health of Latino Children.

PubMed

Vargas, Edward D; Ybarra, Vickie D

2017-08-01

We examine Latino citizen children in mixed-status families and how their physical health status compares to their U.S. citizen, co-ethnic counterparts. We also examine Latino parents' perceptions of state immigration policy and its implications for child health status. Using the 2015 Latino National Health and Immigration Survey (n = 1493), we estimate a series of multivariate ordered logistic regression models with mixed-status family and perceptions of state immigration policy as primary predictors. We find that mixed-status families report worse physical health for their children as compared to their U.S. citizen co-ethnics. We also find that parental perceptions of their states' immigration status further exacerbate health disparities between families. These findings have implications for scholars and policy makers interested in immigrant health, family wellbeing, and health disparities in complex family structures. They contribute to the scholarship on Latino child health and on the erosion of the Latino immigrant health advantage.

U.S. Citizen Children of Undocumented Parents: The Link Between State Immigration Policy and the Health of Latino Children

PubMed Central

Vargas, Edward D.; Ybarra, Vickie D.

2016-01-01

Background We examine Latino citizen children in mixed-status families and how their physical health status compares to their U.S. citizen, co-ethnic counterparts. We also examine Latino parents’ perceptions of state immigration policy and its implications for child health status. Methods Using the 2015 Latino National Health and Immigration Survey (n=1493), we estimate a series of multivariate ordered logistic regression models with mixed-status family and perceptions of state immigration policy as primary predictors. Results We find that mixed-status families report worse physical health for their children as compared to their U.S. citizen co-ethnics. We also find that parental perceptions of their states’ immigration status further exacerbate health disparities between families. Discussion These findings have implications for scholars and policy makers interested in immigrant health, family wellbeing, and health disparities in complex family structures. They contribute to the scholarship on Latino child health and on the erosion of the Latino immigrant health advantage. PMID:27435476

The "Nursing Home Compare" measure of urinary/fecal incontinence: cross-sectional variation, stability over time, and the impact of case mix.

PubMed

Li, Yue; Schnelle, John; Spector, William D; Glance, Laurent G; Mukamel, Dana B

2010-02-01

To assess the impact of facility case mix on cross-sectional variations and short-term stability of the "Nursing Home Compare" incontinence quality measure (QM) and to determine whether multivariate risk adjustment can minimize such impacts. Retrospective analyses of the 2005 national minimum data set (MDS) that included approximately 600,000 long-term care residents in over 10,000 facilities in each quarterly sample. Mixed logistic regression was used to construct the risk-adjusted QM (nonshrinkage estimator). Facility-level ordinary least-squares models and adjusted R(2) were used to estimate the impact of case mix on cross-sectional and short-term longitudinal variations of currently published and risk-adjusted QMs. At least 50 percent of the cross-sectional variation and 25 percent of the short-term longitudinal variation of the published QM are explained by facility case mix. In contrast, the cross-sectional and short-term longitudinal variations of the risk-adjusted QM are much less susceptible to case-mix variations (adjusted R(2)<0.10), even for facilities with more extreme or more unstable outcome. Current "Nursing Home Compare" incontinence QM reflects considerable case-mix variations across facilities and over time, and therefore it may be biased. This issue can be largely addressed by multivariate risk adjustment using risk factors available in the MDS.

Differentiating Tumor Progression from Pseudoprogression in Patients with Glioblastomas Using Diffusion Tensor Imaging and Dynamic Susceptibility Contrast MRI.

PubMed

Wang, S; Martinez-Lage, M; Sakai, Y; Chawla, S; Kim, S G; Alonso-Basanta, M; Lustig, R A; Brem, S; Mohan, S; Wolf, R L; Desai, A; Poptani, H

2016-01-01

Early assessment of treatment response is critical in patients with glioblastomas. A combination of DTI and DSC perfusion imaging parameters was evaluated to distinguish glioblastomas with true progression from mixed response and pseudoprogression. Forty-one patients with glioblastomas exhibiting enhancing lesions within 6 months after completion of chemoradiation therapy were retrospectively studied. All patients underwent surgery after MR imaging and were histologically classified as having true progression (>75% tumor), mixed response (25%-75% tumor), or pseudoprogression (<25% tumor). Mean diffusivity, fractional anisotropy, linear anisotropy coefficient, planar anisotropy coefficient, spheric anisotropy coefficient, and maximum relative cerebral blood volume values were measured from the enhancing tissue. A multivariate logistic regression analysis was used to determine the best model for classification of true progression from mixed response or pseudoprogression. Significantly elevated maximum relative cerebral blood volume, fractional anisotropy, linear anisotropy coefficient, and planar anisotropy coefficient and decreased spheric anisotropy coefficient were observed in true progression compared with pseudoprogression (P < .05). There were also significant differences in maximum relative cerebral blood volume, fractional anisotropy, planar anisotropy coefficient, and spheric anisotropy coefficient measurements between mixed response and true progression groups. The best model to distinguish true progression from non-true progression (pseudoprogression and mixed) consisted of fractional anisotropy, linear anisotropy coefficient, and maximum relative cerebral blood volume, resulting in an area under the curve of 0.905. This model also differentiated true progression from mixed response with an area under the curve of 0.901. A combination of fractional anisotropy and maximum relative cerebral blood volume differentiated pseudoprogression from nonpseudoprogression (true progression and mixed) with an area under the curve of 0.807. DTI and DSC perfusion imaging can improve accuracy in assessing treatment response and may aid in individualized treatment of patients with glioblastomas. © 2016 by American Journal of Neuroradiology.

A hybrid inventory management system respondingto regular demand and surge demand

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

Mohammad S. Roni; Mingzhou Jin; Sandra D. Eksioglu

2014-06-01

This paper proposes a hybrid policy for a stochastic inventory system facing regular demand and surge demand. The combination of two different demand patterns can be observed in many areas, such as healthcare inventory and humanitarian supply chain management. The surge demand has a lower arrival rate but higher demand volume per arrival. The solution approach proposed in this paper incorporates the level crossing method and mixed integer programming technique to optimize the hybrid inventory policy with both regular orders and emergency orders. The level crossing method is applied to obtain the equilibrium distributions of inventory levels under a givenmore » policy. The model is further transformed into a mixed integer program to identify an optimal hybrid policy. A sensitivity analysis is conducted to investigate the impact of parameters on the optimal inventory policy and minimum cost. Numerical results clearly show the benefit of using the proposed hybrid inventory model. The model and solution approach could help healthcare providers or humanitarian logistics providers in managing their emergency supplies in responding to surge demands.« less

Effective algorithm for solving complex problems of production control and of material flows control of industrial enterprise

NASA Astrophysics Data System (ADS)

Mezentsev, Yu A.; Baranova, N. V.

2018-05-01

A universal economical and mathematical model designed for determination of optimal strategies for managing subsystems (components of subsystems) of production and logistics of enterprises is considered. Declared universality allows taking into account on the system level both production components, including limitations on the ways of converting raw materials and components into sold goods, as well as resource and logical restrictions on input and output material flows. The presented model and generated control problems are developed within the framework of the unified approach that allows one to implement logical conditions of any complexity and to define corresponding formal optimization tasks. Conceptual meaning of used criteria and limitations are explained. The belonging of the generated tasks of the mixed programming with the class of NP is shown. An approximate polynomial algorithm for solving the posed optimization tasks for mixed programming of real dimension with high computational complexity is proposed. Results of testing the algorithm on the tasks in a wide range of dimensions are presented.

Risk adjustment models for short-term outcomes after surgical resection for oesophagogastric cancer.

PubMed

Fischer, C; Lingsma, H; Hardwick, R; Cromwell, D A; Steyerberg, E; Groene, O

2016-01-01

Outcomes for oesophagogastric cancer surgery are compared with the aim of benchmarking quality of care. Adjusting for patient characteristics is crucial to avoid biased comparisons between providers. The study objective was to develop a case-mix adjustment model for comparing 30- and 90-day mortality and anastomotic leakage rates after oesophagogastric cancer resections. The study reviewed existing models, considered expert opinion and examined audit data in order to select predictors that were consequently used to develop a case-mix adjustment model for the National Oesophago-Gastric Cancer Audit, covering England and Wales. Models were developed on patients undergoing surgical resection between April 2011 and March 2013 using logistic regression. Model calibration and discrimination was quantified using a bootstrap procedure. Most existing risk models for oesophagogastric resections were methodologically weak, outdated or based on detailed laboratory data that are not generally available. In 4882 patients with oesophagogastric cancer used for model development, 30- and 90-day mortality rates were 2·3 and 4·4 per cent respectively, and 6·2 per cent of patients developed an anastomotic leak. The internally validated models, based on predictors selected from the literature, showed moderate discrimination (area under the receiver operating characteristic (ROC) curve 0·646 for 30-day mortality, 0·664 for 90-day mortality and 0·587 for anastomotic leakage) and good calibration. Based on available data, three case-mix adjustment models for postoperative outcomes in patients undergoing curative surgery for oesophagogastric cancer were developed. These models should be used for risk adjustment when assessing hospital performance in the National Health Service, and tested in other large health systems. © 2015 BJS Society Ltd Published by John Wiley & Sons Ltd.

Modelling with Integer Variables.

DTIC Science & Technology

1984-01-01

Computational Comparison of * ’Equivalent’ Mixed Integer Formulations," Naval Research Logistics Quarterly 28 (1981), pp. 115- 131 . 39. R. R, Meyer and...jE(i) 3 K ".- .e I " Z A . .,.. x jCI (i) IJ ~s ;:. ... i=I 1 1X. integer A- k . . . . . . . . . . . ... . ... . . . . . . . . . o...be such that Z X.. = 1 andIfxCi’e k jcI (i) 11 13 kx m). *x + E okv . Then by putting Xil and X.=O for j* i, j£I(i) kE (2.3.4) holds. Hence S’ Pi" As

Association between percutaneous hemodynamic support device and survival from cardiac arrest in the state of Michigan.

PubMed

Pressman, Andrew; Sawyer, Kelly N; Devlin, William; Swor, Robert

2018-05-01

The role of circulatory support in the post-cardiac arrest period remains controversial. Our objective was to investigate the association between treatment with a percutaneous hemodynamic support device and outcome after admission for cardiac arrest. We performed a retrospective study of adult patients with admission diagnosis of cardiac arrest or ventricular fibrillation (VF) from the Michigan Inpatient Database, treated between July 1, 2010, and June 30, 2013. Patient demographics, clinical characteristics, treatments, and disposition were electronically abstracted based on ICD-9 codes at the hospital level. Mixed-effects logistic regression models were fit to test the effect of percutaneous hemodynamic support device defined as either percutaneous left ventricular assist device (pLVAD) or intra-aortic balloon pump (IABP) on survival. These models controlled for age, sex, VF, myocardial infarction (MI), and cardiogenic shock with hospital modeled as a random effect. A total of 103 hospitals contributed 4393 patients for analysis, predominately male (58.8%) with a mean age of 64.1years (SD 15.5). On univariate analysis, younger age, male sex, VF as the initial rhythm, acute MI, percutaneous coronary intervention, percutaneous hemodynamic support device, and absence of cardiogenic shock were associated with survival to discharge (each p<0.001). Mixed-effects logistic regressions revealed use of percutaneous hemodynamic support device was significantly associated with survival among all patients (OR 1.8 (1.28-2.54)), and especially in those with acute MI (OR 1.95 (1.31-2.93)) or cardiogenic shock (OR 1.96 (1.29-2.98)). Treatment with percutaneous hemodynamic support device in the post-arrest period may provide left ventricular support and improve outcome. Copyright © 2017 Elsevier Inc. All rights reserved.

Campaign Strategies and Voter Approval of School Referenda: A Mixed Methods Analysis

ERIC Educational Resources Information Center

Johnson, Paul A.; Ingle, William Kyle

2009-01-01

Drawing from state administrative data and surveys of superintendents in Ohio, this mixed methods study examined factors associated with voters' approval of local school levies. Utilizing binomial logistic regression, this study found that new levies and poverty rates were significantly associated with a decrease in the likelihood of passage.…

METHAMPHETAMINE USE AMONG RURAL WHITE AND NATIVE AMERICAN ADOLESCENTS: AN APPLICATION OF THE STRESS PROCESS MODEL

PubMed Central

Eitle, David J.; McNulty Eitle, Tamela

2016-01-01

Methamphetamine use has been identified as having significant adverse health consequences, yet we know little about the correlates of its use. Additionally, research has found that Native Americans are at the highest risk for methamphetamine use. Our exploratory study, informed by the stress process model, examines stress and stress buffering factors associated with methamphetamine use among a cross-sectional sample of rural white and Native American adolescents (n=573). Results of logistic regression analyses revealed mixed support for the stress process model; while stress exposure and family methamphetamine use predicted past year methamphetamine use, the inclusion of these variables failed to attenuate the association between race and past year use. PMID:25445505

Modelling individual tree height to crown base of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.)

PubMed Central

Jansa, Václav

2017-01-01

Height to crown base (HCB) of a tree is an important variable often included as a predictor in various forest models that serve as the fundamental tools for decision-making in forestry. We developed spatially explicit and spatially inexplicit mixed-effects HCB models using measurements from a total 19,404 trees of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica L.) on the permanent sample plots that are located across the Czech Republic. Variables describing site quality, stand density or competition, and species mixing effects were included into the HCB model with use of dominant height (HDOM), basal area of trees larger in diameters than a subject tree (BAL- spatially inexplicit measure) or Hegyi’s competition index (HCI—spatially explicit measure), and basal area proportion of a species of interest (BAPOR), respectively. The parameters describing sample plot-level random effects were included into the HCB model by applying the mixed-effects modelling approach. Among several functional forms evaluated, the logistic function was found most suited to our data. The HCB model for Norway spruce was tested against the data originated from different inventory designs, but model for European beech was tested using partitioned dataset (a part of the main dataset). The variance heteroscedasticity in the residuals was substantially reduced through inclusion of a power variance function into the HCB model. The results showed that spatially explicit model described significantly a larger part of the HCB variations [R2adj = 0.86 (spruce), 0.85 (beech)] than its spatially inexplicit counterpart [R2adj = 0.84 (spruce), 0.83 (beech)]. The HCB increased with increasing competitive interactions described by tree-centered competition measure: BAL or HCI, and species mixing effects described by BAPOR. A test of the mixed-effects HCB model with the random effects estimated using at least four trees per sample plot in the validation data confirmed that the model was precise enough for the prediction of HCB for a range of site quality, tree size, stand density, and stand structure. We therefore recommend measuring of HCB on four randomly selected trees of a species of interest on each sample plot for localizing the mixed-effects model and predicting HCB of the remaining trees on the plot. Growth simulations can be made from the data that lack the values for either crown ratio or HCB using the HCB models. PMID:29049391

Contractor Logistics Support in the U.S. Air Force

DTIC Science & Technology

2009-01-01

limits), or it can engage in a mix of the two approaches.2 This monograph addresses CLS, which is defined as contractor sustainment of a weapon system...organic facilities; it can pay contractors to do the work (subject to some congressional limits); or it can apply a mix of the two approaches.2 Organic...levels are largely stable and represent a mix of services, including contractor operated facilities and instal- Figure 3.1 Air Force CSS for Weapon

A brief dataset on the model-based evaluation of the growth performance of Bacillus coagulans and l-lactic acid production in a lignin-supplemented medium.

PubMed

Glaser, Robert; Venus, Joachim

2017-04-01

The data presented in this article are related to the research article entitled "Model-based characterization of growth performance and l-lactic acid production with high optical purity by thermophilic Bacillus coagulans in a lignin-supplemented mixed substrate medium (R. Glaser and J. Venus, 2016) [1]". This data survey provides the information on characterization of three Bacillus coagulans strains. Information on cofermentation of lignocellulose-related sugars in lignin-containing media is given. Basic characterization data are supported by optical-density high-throughput screening and parameter adjustment to logistic growth models. Lab scale fermentation procedures are examined by model adjustment of a Monod kinetics-based growth model. Lignin consumption is analyzed using the data on decolorization of a lignin-supplemented minimal medium.

The role of gender in a smoking cessation intervention: a cluster randomized clinical trial

PubMed Central

2011-01-01

Background The prevalence of smoking in Spain is high in both men and women. The aim of our study was to evaluate the role of gender in the effectiveness of a specific smoking cessation intervention conducted in Spain. Methods This study was a secondary analysis of a cluster randomized clinical trial in which the randomization unit was the Basic Care Unit (family physician and nurse who care for the same group of patients). The intervention consisted of a six-month period of implementing the recommendations of a Clinical Practice Guideline. A total of 2,937 current smokers at 82 Primary Care Centers in 13 different regions of Spain were included (2003-2005). The success rate was measured by a six-month continued abstinence rate at the one-year follow-up. A logistic mixed-effects regression model, taking Basic Care Units as random-effect parameter, was performed in order to analyze gender as a predictor of smoking cessation. Results At the one-year follow-up, the six-month continuous abstinence quit rate was 9.4% in men and 8.5% in women (p = 0.400). The logistic mixed-effects regression model showed that women did not have a higher odds of being an ex-smoker than men after the analysis was adjusted for confounders (OR adjusted = 0.9, 95% CI = 0.7-1.2). Conclusions Gender does not appear to be a predictor of smoking cessation at the one-year follow-up in individuals presenting at Primary Care Centers. ClinicalTrials.gov Identifier NCT00125905. PMID:21605389

Paying for Primary Care: The Factors Associated with Physician Self-selection into Payment Models.

PubMed

Rudoler, David; Deber, Raisa; Barnsley, Janet; Glazier, Richard H; Dass, Adrian Rohit; Laporte, Audrey

2015-09-01

To determine the factors associated with primary care physician self-selection into different payment models, we used a panel of eight waves of administrative data for all primary care physicians who practiced in Ontario between 2003/2004 and 2010/2011. We used a mixed effects logistic regression model to estimate physicians' choice of three alternative payment models: fee for service, enhanced fee for service, and blended capitation. We found that primary care physicians self-selected into payment models based on existing practice characteristics. Physicians with more complex patient populations were less likely to switch into capitation-based payment models where higher levels of effort were not financially rewarded. These findings suggested that investigations aimed at assessing the impact of different primary care reimbursement models on outcomes, including costs and access, should first account for potential selection effects. Copyright © 2015 John Wiley & Sons, Ltd.

Department of the Navy Justification of Estimates for Fiscal Year 1986 Submitted to Congress February 1985, Operation and Maintenance, Navy. Book 2

DTIC Science & Technology

1985-02-01

Range Missile Combatants (CGpCON, DDGFFG) 78 85 95 Mobile Logistics Force (AOE ,AE ,AOR,AO) 27 27 27 . ., Unit costs increase due to the mix of components...low- mix maintenance concept (less on-board maintenance) used on this class ship necessitates rework of these antennas % every four years. FY 1984 FY...4. Other 838 40 1,147 55 563 55 (Component mix changes each year) 7091 77--.-- --- o

Employment Status and Income Generation among Homeless Young Adults: Results from a Five-City, Mixed-Methods Study

ERIC Educational Resources Information Center

Ferguson, Kristin M.; Bender, Kimberly; Thompson, Sanna J.; Maccio, Elaine M.; Pollio, David

2012-01-01

This mixed-methods study identified correlates of unemployment among homeless young adults in five cities. Two hundred thirty-eight homeless young people from Los Angeles (n = 50), Austin (n = 50), Denver (n = 50), New Orleans (n = 50), and St. Louis (n = 38) were recruited using comparable sampling strategies. Multivariate logistic regression…

Neighbourhood walkability, leisure-time and transport-related physical activity in a mixed urban-rural area.

PubMed

de Sa, Eric; Ardern, Chris I

2014-01-01

Objectives. To develop a walkability index specific to mixed rural/suburban areas, and to explore the relationship between walkability scores and leisure time physical activity. Methods. Respondents were geocoded with 500 m and 1,000 m buffer zones around each address. A walkability index was derived from intersections, residential density, and land-use mix according to built environment measures. Multivariable logistic regression models were used to quantify the association between the index and physical activity levels. Analyses used cross-sectional data from the 2007-2008 Canadian Community Health Survey (n = 1158; ≥18 y). Results. Respondents living in highly walkable 500 m buffer zones (upper quartiles of the walkability index) were more likely to walk or cycle for leisure than those living in low-walkable buffer zones (quartile 1). When a 1,000 m buffer zone was applied, respondents in more walkable neighbourhoods were more likely to walk or cycle for both leisure-time and transport-related purposes. Conclusion. Developing a walkability index can assist in exploring the associations between measures of the built environment and physical activity to prioritize neighborhood change.

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

PubMed Central

2012-01-01

Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531

Assessing models of arsenic occurrence in drinking water from bedrock aquifers in New Hampshire

USGS Publications Warehouse

Andy, Caroline; Fahnestock, Maria Florencia; Lombard, Melissa; Hayes, Laura; Bryce, Julie; Ayotte, Joseph

2017-01-01

Three existing multivariate logistic regression models were assessed using new data to evaluate the capacity of the models to correctly predict the probability of groundwater arsenic concentrations exceeding the threshold values of 1, 5, and 10 micrograms per liter (µg/L) in New Hampshire, USA. A recently released testing dataset includes arsenic concentrations from groundwater samples collected in 2004–2005 from a mix of 367 public-supply and private domestic wells. The use of this dataset to test three existing logistic regression models demonstrated enhanced overall predictive accuracy for the 5 and 10 μg/L models. Overall accuracies of 54.8, 76.3, and 86.4 percent were reported for the 1, 5, and 10 μg/L models, respectively. The state was divided by counties into northwest and southeast regions. Regional differences in accuracy were identified; models had an average accuracy of 83.1 percent for the counties in the northwest and 63.7 percent in the southeast. This is most likely due to high model specificity in the northwest and regional differences in arsenic occurrence. Though these models have limitations, they allow for arsenic hazard assessment across the region. The introduction of well-type (public or private), well depth, and casing length as explanatory variables may be appropriate measures to improve model performance. Our findings indicate that the original models generalize to the testing dataset, and should continue to serve as an important vehicle of preventative public health that may be applied to other groundwater contaminants in New Hampshire.

Is recurrence in major depressive disorder related to bipolarity and mixed features? Results from the BRIDGE-II-Mix study.

PubMed

Mazzarini, Lorenzo; Kotzalidis, Georgios D; Piacentino, Daria; Rizzato, Salvatore; Angst, Jules; Azorin, Jean-Michel; Bowden, Charles L; Mosolov, Sergey; Young, Allan H; Vieta, Eduard; Girardi, Paolo; Perugi, Giulio

2018-03-15

Current classifications separate Bipolar (BD) from Major Depressive Disorder (MDD) based on polarity rather than recurrence. We aimed to determine bipolar/mixed feature frequency in a large MDD multinational sample with (High-Rec) and without (Low-Rec) >3 recurrences, comparing the two subsamples. We measured frequency of bipolarity/hypomanic features during current depressive episodes (MDEs) in 2347 MDD patients from the BRIDGE-II-mix database, comparing High-Rec with Low-Rec. We used Bonferroni-corrected Student's t-test for continuous, and chi-squared test, for categorical variables. Logistic regression estimated the size of the association between clinical characteristics and High-Rec MDD. Compared to Low-Rec (n = 1084, 46.2%), High-Rec patients (n = 1263, 53.8%) were older, with earlier depressive onset, had more family history of BD, more atypical features, suicide attempts, hospitalisations, and treatment resistance and (hypo)manic switches when treated with antidepressants, higher comorbidity with borderline personality disorder, and more hypomanic symptoms during current MDE, resulting in higher rates of mixed depression according to both DSM-5 and research-based diagnostic (RBDC) criteria. Logistic regression showed age at first symptoms < 30 years, current MDE duration ≤ 1 month, hypomania/mania among first-degree relatives, past suicide attempts, treatment-resistance, antidepressant-induced swings, and atypical, mixed, or psychotic features during MDE to associate with High-Rec. Number of MDEs for defining recurrence was arbitrary; cross-sectionality did not allow assessment of conversion from MDD to BD. High-Rec MDD differed from Low-Rec group for several clinical/epidemiological variables, including bipolar/mixed features. Bipolarity specifier and RBDC were more sensitive than DSM-5 criteria in detecting bipolar and mixed features in MDD. Copyright © 2017. Published by Elsevier B.V.

Neighborhood characteristics and sexual intimate partner violence against women among low-income, drug-involved New York City residents: results from the IMPACT Studies.

PubMed

Frye, Victoria; Blaney, Shannon; Cerdá, Magdalena; Vlahov, David; Galea, Sandro; Ompad, Danielle C

2014-07-01

We assessed relations among neighborhood characteristics and sexual intimate partner violence against women (SIPVAW), among low-income, drug-involved, women (n = 360) and men (n = 670) in New York City between 2005 and 2009. Six percent of women (n = 22) and 5% of men (n = 33) reported experiencing and perpetrating SIPVAW in the past year with a main partner. In adjusted mixed models among women, neighborhood ethnic heterogeneity was significantly negatively associated with SIPVAW victimization. In adjusted logistic models among men, neighborhood collective efficacy was significantly positively associated with SIPVAW perpetration. Novel theoretical frameworks are needed to guide research on neighborhoods and partner violence. © The Author(s) 2014.

Interdisciplinary mixed methods research with structurally vulnerable populations: case studies of injection drug users in San Francisco.

PubMed

Lopez, Andrea M; Bourgois, Philippe; Wenger, Lynn D; Lorvick, Jennifer; Martinez, Alexis N; Kral, Alex H

2013-03-01

Research with injection drug users (IDUs) benefits from interdisciplinary theoretical and methodological innovation because drug use is illegal, socially sanctioned and often hidden. Despite the increasing visibility of interdisciplinary, mixed methods research projects with IDUs, qualitative components are often subordinated to quantitative approaches and page restrictions in top addiction journals limit detailed reports of complex data collection and analysis logistics, thus minimizing the fuller scientific potential of genuine mixed methods. We present the methodological logistics and conceptual approaches of four mixed-methods research projects that our interdisciplinary team conducted in San Francisco with IDUs over the past two decades. These projects include combinations of participant-observation ethnography, in-depth qualitative interviewing, epidemiological surveys, photo-documentation, and geographic mapping. We adapted Greene et al.'s framework for combining methods in a single research project through: data triangulation, methodological complementarity, methodological initiation, and methodological expansion. We argue that: (1) flexible and self-reflexive methodological procedures allowed us to seize strategic opportunities to document unexpected and sometimes contradictory findings as they emerged to generate new research questions, (2) iteratively mixing methods increased the scope, reliability, and generalizability of our data, and (3) interdisciplinary collaboration contributed to a scientific "value added" that allowed for more robust theoretical and practical findings about drug use and risk-taking. Copyright © 2013 Elsevier B.V. All rights reserved.

Interdisciplinary Mixed Methods Research with Structurally Vulnerable Populations: Case Studies of Injection Drug Users in San Francisco

PubMed Central

Lopez, Andrea; Bourgois, Philippe; Wenger, Lynn; Lorvick, Jennifer; Martinez, Alexis; Kral, Alex H.

2013-01-01

Research with injection drug users (IDUs) benefits from interdisciplinary theoretical and methodological innovation because drug use is illegal, socially sanctioned and often hidden. Despite the increasing visibility of interdisciplinary, mixed methods research projects with IDUs, qualitative components are often subordinated to quantitative approaches and page restrictions in top addiction journals limit detailed reports of complex data collection and analysis logistics, thus minimizing the fuller scientific potential of genuine mixed methods. We present the methodological logistics and conceptual approaches of four mixed-methods research projects that our interdisciplinary team conducted in San Francisco with IDUs over the past two decades. These projects include combinations of participant-observation ethnography, in-depth qualitative interviewing, epidemiological surveys, photo-documentation, and geographic mapping. We adapted Greene et al.’s framework for combining methods in a single research project through: data triangulation, methodological complementarity, methodological initiation, and methodological expansion. We argue that: (1) flexible and self-reflexive methodological procedures allowed us to seize strategic opportunities to document unexpected and sometimes contradictory findings as they emerged to generate new research questions, (2) iteratively mixing methods increased the scope, reliability, and generalizability of our data, and (3) interdisciplinary collaboration contributed to a scientific “value added” that allowed for more robust theoretical and practical findings about drug use and risk-taking. PMID:23312109

Mobile phone use during driving: Effects on speed and effectiveness of driver compensatory behaviour.

PubMed

Choudhary, Pushpa; Velaga, Nagendra R

2017-09-01

This study analysed and modelled the effects of conversation and texting (each with two difficulty levels) on driving performance of Indian drivers in terms of their mean speed and accident avoiding abilities; and further explored the relationship between speed reduction strategy of the drivers and their corresponding accident frequency. 100 drivers of three different age groups (young, mid-age and old-age) participated in the simulator study. Two sudden events of Indian context: unexpected crossing of pedestrians and joining of parked vehicles from road side, were simulated for estimating the accident probabilities. Generalized linear mixed models approach was used for developing linear regression models for mean speed and binary logistic regression models for accident probability. The results of the models showed that the drivers significantly compensated the increased workload by reducing their mean speed by 2.62m/s and 5.29m/s in the presence of conversation and texting tasks respectively. The logistic models for accident probabilities showed that the accident probabilities increased by 3 and 4 times respectively when the drivers were conversing or texting on a phone during driving. Further, the relationship between the speed reduction patterns and their corresponding accident frequencies showed that all the drivers compensated differently; but, among all the drivers, only few drivers, who compensated by reducing the speed by 30% or more, were able to fully offset the increased accident risk associated with the phone use. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mixed features in patients with a major depressive episode: the BRIDGE-II-MIX study.

PubMed

Perugi, Giulio; Angst, Jules; Azorin, Jean-Michel; Bowden, Charles L; Mosolov, Sergey; Reis, Joao; Vieta, Eduard; Young, Allan H

2015-03-01

To estimate the frequency of mixed states in patients diagnosed with major depressive episode (MDE) according to conceptually different definitions and to compare their clinical validity. This multicenter, multinational cross-sectional Bipolar Disorders: Improving Diagnosis, Guidance and Education (BRIDGE)-II-MIX study enrolled 2,811 adult patients experiencing an MDE. Data were collected per protocol on sociodemographic variables, current and past psychiatric symptoms, and clinical variables that are risk factors for bipolar disorder. The frequency of mixed features was determined by applying both DSM-5 criteria and a priori described Research-Based Diagnostic Criteria (RBDC). Clinical variables associated with mixed features were assessed using logistic regression. Overall, 212 patients (7.5%) fulfilled DSM-5 criteria for MDE with mixed features (DSM-5-MXS), and 818 patients (29.1%) fulfilled diagnostic criteria for a predefined RBDC depressive mixed state (RBDC-MXS). The most frequent manic/hypomanic symptoms were irritable mood (32.6%), emotional/mood lability (29.8%), distractibility (24.4%), psychomotor agitation (16.1%), impulsivity (14.5%), aggression (14.2%), racing thoughts (11.8%), and pressure to keep talking (11.4%). Euphoria (4.6%), grandiosity (3.7%), and hypersexuality (2.6%) were less represented. In multivariate logistic regression analysis, RBDC-MXS was associated with the largest number of variables including diagnosis of bipolar disorder, family history of mania, lifetime suicide attempts, duration of the current episode > 1 month, atypical features, early onset, history of antidepressant-induced mania/hypomania, and lifetime comorbidity with anxiety, alcohol and substance use disorders, attention-deficit/hyperactivity disorder, and borderline personality disorder. Depressive mixed state, defined as the presence of 3 or more manic/hypomanic features, was present in around one-third of patients experiencing an MDE. The valid symptom, illness course and family history RBDC criteria we assessed identified 4 times more MDE patients as having mixed features and yielded statistically more robust associations with several illness characteristics of bipolar disorder than did DSM-5 criteria. © Copyright 2015 Physicians Postgraduate Press, Inc.

Does the presence and mix of destinations influence walking and physical activity?

PubMed

King, Tania Louise; Bentley, Rebecca Jodie; Thornton, Lukar Ezra; Kavanagh, Anne Marie

2015-09-17

Local destinations have previously been shown to be associated with higher levels of both physical activity and walking, but little is known about how specific destinations are related to activity. This study examined associations between types and mix of destinations and both walking frequency and physical activity. The sample consisted of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Using geographic information systems, seven types of destinations were examined within three network buffers (400 meters (m), 800 m and 1200 m) of respondents' homes. Multilevel logistic regression was used to estimate effects of each destination type separately, as well as destination mix (variety) on: 1) likelihood of walking for at least 10 min ≥ 4/week; 2) likelihood of being sufficiently physically active. All models were adjusted for potential confounders. All destination types were positively associated with walking frequency, and physical activity sufficiency at 1200 m. For the 800 m buffer: all destinations except transport stops and sports facilities were significantly associated with physical activity, while all except sports facilities were associated with walking frequency; at 400 m, café/takeaway food stores and transport stops were associated with walking frequency and physical activity sufficiency, and sports facilities were also associated with walking frequency. Strongest associations for both outcomes were observed for community resources and small food stores at both 800 m and 1200 m. For all buffer distances: greater mix was associated with greater walking frequency. Inclusion of walking in physical activity models led to attenuation of associations. The results of this analysis indicate that there is an association between destinations and both walking frequency and physical activity sufficiency, and that this relationship varies by destination type. It is also clear that greater mix of destinations positively predicts walking frequency and physical activity sufficiency.

Mixed reality framework for collective motion patterns of swarms with delay coupling

NASA Astrophysics Data System (ADS)

Szwaykowska, Klementyna; Schwartz, Ira

The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is an important subject for many applications within the field of distributed robotic systems. However, there are significant logistical challenges associated with testing fully distributed systems in real-world settings. In this paper, we provide a rigorous theoretical justification for the use of mixed-reality experiments as a stepping stone to fully physical testing of distributed robotic systems. We also model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. Our analyses, assuming agents communicating over an Erdos-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm. K. S. was a National Research Council postdoctoral fellow. I.B.S was supported by the U.S. Naval Research Laboratory funding (N0001414WX00023) and office of Naval Research (N0001414WX20610).

Logistical Support for the Heavy-Light Mix,

DTIC Science & Technology

1988-01-20

determination to learn from history. While the physical ability to support this force is marginal, the logistical procedures, concepts of support, and a...others. £ They emphasized arni-or and mechanized in 4 antry which could keep pace with the tanks. 2 -- t. - - - - *i . h -I. -o, ., . i. . -. rJIPT...Army received a costly review of the combined arms lessons learned during WW II. In June. 1950, the North Korean Army launched an all-out attack into

Modelling the growth kinetics of Kocuria marina DAGII as a function of single and binary substrate during batch production of β-Cryptoxanthin.

PubMed

Mitra, Ruchira; Chaudhuri, Surabhi; Dutta, Debjani

2017-01-01

In the present investigation, growth kinetics of Kocuria marina DAGII during batch production of β-Cryptoxanthin (β-CRX) was studied by considering the effect of glucose and maltose as a single and binary substrate. The importance of mixed substrate over single substrate has been emphasised in the present study. Different mathematical models namely, the Logistic model for cell growth, the Logistic mass balance equation for substrate consumption and the Luedeking-Piret model for β-CRX production were successfully implemented. Model-based analyses for the single substrate experiments suggested that the concentrations of glucose and maltose higher than 7.5 and 10.0 g/L, respectively, inhibited the growth and β-CRX production by K. marina DAGII. The Han and Levenspiel model and the Luong product inhibition model accurately described the cell growth in glucose and maltose substrate systems with a R 2 value of 0.9989 and 0.9998, respectively. The effect of glucose and maltose as binary substrate was further investigated. The binary substrate kinetics was well described using the sum-kinetics with interaction parameters model. The results of production kinetics revealed that the presence of binary substrate in the cultivation medium increased the biomass and β-CRX yield significantly. This study is a first time detailed investigation on kinetic behaviours of K. marina DAGII during β-CRX production. The parameters obtained in the study might be helpful for developing strategies for commercial production of β-CRX by K. marina DAGII.

Effect of molecule-particle binding on the reduction in the mixed-frequency alternating current magnetic susceptibility of magnetic bio-reagents

NASA Astrophysics Data System (ADS)

Yang, C. C.; Yang, S. Y.; Chen, H. H.; Weng, W. L.; Horng, H. E.; Chieh, J. J.; Hong, C. Y.; Yang, H. C.

2012-07-01

By specifically bio-functionalizing magnetic nanoparticles, magnetic nanoparticles are able to label target bio-molecules. This property can be applied to quantitatively detect molecules invitro by measuring the related magnetic signals of nanoparticles bound with target molecules. One of the magnetic signals is the reduction in the mixed-frequency ac magnetic susceptibility of suspended magnetic nanoparticles due to the molecule-particle association. Many experimental results show empirically that the molecular-concentration dependent reduction in ac magnetic susceptibility follows the logistic function. In this study, it has been demonstrated that the logistic behavior is originated from the growth of particle sizes due to the molecule-particle association. The analytic relationship between the growth of particle sizes and the reduction in ac magnetic susceptibility is developed.

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.

Distribution, occupancy, and habitat correlates of American martens (Martes americana) in Rocky Mountain National Park, Colorado

USGS Publications Warehouse

Baldwin, R.A.; Bender, L.C.

2008-01-01

A clear understanding of habitat associations of martens (Martes americana) is necessary to effectively manage and monitor populations. However, this information was lacking for martens in most of their southern range, particularly during the summer season. We studied the distribution and habitat correlates of martens from 2004 to 2006 in Rocky Mountain National Park (RMNP) across 3 spatial scales: site-specific, home-range, and landscape. We used remote-sensored cameras from early August through late October to inventory occurrence of martens and modeled occurrence as a function of habitat and landscape variables using binary response (BR) and binomial count (BC) logistic regression, and occupancy modeling (OM). We also assessed which was the most appropriate modeling technique for martens in RMNP. Of the 3 modeling techniques, OM appeared to be most appropriate given the explanatory power of derived models and its incorporation of detection probabilities, although the results from BR and BC provided corroborating evidence of important habitat correlates. Location of sites in the western portion of the park, riparian mixed-conifer stands, and mixed-conifer with aspen patches were most frequently positively correlated with occurrence of martens, whereas more xeric and open sites were avoided. Additionally, OM yielded unbiased occupancy values ranging from 91% to 100% and 20% to 30% for the western and eastern portions of RMNP, respectively. ?? 2008 American Society of Mammalogists.

Modeling spring habitat requirements of the endangered brown eared pheasant Crossoptilon mantchuricum in the Huanglong Mountains, Shaanxi Province, China.

PubMed

Li, Hongqun; Yue, Bisong; Lian, Zhenmin; Zhao, Hongfeng; Zhao, Delong; Xiao, Xiangming

2012-09-01

A detailed understanding of the habitat needs of brown eared pheasants (Crossoptilon mantchuricum) is essential for conserving the species. We carried out field surveys in the Huanglong Mountains of Shaanxi Province, China, from March to June in 2007 and 2008. We arrayed a total of 206 grid plots (200 × 200 m) along transects in 2007 and 2008 and quantified a suite of environmental variables for each one. In the optimal logistic regression model, the most important variables for brown eared pheasants were slope degree, tree cover, distance to nearest water, cover and depth of fallen leaves. Hosmer and Leweshow goodness-of-fit tests explained that logistic models for the species were good fits. The model suggested that spring habitat selection of the brown eared pheasant was negatively related to distance to nearest water and slope degree, and positively to cover of trees and cover and depth of fallen leaves. In addition, the observed detected and undetected grids in 2007 did not show significant differences with predictions based on the model. These results showed that the model could well predict the habitat selection of brown eared pheasants. Based on these predictive models, we suggest that habitat management plans incorporating this new information can now focus more effectively on restrictions on the number of tourists entering the nature reserve, prohibition of firewood collection, livestock grazing, and medicinal plant harvesting by local residents in the core areas, protection of mixed forest and sources of the permanent water in the reserve, and use of alternatives to firewood.

Applying Kaplan-Meier to Item Response Data

ERIC Educational Resources Information Center

McNeish, Daniel

2018-01-01

Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…

Air Force Journal of Logistics: Logistics Dimensions Improving Bare Base Agile Combat Support, The Path to Integration. Volume 28, Number 2

DTIC Science & Technology

2004-01-01

the system is balanced, there is the right flow of new pilots to match the availability of instructors for initial training missions, the right mix of...which attempted to redesign and streamline the DoD global distribution system , significantly improved delivery time to test locations.4 During its...somewhat confusing priority system that does not guarantee cargo delivery at a specific time and a pricing system that does not adequately differentiate

Serum estradiol does not differentiate stress, mixed and urge incontinent women around menopause. A report from the Women's Health in the Lund Area (WHILA) study.

PubMed

Hamer, Maria Andrada; Källén, Karin; Lidfeldt, Jonas; Samsioe, Göran; Teleman, Pia

2011-11-01

To outline serum estradiol levels in perimenopausal women with stress, mixed or urge incontinence. We believe the majority of urgency symptoms in perimenopausal women to be caused by a pelvic floor dysfunction and a hypermobility of the bladder neck. If this is the case, there would be no difference in estradiol levels between the groups. University hospital. In the observational Women's Health in the Lund Area study, a subset of 400/2221 women reporting urinary incontinence completed a detailed questionnaire regarding lower urinary tract symptoms and had their serum steroid hormone levels measured. Statistical analyses were made by Chi-square test, nonparametrical tests, ANOVA, multi- and univariate logistic regression analysis. Stress incontinence was reported by 196, mixed incontinence by 153 and urge incontinence by 43 women; in 369, serumestradiol values were available. Serum estradiol did not differ significantly between stress incontinent (median 49.5 pmo/l, range 2.63-875.4), urge incontinent (median 31.6 pmol/l, range 2.63-460.7) or mixed incontinent women (median 35.5 pmol/l, range 2.63-787.9, p=0.62). Logistic regression analysis correcting for age, parity, hormonal status, smoking, hysterectomy and BMI also failed to show any difference in estradiol levels between the groups (p=0.41-0.58). No significant differences in serum estradiol levels between stress, mixed or urge incontinent perimenopausal women could be demonstrated. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

ERIC Educational Resources Information Center

Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas

2011-01-01

The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…

Livestock transport from the perspective of the pre-slaughter logistic chain: a review.

PubMed

Miranda-de la Lama, G C; Villarroel, M; María, G A

2014-09-01

New developments in livestock transport within the pre-slaughter chain are discussed in terms of three logistic nodes: origin, stopovers and slaughterhouse. Factors as transport cost, haulier, truck specifications, micro-environment conditions, loading density, route planning, vehicle accidents and journey length are discussed as well as causes of morbidity, mortality, live weight and carcass damage. Taking into account current trends towards increased transport times, logistics stopovers and mixed transport, there is a need to develop systems of evaluation and decision-making that provide tools and protocols that can minimize the biological cost to animals, which may have been underestimated in the past. Copyright © 2014 Elsevier Ltd. All rights reserved.

Design logistics performance measurement model of automotive component industry for srengthening competitiveness of dealing AEC 2015

NASA Astrophysics Data System (ADS)

Amran, T. G.; Janitra Yose, Mindy

2018-03-01

As the free trade Asean Economic Community (AEC) causes the tougher competition, it is important that Indonesia’s automotive industry have high competitiveness as well. A model of logistics performance measurement was designed as an evaluation tool for automotive component companies to improve their logistics performance in order to compete in AEC. The design of logistics performance measurement model was based on the Logistics Scorecard perspectives, divided into two stages: identifying the logistics business strategy to get the KPI and arranging the model. 23 KPI was obtained. The measurement result can be taken into consideration of determining policies to improve the performance logistics competitiveness.

Research on support effectiveness modeling and simulating of aviation materiel autonomic logistics system

NASA Astrophysics Data System (ADS)

Zhou, Yan; Zhou, Yang; Yuan, Kai; Jia, Zhiyu; Li, Shuo

2018-05-01

Aiming at the demonstration of autonomic logistics system to be used at the new generation of aviation materiel in our country, the modeling and simulating method of aviation materiel support effectiveness considering autonomic logistics are studied. Firstly, this paper introduced the idea of JSF autonomic logistics and analyzed the influence of autonomic logistics on support effectiveness from aspects of reliability, false alarm rate, troubleshooting time, and support delay time and maintenance level. On this basis, the paper studies the modeling and simulating methods of support effectiveness considering autonomic logistics, and puts forward the maintenance support simulation process considering autonomic logistics. Finally, taking the typical aviation materiel as an example, this paper analyzes and verifies the above-mentioned support effectiveness modeling and simulating method of aviation materiel considering autonomic logistics.

The Relative Effectiveness of Women-Only and Mixed-Gender Treatment for Substance-Abusing Women

PubMed Central

Prendergast, Michael L.; Messina, Nena P.; Hall, Elizabeth A.; Warda, Umme S.

2011-01-01

Following research indicating that the treatment needs of women are different from those of men, researchers and clinicians have argued that drug treatment programs for women should be designed to take their needs into account. Such programs tend to admit only women and incorporate philosophies and activities that are based on a social, peer-based model that is responsive to their needs. To assess the relative effectiveness of women-only (WO) outpatient programs compared to mixed-gender (MG) outpatient programs, 291 study volunteers were recruited (152 WO, 139 MG), and a 1-year follow-up was completed with 259 women (135 WO, 124 MG). Using bivariate, logistic regression, and generalized estimating equation analysis, the following four outcomes were examined: drug and alcohol use, criminal activity, arrests, and employment. In both groups, women showed improvement in the four outcome measures. Comparison of the groups on outcomes yielded mixed results; women who participated in WO treatment reported significantly less substance use and criminal activity than women in MG treatment, but there were no differences in arrest or employment status at follow up compared with those in MG treatment. PMID:21315540

Interhospital differences and case-mix in a nationwide prevalence survey.

PubMed

Kanerva, M; Ollgren, J; Lyytikäinen, O

2010-10-01

A prevalence survey is a time-saving and useful tool for obtaining an overview of healthcare-associated infection (HCAI) either in a single hospital or nationally. Direct comparison of prevalence rates is difficult. We evaluated the impact of case-mix adjustment on hospital-specific prevalences. All five tertiary care, all 15 secondary care and 10 (25% of 40) other acute care hospitals took part in the first national prevalence survey in Finland in 2005. US Centers for Disease Control and Prevention criteria served to define HCAI. The information collected included demographic characteristics, severity of the underlying disease, use of catheters and a respirator, and previous surgery. Patients with HCAI related to another hospital were excluded. Case-mix-adjusted HCAI prevalences were calculated by using a multivariate logistic regression model for HCAI risk and an indirect standardisation method. Altogether, 587 (7.2%) of 8118 adult patients had at least one infection; hospital-specific prevalences ranged between 1.9% and 12.6%. Risk factors for HCAI that were previously known or identified by univariate analysis (age, male gender, intensive care, high Charlson comorbidity and McCabe indices, respirator, central venous or urinary catheters, and surgery during stay) were included in the multivariate analysis for standardisation. Case-mix-adjusted prevalences varied between 2.6% and 17.0%, and ranked the hospitals differently from the observed rates. In 11 (38%) hospitals, the observed prevalence rank was lower than predicted by the case-mix-adjusted figure. Case-mix should be taken into consideration in the interhospital comparison of prevalence rates. Copyright 2010 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.

IL-8 predicts pediatric oncology patients with febrile neutropenia at low risk for bacteremia.

PubMed

Cost, Carrye R; Stegner, Martha M; Leonard, David; Leavey, Patrick

2013-04-01

Despite a low bacteremia rate, pediatric oncology patients are frequently admitted for febrile neutropenia. A pediatric risk prediction model with high sensitivity to identify patients at low risk for bacteremia is not available. We performed a single-institution prospective cohort study of pediatric oncology patients with febrile neutropenia to create a risk prediction model using clinical factors, respiratory viral infection, and cytokine expression. Pediatric oncology patients with febrile neutropenia were enrolled between March 30, 2010 and April 1, 2011 and managed per institutional protocol. Blood samples for C-reactive protein and cytokine expression and nasopharyngeal swabs for respiratory viral testing were obtained. Medical records were reviewed for clinical data. Statistical analysis utilized mixed multiple logistic regression modeling. During the 12-month period, 195 febrile neutropenia episodes were enrolled. There were 24 (12%) episodes of bacteremia. Univariate analysis revealed several factors predictive for bacteremia, and interleukin (IL)-8 was the most predictive variable in the multivariate stepwise logistic regression. Low serum IL-8 predicted patients at low risk for bacteremia with a sensitivity of 0.9 and negative predictive value of 0.98. IL-8 is a highly sensitive predictor for patients at low risk for bacteremia. IL-8 should be utilized in a multi-institution prospective trial to assign risk stratification to pediatric patients admitted with febrile neutropenia.

Statistical inference methods for sparse biological time series data.

PubMed

Ndukum, Juliet; Fonseca, Luís L; Santos, Helena; Voit, Eberhard O; Datta, Susmita

2011-04-25

Comparing metabolic profiles under different biological perturbations has become a powerful approach to investigating the functioning of cells. The profiles can be taken as single snapshots of a system, but more information is gained if they are measured longitudinally over time. The results are short time series consisting of relatively sparse data that cannot be analyzed effectively with standard time series techniques, such as autocorrelation and frequency domain methods. In this work, we study longitudinal time series profiles of glucose consumption in the yeast Saccharomyces cerevisiae under different temperatures and preconditioning regimens, which we obtained with methods of in vivo nuclear magnetic resonance (NMR) spectroscopy. For the statistical analysis we first fit several nonlinear mixed effect regression models to the longitudinal profiles and then used an ANOVA likelihood ratio method in order to test for significant differences between the profiles. The proposed methods are capable of distinguishing metabolic time trends resulting from different treatments and associate significance levels to these differences. Among several nonlinear mixed-effects regression models tested, a three-parameter logistic function represents the data with highest accuracy. ANOVA and likelihood ratio tests suggest that there are significant differences between the glucose consumption rate profiles for cells that had been--or had not been--preconditioned by heat during growth. Furthermore, pair-wise t-tests reveal significant differences in the longitudinal profiles for glucose consumption rates between optimal conditions and heat stress, optimal and recovery conditions, and heat stress and recovery conditions (p-values <0.0001). We have developed a nonlinear mixed effects model that is appropriate for the analysis of sparse metabolic and physiological time profiles. The model permits sound statistical inference procedures, based on ANOVA likelihood ratio tests, for testing the significance of differences between short time course data under different biological perturbations.

Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints

NASA Astrophysics Data System (ADS)

Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.

2018-01-01

Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.

Diagnostic efficiency of an ability-focused battery.

PubMed

Miller, Justin B; Fichtenberg, Norman L; Millis, Scott R

2010-05-01

An ability-focused battery (AFB) is a selected group of well-validated neuropsychological measures that assess the conventional range of cognitive domains. This study examined the diagnostic efficiency of an AFB for use in clinical decision making with a mixed sample composed of individuals with neurological brain dysfunction and individuals referred for cognitive assessment without evidence of neurological disorders. Using logistic regression analyses and ROC curve analysis, a five-domain model composed of attention, processing speed, visual-spatial reasoning, language/verbal reasoning, and memory domain scores was fitted that had an AUC of.89 (95% CI =.84-.95). A more parsimonious two-domain model using processing speed and memory was also fitted that had an AUC of.90 (95% confidence interval =.84-.95). A model composed of a global ability score calculated from the mean of the individual domain scores was also fitted with an AUC of.88 (95% CI =.82-.94).

Child Maltreatment and Delinquency Onset Among African American Adolescent Males

PubMed Central

Williams, James Herbert; Van Dorn, Richard A.; Bright, Charlotte Lyn; Jonson-Reid, Melissa; Nebbitt, Von E.

2013-01-01

Child welfare and criminology research have increasingly sought to better understand factors that increase the likelihood that abused and neglected children will become involved in the juvenile justice system. However, few studies have addressed this relationship among African American male adolescents. The current study examines the relationship between child maltreatment (i.e., neglect, physical abuse, sexual abuse, and other/mixed abuse) and the likelihood of a delinquency petition using a sample of African American males (N = 2,335) born before 1990. Multivariable logistic regression models compared those with a delinquency-based juvenile justice petition to those without. Results indicate that African American males with a history of neglect, physical abuse, or other/mixed abuse were more likely to be involved in the juvenile justice system than those without any child maltreatment. Additionally, multiple maltreatment reports, a prior history of mental health treatment, victimization, and having a parent who did not complete high school also increased the likelihood of a delinquency petition. Implications for intervention and prevention are discussed. PMID:23730121

Determinants of performance failure in the nursing home industry☆

PubMed Central

Zinn, Jacqueline; Mor, Vincent; Feng, Zhanlian; Intrator, Orna

2013-01-01

This study investigates the determinants of performance failure in U.S. nursing homes. The sample consisted of 91,168 surveys from 10,901 facilities included in the Online Survey Certification and Reporting system from 1996 to 2005. Failed performance was defined as termination from the Medicare and Medicaid programs. Determinants of performance failure were identified as core structural change (ownership change), peripheral change (related diversification), prior financial and quality of care performance, size and environmental shock (Medicaid case mix reimbursement and prospective payment system introduction). Additional control variables that could contribute to the likelihood of performance failure were included in a cross-sectional time series generalized estimating equation logistic regression model. Our results support the contention, derived from structural inertia theory, that where in an organization’s structure change occurs determines whether it is adaptive or disruptive. In addition, while poor prior financial and quality performance and the introduction of case mix reimbursement increases the risk of failure, larger size is protective, decreasing the likelihood of performance failure. PMID:19128865

Determinants of performance failure in the nursing home industry.

PubMed

Zinn, Jacqueline; Mor, Vincent; Feng, Zhanlian; Intrator, Orna

2009-03-01

This study investigates the determinants of performance failure in U.S. nursing homes. The sample consisted of 91,168 surveys from 10,901 facilities included in the Online Survey Certification and Reporting system from 1996 to 2005. Failed performance was defined as termination from the Medicare and Medicaid programs. Determinants of performance failure were identified as core structural change (ownership change), peripheral change (related diversification), prior financial and quality of care performance, size and environmental shock (Medicaid case mix reimbursement and prospective payment system introduction). Additional control variables that could contribute to the likelihood of performance failure were included in a cross-sectional time series generalized estimating equation logistic regression model. Our results support the contention, derived from structural inertia theory, that where in an organization's structure change occurs determines whether it is adaptive or disruptive. In addition, while poor prior financial and quality performance and the introduction of case mix reimbursement increases the risk of failure, larger size is protective, decreasing the likelihood of performance failure.

Child Maltreatment and Delinquency Onset Among African American Adolescent Males.

PubMed

Williams, James Herbert; Van Dorn, Richard A; Bright, Charlotte Lyn; Jonson-Reid, Melissa; Nebbitt, Von E

2010-05-01

Child welfare and criminology research have increasingly sought to better understand factors that increase the likelihood that abused and neglected children will become involved in the juvenile justice system. However, few studies have addressed this relationship among African American male adolescents. The current study examines the relationship between child maltreatment (i.e., neglect, physical abuse, sexual abuse, and other/mixed abuse) and the likelihood of a delinquency petition using a sample of African American males ( N = 2,335) born before 1990. Multivariable logistic regression models compared those with a delinquency-based juvenile justice petition to those without. Results indicate that African American males with a history of neglect, physical abuse, or other/mixed abuse were more likely to be involved in the juvenile justice system than those without any child maltreatment. Additionally, multiple maltreatment reports, a prior history of mental health treatment, victimization, and having a parent who did not complete high school also increased the likelihood of a delinquency petition. Implications for intervention and prevention are discussed.

SPD-based Logistics Management Model of Medical Consumables in Hospitals.

PubMed

Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei; Yang, Shanlin

2016-10-01

With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals. We reviewed books and scientific literature (by searching the articles published from 2010 to 2015 in Engineering Village database) to understand supply chain related theories and methods and performed field investigations in hospitals across many cities to determine the actual state of MC logistics management of hospitals in China. We describe the definition, physical model, construction, and logistics operation processes of the supply, processing, and distribution (SPD) of MC logistics because of the traditional SPD model. With the establishment of a supply-procurement platform and a logistics lean management system, we applied the model to the MC logistics management of Anhui Provincial Hospital with good effects. The SPD model plays a critical role in optimizing the logistics procedures of MCs, improving the management efficiency of logistics, and reducing the costs of logistics of hospitals in China.

Optimizing ACS NSQIP modeling for evaluation of surgical quality and risk: patient risk adjustment, procedure mix adjustment, shrinkage adjustment, and surgical focus.

PubMed

Cohen, Mark E; Ko, Clifford Y; Bilimoria, Karl Y; Zhou, Lynn; Huffman, Kristopher; Wang, Xue; Liu, Yaoming; Kraemer, Kari; Meng, Xiangju; Merkow, Ryan; Chow, Warren; Matel, Brian; Richards, Karen; Hart, Amy J; Dimick, Justin B; Hall, Bruce L

2013-08-01

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) collects detailed clinical data from participating hospitals using standardized data definitions, analyzes these data, and provides participating hospitals with reports that permit risk-adjusted comparisons with a surgical quality standard. Since its inception, the ACS NSQIP has worked to refine surgical outcomes measurements and enhance statistical methods to improve the reliability and validity of this hospital profiling. From an original focus on controlling for between-hospital differences in patient risk factors with logistic regression, ACS NSQIP has added a variable to better adjust for the complexity and risk profile of surgical procedures (procedure mix adjustment) and stabilized estimates derived from small samples by using a hierarchical model with shrinkage adjustment. New models have been developed focusing on specific surgical procedures (eg, "Procedure Targeted" models), which provide opportunities to incorporate indication and other procedure-specific variables and outcomes to improve risk adjustment. In addition, comparative benchmark reports given to participating hospitals have been expanded considerably to allow more detailed evaluations of performance. Finally, procedures have been developed to estimate surgical risk for individual patients. This article describes the development of, and justification for, these new statistical methods and reporting strategies in ACS NSQIP. Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Evolution dynamics modeling and simulation of logistics enterprise's core competence based on service innovation

NASA Astrophysics Data System (ADS)

Yang, Bo; Tong, Yuting

2017-04-01

With the rapid development of economy, the development of logistics enterprises in China is also facing a huge challenge, especially the logistics enterprises generally lack of core competitiveness, and service innovation awareness is not strong. Scholars in the process of studying the core competitiveness of logistics enterprises are mainly from the perspective of static stability, not from the perspective of dynamic evolution to explore. So the author analyzes the influencing factors and the evolution process of the core competence of logistics enterprises, using the method of system dynamics to study the cause and effect of the evolution of the core competence of logistics enterprises, construct a system dynamics model of evolution of core competence logistics enterprises, which can be simulated by vensim PLE. The analysis for the effectiveness and sensitivity of simulation model indicates the model can be used as the fitting of the evolution process of the core competence of logistics enterprises and reveal the process and mechanism of the evolution of the core competence of logistics enterprises, and provide management strategies for improving the core competence of logistics enterprises. The construction and operation of computer simulation model offers a kind of effective method for studying the evolution of logistics enterprise core competence.

Designing a supply chain of ready-mix concrete using Voronoi diagrams

NASA Astrophysics Data System (ADS)

Kozniewski, E.; Orlowski, M.; Orlowski, Z.

2017-10-01

Voronoi diagrams are used to solve scientific and practical problems in many fields. In this paper Voronoi diagrams have been applied to logistic problems in construction, more specifically in the design of the ready-mix concrete supply chain. Apart from the Voronoi diagram, the so-called time-distance circle (circle of range), which in metric space terminology is simply a sphere, appears useful. It was introduced to solve the problem of supplying concrete-related goods.

Dietary factors and the risk of testicular cancer.

PubMed

Bonner, Matthew R; McCann, Susan E; Moysich, Kirsten B

2002-01-01

The etiology of testicular cancer (TC) remains largely unknown. Few studies have investigated the role diet may play in the etiology of TC. We report on a hospital-based case-control study of TC and selected nutrients and food groups. Cases included 117 patients with primary, incident TC treated at Roswell Park Cancer Institute between 1982 and 1998. A total of 334 hospital controls were frequency matched on age to cases. Cases were categorized by histology (seminoma, nonseminoma, and mixed germ cell TC), and multinomial logistic regression and unconditional logistic regression were used to compute odds ratios (ORs) and 95% confidence intervals (CIs) comparing each histological type with the controls. For nonseminoma and mixed germ cell TC, vitamin E intake was suggestive of reduced risk (OR = 0.51, 95% CI = 0.15-1.76 and OR = 0.36, 95% CI = 0.01-1.31, respectively); for seminoma, it was suggestive of an increased risk (OR = 2.94, 95% CI = 0.99-8.78). Fat intakes were not associated with nonseminoma or mixed germ cell risk; high saturated, animal, and total fat intakes were suggestive of an increase in risk of seminoma. Overall, diet was not associated with TC. However, risk seemed to differ by histology, suggesting that seminoma, nonseminoma, and mixed germ cell TC may have different etiologies. We suggest that future investigations should continue to stratify cases by histology.

Research on JD e-commerce's delivery model

NASA Astrophysics Data System (ADS)

Fan, Zhiguo; Ma, Mengkun; Feng, Chaoying

2017-03-01

E-commerce enterprises represented by JD have made a great contribution to the economic growth and economic development of our country. Delivery, as an important part of logistics, has self-evident importance. By establishing efficient and perfect self-built logistics systems and building good cooperation models with third-party logistics enterprises, e-commerce enterprises have created their own logistics advantages. Characterized by multi-batch and small-batch, e-commerce is much more complicated than traditional transaction. It's not easy to decide which delivery model e-commerce enterprises should adopt. Having e-commerce's logistics delivery as the main research object, this essay aims to find a more suitable logistics delivery model for JD's development.

SPD-based Logistics Management Model of Medical Consumables in Hospitals

PubMed Central

LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei; YANG, Shanlin

2016-01-01

Background: With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals. Methods: We reviewed books and scientific literature (by searching the articles published from 2010 to 2015 in Engineering Village database) to understand supply chain related theories and methods and performed field investigations in hospitals across many cities to determine the actual state of MC logistics management of hospitals in China. Results: We describe the definition, physical model, construction, and logistics operation processes of the supply, processing, and distribution (SPD) of MC logistics because of the traditional SPD model. With the establishment of a supply-procurement platform and a logistics lean management system, we applied the model to the MC logistics management of Anhui Provincial Hospital with good effects. Conclusion: The SPD model plays a critical role in optimizing the logistics procedures of MCs, improving the management efficiency of logistics, and reducing the costs of logistics of hospitals in China. PMID:27957435

Selected Logistics Models and Techniques.

DTIC Science & Technology

1984-09-01

TI - 59 Programmable Calculator LCC...Program 27 TI - 59 Programmable Calculator LCC Model 30 Unmanned Spacecraft Cost Model 31 iv I: TABLE OF CONTENTS (CONT’D) (Subject Index) LOGISTICS...34"" - % - "° > - " ° .° - " .’ > -% > ]*° - LOGISTICS ANALYSIS MODEL/TECHNIQUE DATA MODEL/TECHNIQUE NAME: TI - 59 Programmable Calculator LCC Model TYPE MODEL: Cost Estimating DEVELOPED BY:

The influence of maternal and paternal history on stone composition and clinical course of calcium nephrolithiasis in subjects aged between 15 and 25.

PubMed

Guerra, Angela; Ticinesi, Andrea; Allegri, Franca; Nouvenne, Antonio; Pinelli, Silvana; Folesani, Giuseppina; Lauretani, Fulvio; Maggio, Marcello; Borghi, Loris; Meschi, Tiziana

2016-11-01

Our aim was to compare the influence of maternal history of stones (MHS) and paternal history of stones (PHS) on composition of calculi and disease course in a group of patients with calcium nephrolithiasis (CN) aged between 15 and 25, the age range with the maximal influence of family history on disease expression. One-hundred thirty-five patients (68 F) with CN and one stone-forming parent were retrospectively selected from the database of our outpatient stone clinic, and categorized according to MHS or PHS. Data about stone disease course and composition of passed calculi, determined by chemical analysis or Fourier-transformed infrared spectrophotometry, were collected together with information on blood chemistry and 24-h urinary profile of lithogenic risk. The characteristics of disease course and stone composition were compared using logistic regression tests adjusted for age, sex, and BMI or analysis of covariance where appropriate. Patients with MHS (n = 46) had significantly higher urinary calcium/creatinine ratio and ammonium, a higher prevalence of urological treatments (57 vs 27 %, p < 0.001) and mixed calcium oxalate/calcium phosphate stone composition (69 vs 35 %, p = 0.002) than those with PHS. At multivariate logistic regression models, MHS was independently associated with urological treatments (OR 4.5, 95 %CI 1.9-10.7, p < 0.001) and the formation of calculi with mixed calcium oxalate/calcium phosphate composition (OR 5.8, 95 %CI 1.9-17.9, p = 0.002). The method of stone analysis did not affect this result. In conclusion, in subjects aged 15-25, MHS is associated with mixed calcium stones and with a higher risk for urological procedures, and should be, therefore, considered in the management of urolithiasis.

Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

NASA Astrophysics Data System (ADS)

Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

2017-06-01

A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

An investigation of the predictors of photoprotection and UVR dose to the face in patients with XP: a protocol using observational mixed methods

PubMed Central

Walburn, Jessica; Sarkany, Robert; Norton, Sam; Foster, Lesley; Morgan, Myfanwy; Sainsbury, Kirby; Araújo-Soares, Vera; Anderson, Rebecca; Garrood, Isabel; Heydenreich, Jakob; Sniehotta, Falko F; Vieira, Rute; Wulf, Hans Christian; Weinman, John

2017-01-01

Introduction Xeroderma pigmentosum (XP) is a rare genetic condition caused by defective nucleotide excision repair and characterised by skin cancer, ocular and neurological involvement. Stringent ultraviolet protection is the only way to prevent skin cancer. Despite the risks, some patients’ photoprotection is poor, with a potentially devastating impact on their prognosis. The aim of this research is to identify disease-specific and psychosocial predictors of photoprotection behaviour and ultraviolet radiation (UVR) dose to the face. Methods and analysis Mixed methods research based on 45 UK patients will involve qualitative interviews to identify individuals’ experience of XP and the influences on their photoprotection behaviours and a cross-sectional quantitative survey to assess biopsychosocial correlates of these behaviours at baseline. This will be followed by objective measurement of UVR exposure for 21 days by wrist-worn dosimeter and daily recording of photoprotection behaviours and psychological variables for up to 50 days in the summer months. This novel methodology will enable UVR dose reaching the face to be calculated and analysed as a clinically relevant endpoint. A range of qualitative and quantitative analytical approaches will be used, reflecting the mixed methods (eg, cross-sectional qualitative interviews, n-of-1 studies). Framework analysis will be used to analyse the qualitative interviews; mixed-effects longitudinal models will be used to examine the association of clinical and psychosocial factors with the average daily UVR dose; dynamic logistic regression models will be used to investigate participant-specific psychosocial factors associated with photoprotection behaviours. Ethics and dissemination This research has been approved by Camden and King’s Cross Research Ethics Committee 15/LO/1395. The findings will be published in peer-reviewed journals and presented at national and international scientific conferences. PMID:28827277

12-step participation and outcomes over 7 years among adolescent substance use patients with and without psychiatric comorbidity.

PubMed

Chi, Felicia W; Sterling, Stacy; Campbell, Cynthia I; Weisner, Constance

2013-01-01

This study examines the associations between 12-step participation and outcomes over 7 years among 419 adolescent substance use patients with and without psychiatric comorbidities. Although level of participation decreased over time for both groups, comorbid adolescents participated in 12-step groups at comparable or higher levels across time points. Results from mixed-effects logistic regression models indicated that for both groups, 12-step participation was associated with both alcohol and drug abstinence at follow-ups, increasing the likelihood of either by at least 3 times. Findings highlight the potential benefits of 12-step participation in maintaining long-term recovery for adolescents with and without psychiatric disorders.

Optimization Models for Scheduling of Jobs

PubMed Central

Indika, S. H. Sathish; Shier, Douglas R.

2006-01-01

This work is motivated by a particular scheduling problem that is faced by logistics centers that perform aircraft maintenance and modification. Here we concentrate on a single facility (hangar) which is equipped with several work stations (bays). Specifically, a number of jobs have already been scheduled for processing at the facility; the starting times, durations, and work station assignments for these jobs are assumed to be known. We are interested in how best to schedule a number of new jobs that the facility will be processing in the near future. We first develop a mixed integer quadratic programming model (MIQP) for this problem. Since the exact solution of this MIQP formulation is time consuming, we develop a heuristic procedure, based on existing bin packing techniques. This heuristic is further enhanced by application of certain local optimality conditions. PMID:27274921

GIS-based spatial decision support system for grain logistics management

NASA Astrophysics Data System (ADS)

Zhen, Tong; Ge, Hongyi; Jiang, Yuying; Che, Yi

2010-07-01

Grain logistics is the important component of the social logistics, which can be attributed to frequent circulation and the great quantity. At present time, there is no modern grain logistics distribution management system, and the logistics cost is the high. Geographic Information Systems (GIS) have been widely used for spatial data manipulation and model operations and provide effective decision support through its spatial database management capabilities and cartographic visualization. In the present paper, a spatial decision support system (SDSS) is proposed to support policy makers and to reduce the cost of grain logistics. The system is composed of two major components: grain logistics goods tracking model and vehicle routing problem optimization model and also allows incorporation of data coming from external sources. The proposed system is an effective tool to manage grain logistics in order to increase the speed of grain logistics and reduce the grain circulation cost.

Bayesian Estimation of the Logistic Positive Exponent IRT Model

ERIC Educational Resources Information Center

Bolfarine, Heleno; Bazan, Jorge Luis

2010-01-01

A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric…

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

PubMed

Liu, Yang; Traskin, Mikhail; Lorch, Scott A; George, Edward I; Small, Dylan

2015-03-01

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital's expected outcome rate given its patient mix and service is called risk adjustment (Iezzoni 1997). Risk adjustment is critical for accurately evaluating and comparing hospitals' performances since we would not want to unfairly penalize a hospital just because it treats sicker patients. The key to risk adjustment is accurately estimating the probability of an Outcome given patient characteristics. For cases with binary outcomes, the method that is commonly used in risk adjustment is logistic regression. In this paper, we consider ensemble of trees methods as alternatives for risk adjustment, including random forests and Bayesian additive regression trees (BART). Both random forests and BART are modern machine learning methods that have been shown recently to have excellent performance for prediction of outcomes in many settings. We apply these methods to carry out risk adjustment for the performance of neonatal intensive care units (NICU). We show that these ensemble of trees methods outperform logistic regression in predicting mortality among babies treated in NICU, and provide a superior method of risk adjustment compared to logistic regression.

The understanding and experience of mixed emotions in 3-5-year-old children.

PubMed

Smith, Joshua P; Glass, Daniel J; Fireman, Gary

2015-01-01

The term mixed emotions refers to the presence of two opposite-valence emotions toward a single target. Identifying when children begin to report experiencing and understanding mixed emotions is critical in identifying how skills such as adaptive functioning, coping strategies, environmental understanding, and socioemotional competence emerge. Prior research has shown that children as young as 5 years old can understand and experience mixed emotion, but perhaps appropriately sensitive methodologies can reveal these abilities in younger children. The present study evaluated 57 children between 3 and 5 years old for mixed emotion experience and understanding using an animated video clip in which a character experiences a mixed emotional episode. Ordinal logistic regression was utilized to examine the relation of gender, attention, and understanding of content to experience and understanding of mixed emotion. While only 12% of children reported experiencing mixed emotion while watching the clip, 49% of children-some as young as 3 years old-were able to recognize the mixed emotional experience of the character. Thus, mixed emotion understanding emerges earlier than previously identified and the expression of understanding may develop independently of the ability to report mixed emotion experience. These findings are discussed in relation to cognitive and developmental considerations.

Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions.

PubMed

Choi, Yoonha; Liu, Tiffany Ting; Pankratz, Daniel G; Colby, Thomas V; Barth, Neil M; Lynch, David A; Walsh, P Sean; Raghu, Ganesh; Kennedy, Giulia C; Huang, Jing

2018-05-09

We developed a classifier using RNA sequencing data that identifies the usual interstitial pneumonia (UIP) pattern for the diagnosis of idiopathic pulmonary fibrosis. We addressed significant challenges, including limited sample size, biological and technical sample heterogeneity, and reagent and assay batch effects. We identified inter- and intra-patient heterogeneity, particularly within the non-UIP group. The models classified UIP on transbronchial biopsy samples with a receiver-operating characteristic area under the curve of ~ 0.9 in cross-validation. Using in silico mixed samples in training, we prospectively defined a decision boundary to optimize specificity at ≥85%. The penalized logistic regression model showed greater reproducibility across technical replicates and was chosen as the final model. The final model showed sensitivity of 70% and specificity of 88% in the test set. We demonstrated that the suggested methodologies appropriately addressed challenges of the sample size, disease heterogeneity and technical batch effects and developed a highly accurate and robust classifier leveraging RNA sequencing for the classification of UIP.

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression

PubMed Central

Weiss, Brandi A.; Dardick, William

2015-01-01

This article introduces an entropy-based measure of data–model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data–model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Carlo simulation results are used to demonstrate the application of entropy in logistic regression. Entropy should be used in conjunction with other measures of data–model fit to assess how well logistic regression models classify cases into observed categories. PMID:29795897

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression.

PubMed

Weiss, Brandi A; Dardick, William

2016-12-01

This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data-model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Carlo simulation results are used to demonstrate the application of entropy in logistic regression. Entropy should be used in conjunction with other measures of data-model fit to assess how well logistic regression models classify cases into observed categories.

Comparing the Discrete and Continuous Logistic Models

ERIC Educational Resources Information Center

Gordon, Sheldon P.

2008-01-01

The solutions of the discrete logistic growth model based on a difference equation and the continuous logistic growth model based on a differential equation are compared and contrasted. The investigation is conducted using a dynamic interactive spreadsheet. (Contains 5 figures.)

Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 emission reduction targets

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

Zhang, Dezhi; Zhan, Qingwen; Chen, Yuche

This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed modelmore » is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.« less

Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 emission reduction targets

DOE PAGES

Zhang, Dezhi; Zhan, Qingwen; Chen, Yuche; ...

2016-03-14

This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed modelmore » is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.« less

Logistics Modeling for Lunar Exploration Systems

NASA Technical Reports Server (NTRS)

Andraschko, Mark R.; Merrill, R. Gabe; Earle, Kevin D.

2008-01-01

The extensive logistics required to support extended crewed operations in space make effective modeling of logistics requirements and deployment critical to predicting the behavior of human lunar exploration systems. This paper discusses the software that has been developed as part of the Campaign Manifest Analysis Tool in support of strategic analysis activities under the Constellation Architecture Team - Lunar. The described logistics module enables definition of logistics requirements across multiple surface locations and allows for the transfer of logistics between those locations. A key feature of the module is the loading algorithm that is used to efficiently load logistics by type into carriers and then onto landers. Attention is given to the capabilities and limitations of this loading algorithm, particularly with regard to surface transfers. These capabilities are described within the context of the object-oriented software implementation, with details provided on the applicability of using this approach to model other human exploration scenarios. Some challenges of incorporating probabilistics into this type of logistics analysis model are discussed at a high level.

Equal Area Logistic Estimation for Item Response Theory

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching; Wang, Kuo-Chang; Chang, Hsin-Li

2009-08-01

Item response theory (IRT) models use logistic functions exclusively as item response functions (IRFs). Applications of IRT models require obtaining the set of values for logistic function parameters that best fit an empirical data set. However, success in obtaining such set of values does not guarantee that the constructs they represent actually exist, for the adequacy of a model is not sustained by the possibility of estimating parameters. In this study, an equal area based two-parameter logistic model estimation algorithm is proposed. Two theorems are given to prove that the results of the algorithm are equivalent to the results of fitting data by logistic model. Numerical results are presented to show the stability and accuracy of the algorithm.

Evolution Model and Simulation of Profit Model of Agricultural Products Logistics Financing

NASA Astrophysics Data System (ADS)

Yang, Bo; Wu, Yan

2018-03-01

Agricultural products logistics financial warehousing business mainly involves agricultural production and processing enterprises, third-party logistics enterprises and financial institutions tripartite, to enable the three parties to achieve win-win situation, the article first gives the replication dynamics and evolutionary stability strategy between the three parties in business participation, and then use NetLogo simulation platform, using the overall modeling and simulation method of Multi-Agent, established the evolutionary game simulation model, and run the model under different revenue parameters, finally, analyzed the simulation results. To achieve the agricultural products logistics financial financing warehouse business to participate in tripartite mutually beneficial win-win situation, thus promoting the smooth flow of agricultural products logistics business.

Analysis of risk factors in severity of rural truck crashes.

DOT National Transportation Integrated Search

2016-04-01

Trucks are a vital part of the logistics system in North Dakota. Recent energy developments have : generated exponential growth in the demand for truck services. With increased density of trucks in the : traffic mix, it is reasonable to expect some i...

Supply Chain Engineering and the Use of a Supporting Knowledge Management Application

NASA Astrophysics Data System (ADS)

Laakmann, Frank

The future competition in markets will happen between logistics networks and no longer between enterprises. A new approach for supporting the engineering of logistics networks is developed by this research as a part of the Collaborative Research Centre (SFB) 559: "Modeling of Large Networks in Logistics" at the University of Dortmund together with the Fraunhofer-Institute of Material Flow and Logistics founded by Deutsche Forschungsgemeinschaft (DFG). Based on a reference model for logistics processes, the process chain model, a guideline for logistics engineers is developed to manage the different types of design tasks of logistics networks. The technical background of this solution is a collaborative knowledge management application. This paper will introduce how new Internet-based technologies support supply chain design projects.

Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

PubMed

Nikbakht, Roya; Bahrampour, Abbas

2017-01-01

Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

The use of the logistic model in space motion sickness prediction

NASA Technical Reports Server (NTRS)

Lin, Karl K.; Reschke, Millard F.

1987-01-01

The one-equation and the two-equation logistic models were used to predict subjects' susceptibility to motion sickness in KC-135 parabolic flights using data from other ground-based motion sickness tests. The results show that the logistic models correctly predicted substantially more cases (an average of 13 percent) in the data subset used for model building. Overall, the logistic models ranged from 53 to 65 percent predictions of the three endpoint parameters, whereas the Bayes linear discriminant procedure ranged from 48 to 65 percent correct for the cross validation sample.

MIXED-STATUS FAMILIES AND WIC UPTAKE: THE EFFECTS OF RISK OF DEPORTATION ON PROGRAM USE

PubMed Central

Vargas, Edward D.; Pirog, Maureen A.

2016-01-01

Objective Develop and test measures of risk of deportation and mixed-status families on WIC uptake. Mixed-status is a situation in which some family members are U.S. citizens and other family members are in the U.S. without proper authorization. Methods Estimate a series of logistic regressions to estimate WIC uptake by merging data from Fragile Families and Child Well-being Survey with deportation data from U.S.-Immigration Customs and Enforcement. Results The findings of this study suggest that risk of deportation is negatively associated with WIC uptake and among mixed-status families; Mexican origin families are the most sensitive when it comes to deportations and program use. Conclusion Our analysis provides a typology and framework to study mixed-status families and evaluate their usage of social services by including an innovative measure of risk of deportation. PMID:27642194

Growth/no growth boundary of Clostridium perfringens from spores in cooked meat: A logistic analysis.

PubMed

Huang, Lihan; Li, Changcheng; Hwang, Cheng-An

2018-02-02

Clostridium perfringens is a major foodborne health hazard that can cause acute gastroenteritis in consumers, and is often associated with cooked meat and poultry products. Improper cooling after cooking may allow this pathogen to grow in a product, producing an enterotoxin that causes food poisoning. This study was conducted to evaluate the effect of common ingredients, including sodium tripolyphosphate (STPP), sodium lactate (NaL), and sodium chloride (NaCl), on the germination and outgrowth of C. perfringens spores in meat products. The growth/no growth test was conducted in Shahidi Ferguson Perfringens agar mixed with STPP (0-2500ppm), NaL (0-4%), and NaCl (0-4%) in microplates. Turbidity measurements at 600nm were compared before and after anaerobic incubation at 46°C to evaluate growth and no growth conditions. The dichotomous responses were analyzed by logistic regression to develop a model for estimating the growth probability of C. perfringens. The probability model was used to define the threshold of growth (probability >0.1 or 0.2) of C. perfringens and validated using inoculated ground beef under optimum temperature. Inoculated ground beef was mixed with different combinations of STPP, NaL, and NaCl to observe growth or no growth of C. perfringens, and the probability was calculated from the formulation. If the threshold of growth was set to 0.2, the accuracy of the growth and no growth predictions was 95.7%, with 4.3% over-prediction of growth events (fail-safe). The results from this study suggested that proper combinations of STPP, NaL, and NaCl could be used to control the growth of C. perfringens in cooked beef under the optimum temperature. The results may also suggest that proper combinations of STPP, NaL, and NaCl in cooked meat and poultry products could be used to prevent the growth of C. perfringens during cooling. Published by Elsevier B.V.

Comparison of marginal bone loss and implant success between axial and tilted implants in maxillary All-on-4 treatment concept rehabilitations after 5 years of follow-up.

PubMed

Hopp, Milena; de Araújo Nobre, Miguel; Maló, Paulo

2017-10-01

There is need for more scientific and clinical information on longer-term outcomes of tilted implants compared to implants inserted in an axial position. Comparison of marginal bone loss and implant success after a 5-year follow-up between axial and tilted implants inserted for full-arch maxillary rehabilitation. The retrospective clinical study included 891 patients with 3564 maxillary implants rehabilitated according to the All-on-4 treatment concept. The follow-up time was 5 years. Linear mixed-effect models were performed to analyze the influence of implant orientation (axial/tilted) on marginal bone loss and binary logistic regression to assess the effect of patient characteristics on occurrence of marginal bone loss >2.8 mm. Only those patients with measurements of at least one axial and one tilted implant available were analyzed. This resulted in a data set of 2379 implants (1201 axial, 1178 tilted) in 626 patients (=reduced data set). Axial and tilted implants showed comparable mean marginal bone losses of 1.14 ± 0.71 and 1.19 ± 0.82 mm, respectively. Mixed model analysis indicated that marginal bone loss levels at 5 years follow up was not significantly affected by the orientation (axial/tilted) of the implants in the maxillary bone. Smoking and female gender were associated with marginal bone loss >2.8 mm in a logistic regression analysis. Five-year implant success rates were 96%. The occurrence of implant failure showed to be statistically independent from orientation. Within the limitations of this study and considering a follow-up time of 5 years, it can be concluded that tilted implants behave similarly with regards to marginal bone loss and implant success in comparison to axial implants in full-arch rehabilitation of the maxilla. Longer-term outcomes (10 years +) are needed to verify this result. © 2017 Wiley Periodicals, Inc.

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.

Incidence and predictors of suicide attempts in bipolar I and II disorders: A 5-year follow-up study.

PubMed

Pallaskorpi, Sanna; Suominen, Kirsi; Ketokivi, Mikko; Valtonen, Hanna; Arvilommi, Petri; Mantere, Outi; Leppämäki, Sami; Isometsä, Erkki

2017-02-01

Few long-term studies on bipolar disorder (BD) have investigated the incidence and risk factors of suicide attempts (SAs) specifically related to illness phases. We examined the incidence of SAs during different phases of BD in a long-term prospective cohort of bipolar I (BD-I) and bipolar II (BD-II) patients, and risk factors specifically for SAs during major depressive episodes (MDEs). In the Jorvi Bipolar Study (JoBS), 191 BD-I and BD-II patients were followed using life-chart methodology. Prospective information on SAs of 177 patients (92.7%) during different illness phases was available up to 5 years. The incidence of SAs and their predictors were investigated using logistic and Poisson regression models. Analyses of risk factors for SAs occurring during MDEs were conducted using two-level random-intercept logistic regression models. During the 5 years of follow-up, 90 SAs per 718 patient-years occurred. The incidence was highest, over 120-fold higher than in euthymia, during mixed states (765/1000 person-years; 95% confidence interval [CI] 461-1269 person-years), and also very high in MDEs, almost 60-fold higher than in euthymia (354/1000 person-years; 95% CI 277-451 person-years). For risk of SAs during MDEs, the duration of MDEs, severity of depression, and cluster C personality disorders were significant predictors. We confirmed in this long-term study that the highest incidences of SAs occur in mixed and major depressive illness phases. The variations in incidence rates between euthymia and illness phases were remarkably large, suggesting that the question "when" rather than "who" may be more relevant for suicide risk in BD. However, risk during MDEs is likely also influenced by personality factors. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Hele-Shaw Experiments on Plume Stretching and Folding

NASA Astrophysics Data System (ADS)

Foster, M.; Mays, D. C.; Neupauer, R. M.

2013-12-01

Fluid mixing in laminar flow is important in a number of practical applications, including remediation of contaminated groundwater. Recent modeling studies have shown that mixing can be accelerated and amplified by imposing a flow that generates stretching and folding of an injected plume of treatment solution. Stretching and folding, in turn, results from engineered injection and extraction of clean water through an array of wells surrounding the treatment solution. This poster describes a series of experiments whose goal is to demonstrate plume stretching and folding in a Hele-Shaw apparatus. An initial plume of treatment solution is injected into the center of the Hele-Shaw apparatus, which is assumed to represent a zone of contaminated groundwater, with four wells spaced evenly around the treatment solution. In order to spread the treatment solution into the groundwater, the four wells perform a series of infusions and withdrawals that push and pull apart the plume of treatment solution. With the proper steps, it will be shown that the plume can be stretched and folded to greatly increase the reactive interface area between the treatment solution and the contaminated groundwater. Consideration is given to two qualitative differences with respect to previous modeling studies. First, constant volume is required by the no-flow boundary used at the edge of the Hele-Shaw cell; any pump that is withdrawing water must have a complementary pump adding water at the same rate. Second, in these experiments, mixing results from a physical process, namely Taylor dispersion, eliminating the uncertainty resulting from the need to assume dispersion mechanisms in numerical models. Therefore, these experiments further elucidate the benefits and challenges of imposing plume stretching and folding in systems (like aquifers) where dispersion is unavoidable, providing new insight into the required logistics of using this approach in groundwater treatment.

A mixed-methods exploration of implementation of a comprehensive school healthy eating model one year after scale-up.

PubMed

Naylor, Patti-Jean; McKay, Heather A; Valente, Maria; Mâsse, Louise C

2016-04-01

To study the implementation of a school-based healthy eating (HE) model one year after scale-up in British Columbia (BC). Specifically, to examine implementation of Action Schools! BC (AS! BC) and its influence on implementation of classroom HE activities, and to explore factors associated with implementation. Diffusion of Innovations, Social Cognitive and Organizational Change theories guided our approach. We used a mixed-methods research design including focus group interviews (seven schools, sixty-two implementers) and a cross-sectional multistage survey to principals (n 36, 92 % response rate) and teachers of grades 4 to 7 (n 168, 70 % response rate). Self-reported implementation of classroom HE activities and reported use of specific AS! BC HE activities were primary implementation measures. Thematic analysis of focus group data and multilevel mixed-effect logistic regression analyses of survey data were conducted. Elementary schools across BC, Canada. Thirty-nine school districts, thirty-six principals, 168 grade 4 to 7 teachers. Forty-two per cent of teachers in registered schools were implementing AS! BC HE in their classrooms. Users were 6·25 times more likely to have delivered a HE lesson in the past week. Implementation facilitators were school champions, technical support and access to resources; barriers were lack of time, loss of leadership or momentum. Implementation predictors were teacher training, self-efficacy, experience with the physical activity component of AS! BC, supportive school climate and parental post-secondary education. Our findings reinforce that continued teacher training and support are important public health investments that contribute to successful implementation of school-based HE models after scale-up.

Genome analysis of Legionella pneumophila strains using a mixed-genome microarray.

PubMed

Euser, Sjoerd M; Nagelkerke, Nico J; Schuren, Frank; Jansen, Ruud; Den Boer, Jeroen W

2012-01-01

Legionella, the causative agent for Legionnaires' disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data. Microarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in The Netherlands in the period 2002-2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental. Four genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment.

Lung functions among patients with pulmonary tuberculosis in Dar es Salaam - a cross-sectional study.

PubMed

Manji, Mohamed; Shayo, Grace; Mamuya, Simon; Mpembeni, Rose; Jusabani, Ahmed; Mugusi, Ferdinand

2016-04-23

Approximately 40-60 % of patients remain sufferers of sequela of obstructive, restrictive or mixed patterns of lung disease despite treatment for pulmonary tuberculosis (PTB). The prevalence of these abnormalities in Tanzania remains unknown. A descriptive cross-sectional study was carried out among 501 patients with PTB who had completed at least 20 weeks of treatment. These underwent spirometry and their lung functions were classified as normal or abnormal (obstructive, restrictive or mixed). Logistic regression models were used to explore factors associated with abnormal lung functions. Abnormal lung functions were present in 371 (74 %) patients. There were 210 (42 %) patients with obstructive, 65 (13 %) patients with restrictive and 96 (19 %) patients with mixed patterns respectively. Significant factors associated with abnormal lung functions included recurrent PTB (Adj OR 2.8, CI 1.274 - 6.106), Human Immunodeficiency Virus (HIV) negative status (Adj OR 1.7, CI 1.055 - 2.583), age more than 40 years (Adj OR 1.7, CI 1.080 - 2.804) and male sex (Adj OR 1.7, CI 1.123 - 2.614). The prevalence of abnormal lung functions is high and it is associated with male sex, age older than 40 years, recurrent PTB and HIV negative status.

Occupational dermatitis in Danish gardeners and greenhouse workers (III). Compositae-related symptoms.

PubMed

Paulsen, E; Søgaard, J; Andersen, K E

1998-03-01

The clinical part of the study aimed at describing epidemiological and diagnostic aspects of occupational Compositae dermatitis. Patch testing with the sesquiterpene lactone (SL) and Compositae mixes, feverfew extract and supplementary allergens in 250 selected gardeners showed Compositae allergy in 25, 17 females and 8 males. 24 were possibly occupationally sensitized. The mean age was lower and the preponderance of women higher compared to classical Compositae dermatitis, and the distribution and course of the dermatitis most often did not differ from other occupational plant dermatoses. The Compositae mix detected 2x as many as the SL mix, and the overall detection rate with both was 76%, making aimed patch testing necessary. Chrysanthemum (Dendranthema), marguerite daisy (Argyranthemum frutescens) and lettuce (Lactuca sativa) were frequent sensitizers. Occupational type I allergy to Compositae comprised sensitization to Gerbera, chrysanthemum, lettuce, Senecio cruentus and Aster. Among 1657 respondents in the questionnaire part of the study, 824 had worked with Compositae, and 160 (19%) reported occupational Compositae-related symptoms of skin and mucous membranes. Possible risk factors for the development of these were assessed in a stepwise logistic regression model and a history of childhood eczema, hay fever and duration of exposure were significantly associated with Compositae-related irritant and allergic symptoms in both sexes.

Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite.

PubMed

Castelo, Paula Midori; Gavião, Maria Beatriz Duarte; Pereira, Luciano José; Bonjardim, Leonardo Rigoldi

2010-01-01

The maintenance of normal conditions of the masticatory function is determinant for the correct growth and development of its structures. Thus, the aims of this study were to evaluate the influence of sucking habits on the presence of crossbite and its relationship with maximal bite force, facial morphology and body variables in 67 children of both genders (3.5-7 years) with primary or early mixed dentition. The children were divided in four groups: primary-normocclusion (PN, n=19), primary-crossbite (PC, n=19), mixed-normocclusion (MN, n=13), and mixed-crossbite (MC, n=16). Bite force was measured with a pressurized tube, and facial morphology was determined by standardized frontal photographs: AFH (anterior face height) and BFW (bizygomatic facial width). It was observed that MC group showed lower bite force than MN, and AFH/BFW was significantly smaller in PN than PC (t-test). Weight and height were only significantly correlated with bite force in PC group (Pearson's correlation test). In the primary dentition, AFH/BFW and breast-feeding (at least six months) were positive and negatively associated with crossbite, respectively (multiple logistic regression). In the mixed dentition, breast-feeding and bite force showed negative associations with crossbite (univariate regression), while nonnutritive sucking (up to 3 years) associated significantly with crossbite in all groups (multiple logistic regression). In the studied sample, sucking habits played an important role in the etiology of crossbite, which was associated with lower bite force and long-face tendency.

Relevance of the c-statistic when evaluating risk-adjustment models in surgery.

PubMed

Merkow, Ryan P; Hall, Bruce L; Cohen, Mark E; Dimick, Justin B; Wang, Edward; Chow, Warren B; Ko, Clifford Y; Bilimoria, Karl Y

2012-05-01

The measurement of hospital quality based on outcomes requires risk adjustment. The c-statistic is a popular tool used to judge model performance, but can be limited, particularly when evaluating specific operations in focused populations. Our objectives were to examine the interpretation and relevance of the c-statistic when used in models with increasingly similar case mix and to consider an alternative perspective on model calibration based on a graphical depiction of model fit. From the American College of Surgeons National Surgical Quality Improvement Program (2008-2009), patients were identified who underwent a general surgery procedure, and procedure groups were increasingly restricted: colorectal-all, colorectal-elective cases only, and colorectal-elective cancer cases only. Mortality and serious morbidity outcomes were evaluated using logistic regression-based risk adjustment, and model c-statistics and calibration curves were used to compare model performance. During the study period, 323,427 general, 47,605 colorectal-all, 39,860 colorectal-elective, and 21,680 colorectal cancer patients were studied. Mortality ranged from 1.0% in general surgery to 4.1% in the colorectal-all group, and serious morbidity ranged from 3.9% in general surgery to 12.4% in the colorectal-all procedural group. As case mix was restricted, c-statistics progressively declined from the general to the colorectal cancer surgery cohorts for both mortality and serious morbidity (mortality: 0.949 to 0.866; serious morbidity: 0.861 to 0.668). Calibration was evaluated graphically by examining predicted vs observed number of events over risk deciles. For both mortality and serious morbidity, there was no qualitative difference in calibration identified between the procedure groups. In the present study, we demonstrate how the c-statistic can become less informative and, in certain circumstances, can lead to incorrect model-based conclusions, as case mix is restricted and patients become more homogenous. Although it remains an important tool, caution is advised when the c-statistic is advanced as the sole measure of a model performance. Copyright © 2012 American College of Surgeons. All rights reserved.

Landscape factors influencing the spatial distribution and abundance of mosquito vector Culex quinquefasciatus (Diptera: Culicidae) in a mixed residential-agricultural community in Hawai'i

USGS Publications Warehouse

Reiter, M.E.; Lapointe, D.A.

2007-01-01

Mosquito-borne avian diseases, principally avian malaria (Plasmodium relictum Grassi and Feletti) and avian pox (Avipoxvirus sp.) have been implicated as the key limiting factor associated with recent declines of endemic avifauna in the Hawaiian Island archipelago. We present data on the relative abundance, infection status, and spatial distribution of the primary mosquito vector Culex quinquefasciatus Say (Diptera: Culicidae) across a mixed, residential-agricultural community adjacent to Hawai'i Volcanoes National Park on Hawai'i Island. We modeled the effect of agriculture and forest fragmentation in determining relative abundance of adult Cx. quinquefasciatus in Volcano Village, and we implement our statistical model in a geographic information system to generate a probability of mosquito capture prediction surface for the study area. Our model was based on biweekly captures of adult mosquitoes from 20 locations within Volcano Village from October 2001 to April 2003. We used mixed effects logistic regression to model the probability of capturing a mosquito, and we developed a set of 17 competing models a priori to specifically evaluate the effect of agriculture and fragmentation (i.e., residential landscapes) at two spatial scales. In total, 2,126 mosquitoes were captured in CO 2-baited traps with an average probability of 0.27 (SE = 0.10) of capturing one or more mosquitoes per trap night. Twelve percent of mosquitoes captured were infected with P. relictum. Our data indicate that agricultural lands and forest fragmentation significantly increase the probability of mosquito capture. The prediction surface identified areas along the Hawai'i Volcanoes National Park boundary that may have high relative abundance of the vector. Our data document the potential of avian malaria transmission in residential-agricultural landscapes and support the need for vector management that extends beyond reserve boundaries and considers a reserve's spatial position in a highly heterogeneous landscape.

No causal impact of serum vascular endothelial growth factor level on temporal changes in body mass index in Japanese male workers: a five-year longitudinal study.

PubMed

Imatoh, Takuya; Kamimura, Seiichiro; Miyazaki, Motonobu

2017-03-01

It has been reported that adipocytes secrete vascular endothelial growth factor. Therefore, we conducted a 5-year longitudinal epidemiological study to further elucidate the association between vascular endothelial growth factor levels and temporal changes in body mass index. Our study subjects were Japanese male workers, who had regular health check-ups. Vascular endothelial growth factor levels were measured at baseline. To examine the association between vascular endothelial growth factor levels and overweight, we calculated the odds ratio using a multivariate logistic regression model. Moreover, linear mixed effect models were used to assess the association between vascular endothelial growth factor level and temporal changes in body mass index during the 5-year follow-up period. Vascular endothelial growth factor levels were marginally higher in subjects with a body mass index greater than 25 kg/m 2 compared with in those with a body mass index less than 25 kg/m 2 (505.4 vs. 465.5 pg/mL, P = 0.1) and were weakly correlated with leptin levels (β: 0.05, P = 0.07). In multivariate logistic regression, subjects in the highest vascular endothelial growth factor quantile were significantly associated with an increased risk for overweight compared with those in the lowest quantile (odds ratio 1.65, 95 % confidential interval: 1.10-2.50). Moreover P for trend was significant (P for trend = 0.003). However, the linear mixed effect model revealed that vascular endothelial growth factor levels were not associated with changes in body mass index over a 5-year period (quantile 2, β: 0.06, P = 0.46; quantile 3, β: -0.06, P = 0.45; quantile 4, β: -0.10, P = 0.22; quantile 1 as reference). Our results suggested that high vascular endothelial growth factor levels were significantly associated with overweight in Japanese males but high vascular endothelial growth factor levels did not necessarily cause obesity.

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.

Comparison of the binary logistic and skewed logistic (Scobit) models of injury severity in motor vehicle collisions.

PubMed

Tay, Richard

2016-03-01

The binary logistic model has been extensively used to analyze traffic collision and injury data where the outcome of interest has two categories. However, the assumption of a symmetric distribution may not be a desirable property in some cases, especially when there is a significant imbalance in the two categories of outcome. This study compares the standard binary logistic model with the skewed logistic model in two cases in which the symmetry assumption is violated in one but not the other case. The differences in the estimates, and thus the marginal effects obtained, are significant when the assumption of symmetry is violated. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression

ERIC Educational Resources Information Center

Weiss, Brandi A.; Dardick, William

2016-01-01

This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify…

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Racial bullying and adolescent substance use: An examination of school-attending young adolescents in the United States.

PubMed

Stone, Andrea L; Carlisle, Shauna K

2017-01-01

This article examines the association between race and racial bullying (bullying due to one's race), in relation to youth substance use in school attending young adolescents in the United States. Weighted unadjusted and adjusted logistic regression models were run to assess if racial bullying involvement was associated with youth substance use. Data for this study come from the Health Behaviors in School-Aged Children survey (n = 7,585). An association between racial bullying status (not involve, bullying victim, bullying perpetrator, or mixed bullying victim/perpetrator) and youth substance was identified in this study. Racial bully perpetrators were most likely to have used cigarettes, alcohol, and marijuana, followed by youth in the mixed victim/perpetrator group. When analyses were stratified by race, non-Hispanic White and Hispanic youth experienced an increased risk of cigarette, alcohol, and marijuana use if in the perpetrator or mixed group (compared to those not involved with racial bullying). Non-Hispanic White and Asian youth were also more likely to report marijuana use if in the victim group. Non-Hispanic Black youth were more likely to use alcohol and marijuana if they were a perpetrator or in the mixed group, but they were not more likely to use cigarettes. Differences appear to exist in relation to racial bullying experience and substance across racial/ethnic group among youth in grades 7-10. Implications for prevention and educational professionals are discussed.

Logistics in hospitals: a case study of some Singapore hospitals.

PubMed

Pan, Zhi Xiong; Pokharel, Shaligram

2007-01-01

The purpose of this paper is to investigate logistics activities in Singapore hospitals. It defines various types of activities handled by a logistics division. Inventory management policy and the use of information and communication technologies (ICT) for logistics purposes are also discussed. The study identifies the nature of strategic alliances in Singapore's health care industry. This study was conducted by utilizing a framework for data collection, pre-testing the questionnaire and conducting interviews. Various relevant literature was reviewed to design the questionnaire. This study finds that logistics division carry out many related activities and some of them also provide engineering services. The hospitals make use of ICT. The hospitals are clustered under various groups to minimize the cost of operation, including the logistics related costs. However, hospitals do not see alliances with suppliers as a strategic option; rather they focus on outsourcing of logistics services. The findings also show that Singapore hospitals have a good stocking policy for both medical and non-medical items so that changes in patient mix can be easily handled. Singapore is continuously improving its health care industry and therefore, the findings will help hospitals in other regions to adopt some of the practices, like concentrating on local vendors, outsourcing, clustering, and maximum use of information technology as competitive factors that can improve the service and reduce the cost of operation. The paper suggests motivators and barriers to the use of ICT in logistics in the health care industry.

IMPACT: Investigating the impact of Models of Practice for Allied health Care in subacuTe settings. A protocol for a quasi-experimental mixed methods study of cost effectiveness and outcomes for patients exposed to different models of allied health care.

PubMed

Coker, Freya; Williams, Cylie M; Taylor, Nicholas F; Caspers, Kirsten; McAlinden, Fiona; Wilton, Anita; Shields, Nora; Haines, Terry P

2018-05-10

This protocol considers three allied health staffing models across public health subacute hospitals. This quasi-experimental mixed-methods study, including qualitative process evaluation, aims to evaluate the impact of additional allied health services in subacute care, in rehabilitation and geriatric evaluation management settings, on patient, health service and societal outcomes. This health services research will analyse outcomes of patients exposed to different allied health models of care at three health services. Each health service will have a control ward (routine care) and an intervention ward (additional allied health). This project has two parts. Part 1: a whole of site data extraction for included wards. Outcome measures will include: length of stay, rate of readmissions, discharge destinations, community referrals, patient feedback and staff perspectives. Part 2: Functional Independence Measure scores will be collected every 2-3 days for the duration of 60 patient admissions.Data from part 1 will be analysed by linear regression analysis for continuous outcomes using patient-level data and logistic regression analysis for binary outcomes. Qualitative data will be analysed using a deductive thematic approach. For part 2, a linear mixed model analysis will be conducted using therapy service delivery and days since admission to subacute care as fixed factors in the model and individual participant as a random factor. Graphical analysis will be used to examine the growth curve of the model and transformations. The days since admission factor will be used to examine non-linear growth trajectories to determine if they lead to better model fit. Findings will be disseminated through local reports and to the Department of Health and Human Services Victoria. Results will be presented at conferences and submitted to peer-reviewed journals. The Monash Health Human Research Ethics committee approved this multisite research (HREC/17/MonH/144 and HREC/17/MonH/547). © 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.

Identification of different bacterial species in biofilms using confocal Raman microscopy

NASA Astrophysics Data System (ADS)

Beier, Brooke D.; Quivey, Robert G.; Berger, Andrew J.

2010-11-01

Confocal Raman microspectroscopy is used to discriminate between different species of bacteria grown in biofilms. Tests are performed using two bacterial species, Streptococcus sanguinis and Streptococcus mutans, which are major components of oral plaque and of particular interest due to their association with healthy and cariogenic plaque, respectively. Dehydrated biofilms of these species are studied as a simplified model of dental plaque. A prediction model based on principal component analysis and logistic regression is calibrated using pure biofilms of each species and validated on pure biofilms grown months later, achieving 96% accuracy in prospective classification. When biofilms of the two species are partially mixed together, Raman-based identifications are achieved within ~2 μm of the boundaries between species with 97% accuracy. This combination of spatial resolution and predication accuracy should be suitable for forming images of species distributions within intact two-species biofilms.

Estimating the Prevalence of Childhood Obesity in Alaska Using Partial, Nonrandom Measurement Data

PubMed Central

Boles, Myde; Fink, Karol; Topol, Rebecca; Fenaughty, Andrea

2016-01-01

Although monitoring childhood obesity prevalence is critical for state public health programs to assess trends and the effectiveness of interventions, few states have comprehensive body mass index measurement systems in place. In some states, however, assorted school districts collect measurements on student height and weight as part of annual health screenings. To estimate childhood obesity prevalence in Alaska, we created a logistic regression model using such annual measurements along with public data on demographics and socioeconomic status. Our mixed-effects model-generated prevalence estimates validated well against weighted estimates, with 95% confidence intervals overlapping between methodologies among 7 of 8 participating school districts. Our methodology accounts for variation in school-level and student-level demographic factors across the state, and the approach we describe can be applied by other states that have existing nonrandom student measurement data to estimate childhood obesity prevalence. PMID:27010843

Population analyses of efficacy and safety of ABT-594 in subjects with diabetic peripheral neuropathic pain.

PubMed

Dutta, Sandeep; Hosmane, Balakrishna S; Awni, Walid M

2012-06-01

ABT-594, a neuronal nicotinic acetylcholine receptor ligand, is 30- to 100-fold more potent than morphine in animal models of nociceptive and neuropathic pain. Efficacy and safety of ABT-594 in subjects with painful diabetic polyneuropathy was evaluated in a phase 2 study. The objective of this work was to use a nonlinear mixed effects model-based approach for characterizing the relationship between dose and response (efficacy and safety) of ABT-594. Subjects (N = 266) were randomized into four groups in a double-blind, placebo-controlled, 7-week study to receive twice daily regimens of placebo or 150, 225, and 300 μg of ABT-594. The primary efficacy variable, pain score (11-point Likert scale), was assessed on five occasions. The probability of change from baseline pain score of ≥1, ≥2, and ≥3 was modeled using cumulative logistic regression with dose and days of treatment as explanatory variables. The incidence of five most frequently occurring adverse events (AEs) was modeled using linear logistic regression. ABT-594 ED(50) values (improvement in 50% of subjects) for improvement in pain scores of ≥1, ≥2, and ≥3 were 50, 215, and 340 μg, respectively, for the average number of days (33) on treatment. The rank order of ED(50) values for AEs was nausea, vomiting, dizziness, headache, and abnormal dreams; nicotine users were less sensitive to AEs. Population pharmacodynamic models developed to characterize the improvement in pain score and incidence of adverse events indicate an approximately twofold separation between the ED(50) values for efficacy and AEs.

Metamodeling and the Critic-based approach to multi-level optimization.

PubMed

Werbos, Ludmilla; Kozma, Robert; Silva-Lugo, Rodrigo; Pazienza, Giovanni E; Werbos, Paul J

2012-08-01

Large-scale networks with hundreds of thousands of variables and constraints are becoming more and more common in logistics, communications, and distribution domains. Traditionally, the utility functions defined on such networks are optimized using some variation of Linear Programming, such as Mixed Integer Programming (MIP). Despite enormous progress both in hardware (multiprocessor systems and specialized processors) and software (Gurobi) we are reaching the limits of what these tools can handle in real time. Modern logistic problems, for example, call for expanding the problem both vertically (from one day up to several days) and horizontally (combining separate solution stages into an integrated model). The complexity of such integrated models calls for alternative methods of solution, such as Approximate Dynamic Programming (ADP), which provide a further increase in the performance necessary for the daily operation. In this paper, we present the theoretical basis and related experiments for solving the multistage decision problems based on the results obtained for shorter periods, as building blocks for the models and the solution, via Critic-Model-Action cycles, where various types of neural networks are combined with traditional MIP models in a unified optimization system. In this system architecture, fast and simple feed-forward networks are trained to reasonably initialize more complicated recurrent networks, which serve as approximators of the value function (Critic). The combination of interrelated neural networks and optimization modules allows for multiple queries for the same system, providing flexibility and optimizing performance for large-scale real-life problems. A MATLAB implementation of our solution procedure for a realistic set of data and constraints shows promising results, compared to the iterative MIP approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

Trajectories of Community-Based Service Use: The Importance of Poverty and Living Arrangements.

PubMed

Park, Sojung; Kim, BoRin; Kwon, Eunsun; Lee, Hyunjoo

2017-07-01

This study examined how older adults' living arrangements and poverty status affected their use of in-home health, functional, and out-of-home services over time. Using eight waves of data from the Korea Welfare Panel Study, we employed a logistic mixed-effect model to analyze how poverty and living arrangements affect community-based service use. Living-alone older adults and elder-only couples were more likely than co-residing households to use services. Elder-only couples, when poor, were more likely to use in-home and out-of-home services over time. Understanding predictors of community-based service use over time enables researchers and policymakers to better understand the process of aging-in-place.

Logistics in a low carbon concept: Connotation and realization way

NASA Astrophysics Data System (ADS)

Zheng, Chaocheng; Qiu, Xiaoying; Mao, Jiarong

2017-01-01

Low-carbon logistics has become a trend for the logistics industry-as a high-energy consumption industry, continuation of its previous operating mode has been significantly behind the times. So logistics industry must release lower carbon emissions. This paper sort out the literature home and abroad from three aspects, that is, the definition of low-carbon logistics, low-carbon logistics implementation mechanisms or measures, and low carbon design quantitative models. The research shows: low-carbon logistics needed to implemented both in enterprise' macro and micro level, which means the government should provide relevant policy support and micro enterprises should be actively sought from all sectors of the logistics in energy saving. In practice, low-carbon logistics optimization models are effective tools for enterprises to implement emission reduction.

An Empirical Model and Ethnic Differences in Cultural Meanings Via Motives for Suicide.

PubMed

Chu, Joyce; Khoury, Oula; Ma, Johnson; Bahn, Francesca; Bongar, Bruce; Goldblum, Peter

2017-10-01

The importance of cultural meanings via motives for suicide - what is considered acceptable to motivate suicide - has been advocated as a key step in understanding and preventing development of suicidal behaviors. There have been limited systematic empirical attempts to establish different cultural motives ascribed to suicide across ethnic groups. We used a mixed methods approach and grounded theory methodology to guide the analysis of qualitative data querying for meanings via motives for suicide among 232 Caucasians, Asian Americans, and Latino/a Americans with a history of suicide attempts, ideation, intent, or plan. We used subsequent logistic regression analyses to examine ethnic differences in suicide motive themes. This inductive approach of generating theory from data yielded an empirical model of 6 cultural meanings via motives for suicide themes: intrapersonal perceptions, intrapersonal emotions, intrapersonal behavior, interpersonal, mental health/medical, and external environment. Logistic regressions showed ethnic differences in intrapersonal perceptions (low endorsement by Latino/a Americans) and external environment (high endorsement by Latino/a Americans) categories. Results advance suicide research and practice by establishing 6 empirically based cultural motives for suicide themes that may represent a key intermediary step in the pathway toward suicidal behaviors. Clinicians can use these suicide meanings via motives to guide their assessment and determination of suicide risk. Emphasis on environmental stressors rather than negative perceptions like hopelessness should be considered with Latino/a clients. © 2017 Wiley Periodicals, Inc.

A breast health educational program for Chinese-American women: 3- to 12-month postintervention effect.

PubMed

Lee-Lin, Frances; Nguyen, Thuan; Pedhiwala, Nisreen; Dieckmann, Nathan; Menon, Usha

2015-01-01

To test the efficacy of a culturally targeted breast cancer screening educational program in increasing mammogram completion in Chinese-American immigrant women. Randomized controlled study. Chinese communities, Portland, Oregon. From April 2010 to September 2011, 300 women were randomized to receive a theory-based, culturally targeted breast cancer screening educational intervention (n = 147) or a mammography screening brochure published by the National Cancer Institute (n = 153). The two-part intervention consisted of group teaching with targeted, theory-based messages followed by individual counseling sessions. Mammography completion, perceived susceptibility, perceived benefits, perceived barriers, perceived cultural barriers, and demographic variables. A 2 × 3 mixed logistic model was applied to determine odds ratio of mammogram completion. Behavior changed in both groups, with a total of 170 participants (56.7%) reporting a mammogram at 12 months. The logistic model indicated increased odds of mammogram completion in the intervention compared to the control group at 3, 6, and 12 months. When controlling for marital status, age, and age moved to the United States, the intervention group was nine times more likely to complete mammograms than the control group. The culturally targeted educational program significantly increased mammogram use among Chinese immigrant women. Further testing of effectiveness in larger community settings is needed. The intervention may also serve as a foundation from which to develop education to increase cancer screening among other minority subgroups.

Did Rev-1 small ruminants vaccination helped improve cattle brucellosis prevalence status in Algeria?

PubMed

Kardjadj, Moustafa

2017-12-01

In 2006, the Algerian authorities started the Rev-1 vaccination of sheep and goats; consequently, there was a significant improvement of small ruminant brucellosis sanitary status. In this paper, we attempt to study the effect of Rev-1 small ruminants' vaccination on cattle brucellosis prevalence in Algeria. Our results showed an overall cattle herd seroprevalence of 12% (9 positive herds of 75). The risk factor analysis using a logistic regression model indicated that the presence of small ruminants along with cattle in the herd (mixed herds) decreased the odds for brucellosis seropositivity by 1.69 [95% CI 0.54-2.84; P = 0.042] compared to the cattle herds only. Likewise, the present study showed that the presence of Rev-1 vaccinated small ruminants in the herd decreased also the odds for brucellosis seropositivity by 4.10 [95% CI 3.20-5.00; P = 0.003] compared to other herds. This result lead to the assumption that the small ruminants Rev-1 vaccination diminish Brucella microbisme pressure in the mixed herds and help decrease the cattle brucellosis prevalence in these herds.

Analyzing Student Learning Outcomes: Usefulness of Logistic and Cox Regression Models. IR Applications, Volume 5

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2005-01-01

Logistic and Cox regression methods are practical tools used to model the relationships between certain student learning outcomes and their relevant explanatory variables. The logistic regression model fits an S-shaped curve into a binary outcome with data points of zero and one. The Cox regression model allows investigators to study the duration…

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.

Should metacognition be measured by logistic regression?

PubMed

Rausch, Manuel; Zehetleitner, Michael

2017-03-01

Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.

Injury profiles related to mortality in patients with a low Injury Severity Score: a case-mix issue?

PubMed

Joosse, Pieter; Schep, Niels W L; Goslings, J Carel

2012-07-01

Outcome prediction models are widely used to evaluate trauma care. External benchmarking provides individual institutions with a tool to compare survival with a reference dataset. However, these models do have limitations. In this study, the hypothesis was tested whether specific injuries are associated with increased mortality and whether differences in case-mix of these injuries influence outcome comparison. A retrospective study was conducted in a Dutch trauma region. Injury profiles, based on injuries most frequently endured by unexpected death, were determined. The association between these injury profiles and mortality was studied in patients with a low Injury Severity Score by logistic regression. The standardized survival of our population (Ws statistic) was compared with North-American and British reference databases, with and without patients suffering from previously defined injury profiles. In total, 14,811 patients were included. Hip fractures, minor pelvic fractures, femur fractures, and minor thoracic injuries were significantly associated with mortality corrected for age, sex, and physiologic derangement in patients with a low injury severity. Odds ratios ranged from 2.42 to 2.92. The Ws statistic for comparison with North-American databases significantly improved after exclusion of patients with these injuries. The Ws statistic for comparison with a British reference database remained unchanged. Hip fractures, minor pelvic fractures, femur fractures, and minor thoracic wall injuries are associated with increased mortality. Comparative outcome analysis of a population with a reference database that differs in case-mix with respect to these injuries should be interpreted cautiously. Prognostic study, level II.

Routine Laboratory Blood Tests May Diagnose Significant Fibrosis in Liver Transplant Recipients with Chronic Hepatitis C: A 10 Year Experience.

PubMed

Sheen, Victoria; Nguyen, Heajung; Jimenez, Melissa; Agopian, Vatche; Vangala, Sitaram; Elashoff, David; Saab, Sammy

2016-03-28

The aims of our study were to determine whether routine blood tests, the aspartate aminotransferase (AST) to Platelet Ratio Index (APRI) and Fibrosis 4 (Fib-4) scores, were associated with advanced fibrosis and to create a novel model in liver transplant recipients with chronic hepatitis C virus (HCV). We performed a cross sectional study of patients at The University of California at Los Angeles (UCLA) Medical Center who underwent liver transplantation for HCV. We used linear mixed effects models to analyze association between fibrosis severity and individual biochemical markers and mixed effects logistic regression to construct diagnostic models for advanced fibrosis (METAVIR F3-4). Cross-validation was used to estimate a receiving operator characteristic (ROC) curve for the prediction models and to estimate the area under the curve (AUC). The mean (± standard deviation [SD]) age of our cohort was 55 (±7.7) years, and almost three quarter were male. The mean (±SD) time from transplant to liver biopsy was 19.9 (±17.1) months. The mean (±SD) APRI and Fib-4 scores were 3 (±12) and 7 (±14), respectively. Increased fibrosis was associated with lower platelet count and alanine aminotransferase (ALT) values and higher total bilirubin and Fib-4 scores. We developed a model that takes into account age, gender, platelet count, ALT, and total bilirubin, and this model outperformed APRI and Fib-4 with an AUC of 0.68 (p < 0.001). Our novel prediction model diagnosed the presence of advanced fibrosis more reliably than APRI and Fib-4 scores. This noninvasive calculation may be used clinically to identify liver transplant recipients with HCV with significant liver damage.

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.

The New York Sepsis Severity Score: Development of a Risk-Adjusted Severity Model for Sepsis.

PubMed

Phillips, Gary S; Osborn, Tiffany M; Terry, Kathleen M; Gesten, Foster; Levy, Mitchell M; Lemeshow, Stanley

2018-05-01

In accordance with Rory's Regulations, hospitals across New York State developed and implemented protocols for sepsis recognition and treatment to reduce variations in evidence informed care and preventable mortality. The New York Department of Health sought to develop a risk assessment model for accurate and standardized hospital mortality comparisons of adult septic patients across institutions using case-mix adjustment. Retrospective evaluation of prospectively collected data. Data from 43,204 severe sepsis and septic shock patients from 179 hospitals across New York State were evaluated. Prospective data were submitted to a database from January 1, 2015, to December 31, 2015. None. Maximum likelihood logistic regression was used to estimate model coefficients used in the New York State risk model. The mortality probability was estimated using a logistic regression model. Variables to be included in the model were determined as part of the model-building process. Interactions between variables were included if they made clinical sense and if their p values were less than 0.05. Model development used a random sample of 90% of available patients and was validated using the remaining 10%. Hosmer-Lemeshow goodness of fit p values were considerably greater than 0.05, suggesting good calibration. Areas under the receiver operator curve in the developmental and validation subsets were 0.770 (95% CI, 0.765-0.775) and 0.773 (95% CI, 0.758-0.787), respectively, indicating good discrimination. Development and validation datasets had similar distributions of estimated mortality probabilities. Mortality increased with rising age, comorbidities, and lactate. The New York Sepsis Severity Score accurately estimated the probability of hospital mortality in severe sepsis and septic shock patients. It performed well with respect to calibration and discrimination. This sepsis-specific model provides an accurate, comprehensive method for standardized mortality comparison of adult patients with severe sepsis and septic shock.

A Note on the Item Information Function of the Four-Parameter Logistic Model

ERIC Educational Resources Information Center

Magis, David

2013-01-01

This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…

Conventional, Hybrid, or Electric Vehicles: Which Technology for an Urban Distribution Centre?

PubMed Central

Lebeau, Philippe; De Cauwer, Cedric; Macharis, Cathy; Verbeke, Wouter; Coosemans, Thierry

2015-01-01

Freight transport has an important impact on urban welfare. It is estimated to be responsible for 25% of CO2 emissions and up to 50% of particles matters generated by the transport sector in cities. Facing that problem, the European Commission set the objective of reaching free CO2 city logistics by 2030 in major urban areas. In order to achieve this goal, electric vehicles could be an important part of the solution. However, this technology still faces a number of barriers, in particular high purchase costs and limited driving range. This paper explores the possible integration of electric vehicles in urban logistics operations. In order to answer this research question, the authors have developed a fleet size and mix vehicle routing problem with time windows for electric vehicles. In particular, an energy consumption model is integrated in order to consider variable range of electric vehicles. Based on generated instances, the authors analyse different sets of vehicles in terms of vehicle class (quadricycles, small vans, large vans, and trucks) and vehicle technology (petrol, hybrid, diesel, and electric vehicles). Results show that a fleet with different technologies has the opportunity of reducing costs of the last mile. PMID:26236769

Conventional, Hybrid, or Electric Vehicles: Which Technology for an Urban Distribution Centre?

PubMed

Lebeau, Philippe; De Cauwer, Cedric; Van Mierlo, Joeri; Macharis, Cathy; Verbeke, Wouter; Coosemans, Thierry

2015-01-01

Freight transport has an important impact on urban welfare. It is estimated to be responsible for 25% of CO2 emissions and up to 50% of particles matters generated by the transport sector in cities. Facing that problem, the European Commission set the objective of reaching free CO2 city logistics by 2030 in major urban areas. In order to achieve this goal, electric vehicles could be an important part of the solution. However, this technology still faces a number of barriers, in particular high purchase costs and limited driving range. This paper explores the possible integration of electric vehicles in urban logistics operations. In order to answer this research question, the authors have developed a fleet size and mix vehicle routing problem with time windows for electric vehicles. In particular, an energy consumption model is integrated in order to consider variable range of electric vehicles. Based on generated instances, the authors analyse different sets of vehicles in terms of vehicle class (quadricycles, small vans, large vans, and trucks) and vehicle technology (petrol, hybrid, diesel, and electric vehicles). Results show that a fleet with different technologies has the opportunity of reducing costs of the last mile.

Association between developmental enamel defects in the primary and permanent dentitions.

PubMed

Casanova-Rosado, A J; Medina-Solís, C E; Casanova-Rosado, J F; Vallejos-Sánchez, A A; Martinez-Mier, E A; Loyola-Rodríguez, J P; Islas-Márquez, A J; Maupomé, G

2011-09-01

To determine if the presence of developmental enamel defects (DED) in the primary dentition is a risk indicator for the presence of DED in the permanent dentition in children with mixed dentition, as well as others factors. A cross-sectional study was undertaken in 1296 school children ages six to 72 years. The DED [FDI; 1982] in both dentitions were identified by means of an oral exam scoring enamel opacities [classified as demarcated or diffused], and enamel hypoplasia. Sociodemographic and socioeconomic variables were collected through a questionnaire. Socioeconomic status (SES) was determined based on the occupation and maximum level of education of parents. Statistical analysis included logistic regression. Mean age of participants was 8.40 +/- 1.68; 51.6% were boys. DED prevalence was 7.5% in the permanent dentition and 10.0% in the primary dentition. The logistic regression model, adjusting for sociodemographic and socioeconomic variables, showed that for each primary tooth with DED, the odds of observing DED in the permanent dentition increased 7.38 times [95% CI = 1.17-1.64; p < 0.001]. An association between DED presence in both permanent and primary dentitions was observed. Further studies are necessary to fully characterise such relationship.

No compelling positive association between ovarian hormones and wearing red clothing when using multinomial analyses.

PubMed

Blake, Khandis R; Dixson, Barnaby J W; O'Dean, Siobhan M; Denson, Thomas F

2017-04-01

Several studies report that wearing red clothing enhances women's attractiveness and signals sexual proceptivity to men. The associated hypothesis that women will choose to wear red clothing when fertility is highest, however, has received mixed support from empirical studies. One possible cause of these mixed findings may be methodological. The current study aimed to replicate recent findings suggesting a positive association between hormonal profiles associated with high fertility (high estradiol to progesterone ratios) and the likelihood of wearing red. We compared the effect of the estradiol to progesterone ratio on the probability of wearing: red versus non-red (binary logistic regression); red versus neutral, black, blue, green, orange, multi-color, and gray (multinomial logistic regression); and each of these same colors in separate binary models (e.g., green versus non-green). Red versus non-red analyses showed a positive trend between a high estradiol to progesterone ratio and wearing red, but the effect only arose for younger women and was not robust across samples. We found no compelling evidence for ovarian hormones increasing the probability of wearing red in the other analyses. However, we did find that the probability of wearing neutral was positively associated with the estradiol to progesterone ratio, though the effect did not reach conventional levels of statistical significance. Findings suggest that although ovarian hormones may affect younger women's preference for red clothing under some conditions, the effect is not robust when differentiating amongst other colors of clothing. In addition, the effect of ovarian hormones on clothing color preference may not be specific to the color red. Copyright © 2017 Elsevier Inc. All rights reserved.

Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials.

PubMed

Theofilatos, Athanasios

2017-06-01

The effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece. Random Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively. Regarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity. The study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms. The identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials. Copyright © 2017 Elsevier Ltd and National Safety Council. All rights reserved.

Logistic regression models of factors influencing the location of bioenergy and biofuels plants

Treesearch

T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu

2011-01-01

Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...

Maximal bite force, facial morphology and sucking habits in young children with functional posterior crossbite

PubMed Central

CASTELO, Paula Midori; GAVIÃO, Maria Beatriz Duarte; PEREIRA, Luciano José; BONJARDIM, Leonardo Rigoldi

2010-01-01

Objective The maintenance of normal conditions of the masticatory function is determinant for the correct growth and development of its structures. Thus, the aims of this study were to evaluate the influence of sucking habits on the presence of crossbite and its relationship with maximal bite force, facial morphology and body variables in 67 children of both genders (3.5-7 years) with primary or early mixed dentition. Material and methods The children were divided in four groups: primary-normocclusion (PN, n=19), primary-crossbite (PC, n=19), mixed-normocclusion (MN, n=13), and mixed-crossbite (MC, n=16). Bite force was measured with a pressurized tube, and facial morphology was determined by standardized frontal photographs: AFH (anterior face height) and BFW (bizygomatic facial width). Results It was observed that MC group showed lower bite force than MN, and AFH/ BFW was significantly smaller in PN than PC (t-test). Weight and height were only significantly correlated with bite force in PC group (Pearson’s correlation test). In the primary dentition, AFH/BFW and breast-feeding (at least six months) were positive and negatively associated with crossbite, respectively (multiple logistic regression). In the mixed dentition, breastfeeding and bite force showed negative associations with crossbite (univariate regression), while nonnutritive sucking (up to 3 years) associated significantly with crossbite in all groups (multiple logistic regression). Conclusions In the studied sample, sucking habits played an important role in the etiology of crossbite, which was associated with lower bite force and long-face tendency. PMID:20485925

FITPOP, a heuristic simulation model of population dynamics and genetics with special reference to fisheries

USGS Publications Warehouse

McKenna, James E.

2000-01-01

Although, perceiving genetic differences and their effects on fish population dynamics is difficult, simulation models offer a means to explore and illustrate these effects. I partitioned the intrinsic rate of increase parameter of a simple logistic-competition model into three components, allowing specification of effects of relative differences in fitness and mortality, as well as finite rate of increase. This model was placed into an interactive, stochastic environment to allow easy manipulation of model parameters (FITPOP). Simulation results illustrated the effects of subtle differences in genetic and population parameters on total population size, overall fitness, and sensitivity of the system to variability. Several consequences of mixing genetically distinct populations were illustrated. For example, behaviors such as depression of population size after initial introgression and extirpation of native stocks due to continuous stocking of genetically inferior fish were reproduced. It also was shown that carrying capacity relative to the amount of stocking had an important influence on population dynamics. Uncertainty associated with parameter estimates reduced confidence in model projections. The FITPOP model provided a simple tool to explore population dynamics, which may assist in formulating management strategies and identifying research needs.

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.

Using phenomenological models for forecasting the 2015 Ebola challenge.

PubMed

Pell, Bruce; Kuang, Yang; Viboud, Cecile; Chowell, Gerardo

2018-03-01

The rising number of novel pathogens threatening the human population has motivated the application of mathematical modeling for forecasting the trajectory and size of epidemics. We summarize the real-time forecasting results of the logistic equation during the 2015 Ebola challenge focused on predicting synthetic data derived from a detailed individual-based model of Ebola transmission dynamics and control. We also carry out a post-challenge comparison of two simple phenomenological models. In particular, we systematically compare the logistic growth model and a recently introduced generalized Richards model (GRM) that captures a range of early epidemic growth profiles ranging from sub-exponential to exponential growth. Specifically, we assess the performance of each model for estimating the reproduction number, generate short-term forecasts of the epidemic trajectory, and predict the final epidemic size. During the challenge the logistic equation consistently underestimated the final epidemic size, peak timing and the number of cases at peak timing with an average mean absolute percentage error (MAPE) of 0.49, 0.36 and 0.40, respectively. Post-challenge, the GRM which has the flexibility to reproduce a range of epidemic growth profiles ranging from early sub-exponential to exponential growth dynamics outperformed the logistic growth model in ascertaining the final epidemic size as more incidence data was made available, while the logistic model underestimated the final epidemic even with an increasing amount of data of the evolving epidemic. Incidence forecasts provided by the generalized Richards model performed better across all scenarios and time points than the logistic growth model with mean RMS decreasing from 78.00 (logistic) to 60.80 (GRM). Both models provided reasonable predictions of the effective reproduction number, but the GRM slightly outperformed the logistic growth model with a MAPE of 0.08 compared to 0.10, averaged across all scenarios and time points. Our findings further support the consideration of transmission models that incorporate flexible early epidemic growth profiles in the forecasting toolkit. Such models are particularly useful for quickly evaluating a developing infectious disease outbreak using only case incidence time series of the early phase of an infectious disease outbreak. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Predicting 30-day Hospital Readmission with Publicly Available Administrative Database. A Conditional Logistic Regression Modeling Approach.

PubMed

Zhu, K; Lou, Z; Zhou, J; Ballester, N; Kong, N; Parikh, P

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Hospital readmissions raise healthcare costs and cause significant distress to providers and patients. It is, therefore, of great interest to healthcare organizations to predict what patients are at risk to be readmitted to their hospitals. However, current logistic regression based risk prediction models have limited prediction power when applied to hospital administrative data. Meanwhile, although decision trees and random forests have been applied, they tend to be too complex to understand among the hospital practitioners. Explore the use of conditional logistic regression to increase the prediction accuracy. We analyzed an HCUP statewide inpatient discharge record dataset, which includes patient demographics, clinical and care utilization data from California. We extracted records of heart failure Medicare beneficiaries who had inpatient experience during an 11-month period. We corrected the data imbalance issue with under-sampling. In our study, we first applied standard logistic regression and decision tree to obtain influential variables and derive practically meaning decision rules. We then stratified the original data set accordingly and applied logistic regression on each data stratum. We further explored the effect of interacting variables in the logistic regression modeling. We conducted cross validation to assess the overall prediction performance of conditional logistic regression (CLR) and compared it with standard classification models. The developed CLR models outperformed several standard classification models (e.g., straightforward logistic regression, stepwise logistic regression, random forest, support vector machine). For example, the best CLR model improved the classification accuracy by nearly 20% over the straightforward logistic regression model. Furthermore, the developed CLR models tend to achieve better sensitivity of more than 10% over the standard classification models, which can be translated to correct labeling of additional 400 - 500 readmissions for heart failure patients in the state of California over a year. Lastly, several key predictor identified from the HCUP data include the disposition location from discharge, the number of chronic conditions, and the number of acute procedures. It would be beneficial to apply simple decision rules obtained from the decision tree in an ad-hoc manner to guide the cohort stratification. It could be potentially beneficial to explore the effect of pairwise interactions between influential predictors when building the logistic regression models for different data strata. Judicious use of the ad-hoc CLR models developed offers insights into future development of prediction models for hospital readmissions, which can lead to better intuition in identifying high-risk patients and developing effective post-discharge care strategies. Lastly, this paper is expected to raise the awareness of collecting data on additional markers and developing necessary database infrastructure for larger-scale exploratory studies on readmission risk prediction.

Logistic regression for dichotomized counts.

PubMed

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

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

A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

Treesearch

Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen Fitzgerald

2012-01-01

Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

Differentially private distributed logistic regression using private and public data.

PubMed

Ji, Zhanglong; Jiang, Xiaoqian; Wang, Shuang; Xiong, Li; Ohno-Machado, Lucila

2014-01-01

Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods sometimes introduce too much noise and make outputs less useful. Given available public data in medical research (e.g. from patients who sign open-consent agreements), we can design algorithms that use both public and private data sets to decrease the amount of noise that is introduced. In this paper, we modify the update step in Newton-Raphson method to propose a differentially private distributed logistic regression model based on both public and private data. We try our algorithm on three different data sets, and show its advantage over: (1) a logistic regression model based solely on public data, and (2) a differentially private distributed logistic regression model based on private data under various scenarios. Logistic regression models built with our new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee.

Carbon emissions, logistics volume and GDP in China: empirical analysis based on panel data model.

PubMed

Guo, Xiaopeng; Ren, Dongfang; Shi, Jiaxing

2016-12-01

This paper studies the relationship among carbon emissions, GDP, and logistics by using a panel data model and a combination of statistics and econometrics theory. The model is based on the historical data of 10 typical provinces and cities in China during 2005-2014. The model in this paper adds the variability of logistics on the basis of previous studies, and this variable is replaced by the freight turnover of the provinces. Carbon emissions are calculated by using the annual consumption of coal, oil, and natural gas. GDP is the gross domestic product. The results showed that the amount of logistics and GDP have a contribution to carbon emissions and the long-term relationships are different between different cities in China, mainly influenced by the difference among development mode, economic structure, and level of logistic development. After the testing of panel model setting, this paper established a variable coefficient model of the panel. The influence of GDP and logistics on carbon emissions is obtained according to the influence factors among the variables. The paper concludes with main findings and provides recommendations toward rational planning of urban sustainable development and environmental protection for China.

Associations between physical activity parenting practices and adolescent girls' self-perceptions and physical activity intentions.

PubMed

Sebire, Simon J; Haase, Anne M; Montgomery, Alan A; McNeill, Jade; Jago, Russ

2014-05-01

The current study investigated cross-sectional associations between maternal and paternal logistic and modeling physical activity support and the self-efficacy, self-esteem, and physical activity intentions of 11- to 12-year-old girls. 210 girls reported perceptions of maternal and paternal logistic and modeling support and their self-efficacy, self-esteem and intention to be physically active. Data were analyzed using multivariable regression models. Maternal logistic support was positively associated with participants' self-esteem, physical activity self-efficacy, and intention to be active. Maternal modeling was positively associated with self-efficacy. Paternal modeling was positively associated with self-esteem and self-efficacy but there was no evidence that paternal logistic support was associated with the psychosocial variables. Activity-related parenting practices were associated with psychosocial correlates of physical activity among adolescent girls. Logistic support from mothers, rather than modeling support or paternal support may be a particularly important target when designing interventions aimed at preventing the age-related decline in physical activity among girls.

Effects of impairment in activities of daily living on predicting mortality following hip fracture surgery in studies using administrative healthcare databases

PubMed Central

2014-01-01

Background Impairment in activities of daily living (ADL) is an important predictor of outcomes although many administrative databases lack information on ADL function. We evaluated the impact of ADL function on predicting postoperative mortality among older adults with hip fractures in Ontario, Canada. Methods Sociodemographic and medical correlates of ADL impairment were first identified in a population of older adults with hip fractures who had ADL information available prior to hip fracture. A logistic regression model was developed to predict 360-day postoperative mortality and the predictive ability of this model were compared when ADL impairment was included or omitted from the model. Results The study sample (N = 1,329) had a mean age of 85.2 years, were 72.8% female and the majority resided in long-term care (78.5%). Overall, 36.4% of individuals died within 360 days of surgery. After controlling for age, sex, medical comorbidity and medical conditions correlated with ADL impairment, addition of ADL measures improved the logistic regression model for predicting 360 day mortality (AIC = 1706.9 vs. 1695.0; c -statistic = 0.65 vs 0.67; difference in - 2 log likelihood ratios: χ2 = 16.9, p = 0.002). Conclusions Direct measures of ADL impairment provides additional prognostic information on mortality for older adults with hip fractures even after controlling for medical comorbidity. Observational studies using administrative databases without measures of ADLs may be potentially prone to confounding and bias and case-mix adjustment for hip fracture outcomes should include ADL measures where these are available. PMID:24472282

Regional Logistics Information Resources Integration Patterns and Countermeasures

NASA Astrophysics Data System (ADS)

Wu, Hui; Shangguan, Xu-ming

Effective integration of regional logistics information resources can provide collaborative services in information flow, business flow and logistics for regional logistics enterprises, which also can reduce operating costs and improve market responsiveness. First, this paper analyzes the realistic significance on the integration of regional logistics information. Second, this paper brings forward three feasible patterns on the integration of regional logistics information resources, These three models have their own strengths and the scope of application and implementation, which model is selected will depend on the specific business and the regional distribution of enterprises. Last, this paper discusses the related countermeasures on the integration of regional logistics information resources, because the integration of regional logistics information is a systems engineering, when the integration is advancing, the countermeasures should pay close attention to the current needs and long-term development of regional enterprises.

Materialist and post-materialist values and cannabis smoking among young adults: a population-based study in southern Sweden.

PubMed

Lindström, Martin

2007-04-01

The association between materialist, mixed and post-materialist values, and the experience of cannabis smoking among young adults was investigated. The 2004 public health survey in Skåne, southern Sweden, is a cross-sectional study with a 59% response rate. The 6787 persons aged 18-34 years included in this study answered a postal questionnaire. A logistic regression model was used to investigate the association between materialist, mixed and post-materialist values and ever having experienced cannabis smoking. The multivariate analysis was performed to investigate the importance of possible confounders (age and education) on the differences in ever having experienced cannabis smoking according to materialist, mixed and post-materialist values. 28% of the men and 17% of the women had ever experienced cannabis smoking. The experience of cannabis smoking was significantly and positively associated with post-materialist values among both men and women. The odds ratios were 2.4 (1.8-3.1) for men with post-materialist values compared to men with materialist values, and 3.1 (2.4-4.0) for women with post-materialist values compared to women with materialist values. This study suggests that post-materialist values are positively associated with the risk of ever smoking cannabis. Because this is a cross-sectional study, the direction of causality remains to be investigated.

Comparing two basic subtypes in OCD across three large community samples: a pure compulsive versus a mixed obsessive-compulsive subtype.

PubMed

Rodgers, Stephanie; Ajdacic-Gross, Vladeta; Kawohl, Wolfram; Müller, Mario; Rössler, Wulf; Hengartner, Michael P; Castelao, Enrique; Vandeleur, Caroline; Angst, Jules; Preisig, Martin

2015-12-01

Due to its heterogeneous phenomenology, obsessive-compulsive disorder (OCD) has been subtyped. However, these subtypes are not mutually exclusive. This study presents an alternative subtyping approach by deriving non-overlapping OCD subtypes. A pure compulsive and a mixed obsessive-compulsive subtype (including subjects manifesting obsessions with/without compulsions) were analyzed with respect to a broad pattern of psychosocial risk factors and comorbid syndromes/diagnoses in three representative Swiss community samples: the Zurich Study (n = 591), the ZInEP sample (n = 1500), and the PsyCoLaus sample (n = 3720). A selection of comorbidities was examined in a pooled database. Odds ratios were derived from logistic regressions and, in the analysis of pooled data, multilevel models. The pure compulsive subtype showed a lower age of onset and was characterized by few associations with psychosocial risk factors. The higher social popularity of the pure compulsive subjects and their families was remarkable. Comorbidities within the pure compulsive subtype were mainly restricted to phobias. In contrast, the mixed obsessive-compulsive subtype had a higher prevalence and was associated with various childhood adversities, more familial burden, and numerous comorbid disorders, including disorders characterized by high impulsivity. The current comparison study across three representative community surveys presented two basic, distinct OCD subtypes associated with differing psychosocial impairment. Such highly specific subtypes offer the opportunity to learn about pathophysiological mechanisms specifically involved in OCD.

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

Examining Factors Influencing Attrition at a Small, Private, Selective Liberal Arts College

ERIC Educational Resources Information Center

Gansemer-Topf, Ann M.; Zhang, Yi; Beatty, Cameron C.; Paja, Scott

2014-01-01

Despite a diverse body of literature on college student retention, studies focusing on small, private, selective liberal arts colleges are limited. This study utilized a mixed methodology beginning with logistic regression analyses and followed with a qualitative inquiry that included interviews with students who had not persisted. While variables…

Movement of Fuel Ashore: Storage, Capacity, Throughput, and Distribution Analysis

DTIC Science & Technology

2015-12-01

89  ix LIST OF FIGURES Figure 1.  Principles of Operational Maneuver from the Sea ........................... 7  Figure 2.  Compositing and...30  Table 2.  Force Mix Composition ...procedures, and force composition . Such alterations represent an acceptance of operational risk to buy down the foundational risk that the logistics network

An investigation of the predictors of photoprotection and UVR dose to the face in patients with XP: a protocol using observational mixed methods.

PubMed

Walburn, Jessica; Sarkany, Robert; Norton, Sam; Foster, Lesley; Morgan, Myfanwy; Sainsbury, Kirby; Araújo-Soares, Vera; Anderson, Rebecca; Garrood, Isabel; Heydenreich, Jakob; Sniehotta, Falko F; Vieira, Rute; Wulf, Hans Christian; Weinman, John

2017-08-21

Xeroderma pigmentosum (XP) is a rare genetic condition caused by defective nucleotide excision repair and characterised by skin cancer, ocular and neurological involvement. Stringent ultraviolet protection is the only way to prevent skin cancer. Despite the risks, some patients' photoprotection is poor, with a potentially devastating impact on their prognosis. The aim of this research is to identify disease-specific and psychosocial predictors of photoprotection behaviour and ultraviolet radiation (UVR) dose to the face. Mixed methods research based on 45 UK patients will involve qualitative interviews to identify individuals' experience of XP and the influences on their photoprotection behaviours and a cross-sectional quantitative survey to assess biopsychosocial correlates of these behaviours at baseline. This will be followed by objective measurement of UVR exposure for 21 days by wrist-worn dosimeter and daily recording of photoprotection behaviours and psychological variables for up to 50 days in the summer months. This novel methodology will enable UVR dose reaching the face to be calculated and analysed as a clinically relevant endpoint. A range of qualitative and quantitative analytical approaches will be used, reflecting the mixed methods (eg, cross-sectional qualitative interviews, n-of-1 studies). Framework analysis will be used to analyse the qualitative interviews; mixed-effects longitudinal models will be used to examine the association of clinical and psychosocial factors with the average daily UVR dose; dynamic logistic regression models will be used to investigate participant-specific psychosocial factors associated with photoprotection behaviours. This research has been approved by Camden and King's Cross Research Ethics Committee 15/LO/1395. The findings will be published in peer-reviewed journals and presented at national and international scientific conferences. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Understanding the Essential Meaning of Measured Changes in Weight and Body Composition Among Women During and After Adjuvant Treatment for Breast Cancer: A Mixed-Methods Study.

PubMed

Pedersen, Birgith; Groenkjaer, Mette; Falkmer, Ursula; Delmar, Charlotte

Changes in weight and body composition among women during and after adjuvant antineoplastic treatment for breast cancer may influence long-term survival and quality of life. Research on factual weight changes is diverse and contrasting, and their influence on women's perception of body and self seems to be insufficiently explored. The aim of this study was to expand the understanding of the association between changes in weight and body composition and the women's perception of body and selves. A mixed-methods research design was used. Data consisted of weight and body composition measures from 95 women with breast cancer during 18 months past surgery. Twelve women from this cohort were interviewed individually at 12 months. Linear mixed model and logistic regression were used to estimate changes of repeated measures and odds ratio. Interviews were analyzed guided by existential phenomenology. Joint displays and integrative mixed-methods interpretation demonstrated that even small weight gains, extended waist, and weight loss were associated with fearing recurrence of breast cancer. Perceiving an ambiguous transforming body, the women moved between a unified body subject and the body as an object dissociated in "I" and "it" while fighting against or accepting the body changes. Integrating findings demonstrated that factual weight changes do not correspond with the perceived changes and may trigger existential threats. Transition to a new habitual body demand health practitioners to enter a joint narrative work to reveal how the changes impact on the women's body and self-perception independent of how they are displayed quantitatively.

Is pacemaker therapy the right key to patients with vasovagal syncope?

PubMed

Radovanović, Nikola N; Kirćanski, Bratislav; Raspopović, Srdjan; Pavlović, Siniša U; Jovanović, Velibor; Milašinović, Goran

2016-01-01

Vasovagal syncope is the most common type of reflex syncope. Efficacy of cardiac pacing in this indication has not been the subject of many studies and pacemaker therapy in patients with vasovagal syncope is still controversial. This study aimed to assess the efficacy and safety of pacing therapy in treatment of patients with vasovagal syncope, to determine contribution of new therapeutic models in increasing its success, and to identify risk factors associated with a higher rate of symptoms after pacemaker implantation. A retrospective study included 30 patients with pacemaker implanted due to vasovagal syncope in the Pacemaker Center, Clinical Center of Serbia, between November 2003 and June 2014. Head-up tilt test was performed to diagnose vasovagal syncope. Patients with cardioinhibitory and mixed type of disease were enrolled in the study. Mean age was 48.1 ± 11.1 years and 18 (60%) patients were men. Mean follow-up period was 5.9 ± 3.0 years. Primarily, implantable loop recorder was implanted in 10 (33.3%) patients. Twenty (66.7%) patients presented cardioinhibitory and 10 (33.3%) mixed type of vasovagal syncope. After pacemaker implantation, 11 (36.7%) patients had syncope. In multiple logistic regression analysis we showed that syncope is statistically more likely to occur after pacemaker implantation in patients with mixed type of vasovagal syncope (p = 0.018). There were two (6.7%) perioperative surgical complications. Pacemaker therapy is a safe treatment for patients with vasovagal syncope, whose efficacy can be improved by strict selection of patients. We showed that symptoms occur statistically more often in patients with mixed type of disease after pacemaker implantation.

Development and Validation of an Empiric Tool to Predict Favorable Neurologic Outcomes Among PICU Patients.

PubMed

Gupta, Punkaj; Rettiganti, Mallikarjuna; Gossett, Jeffrey M; Daufeldt, Jennifer; Rice, Tom B; Wetzel, Randall C

2018-01-01

To create a novel tool to predict favorable neurologic outcomes during ICU stay among children with critical illness. Logistic regression models using adaptive lasso methodology were used to identify independent factors associated with favorable neurologic outcomes. A mixed effects logistic regression model was used to create the final prediction model including all predictors selected from the lasso model. Model validation was performed using a 10-fold internal cross-validation approach. Virtual Pediatric Systems (VPS, LLC, Los Angeles, CA) database. Patients less than 18 years old admitted to one of the participating ICUs in the Virtual Pediatric Systems database were included (2009-2015). None. A total of 160,570 patients from 90 hospitals qualified for inclusion. Of these, 1,675 patients (1.04%) were associated with a decline in Pediatric Cerebral Performance Category scale by at least 2 between ICU admission and ICU discharge (unfavorable neurologic outcome). The independent factors associated with unfavorable neurologic outcome included higher weight at ICU admission, higher Pediatric Index of Morality-2 score at ICU admission, cardiac arrest, stroke, seizures, head/nonhead trauma, use of conventional mechanical ventilation and high-frequency oscillatory ventilation, prolonged hospital length of ICU stay, and prolonged use of mechanical ventilation. The presence of chromosomal anomaly, cardiac surgery, and utilization of nitric oxide were associated with favorable neurologic outcome. The final online prediction tool can be accessed at https://soipredictiontool.shinyapps.io/GNOScore/. Our model predicted 139,688 patients with favorable neurologic outcomes in an internal validation sample when the observed number of patients with favorable neurologic outcomes was among 139,591 patients. The area under the receiver operating curve for the validation model was 0.90. This proposed prediction tool encompasses 20 risk factors into one probability to predict favorable neurologic outcome during ICU stay among children with critical illness. Future studies should seek external validation and improved discrimination of this prediction tool.

The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model.

PubMed

Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei

2017-06-01

We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers.

An appraisal of convergence failures in the application of logistic regression model in published manuscripts.

PubMed

Yusuf, O B; Bamgboye, E A; Afolabi, R F; Shodimu, M A

2014-09-01

Logistic regression model is widely used in health research for description and predictive purposes. Unfortunately, most researchers are sometimes not aware that the underlying principles of the techniques have failed when the algorithm for maximum likelihood does not converge. Young researchers particularly postgraduate students may not know why separation problem whether quasi or complete occurs, how to identify it and how to fix it. This study was designed to critically evaluate convergence issues in articles that employed logistic regression analysis published in an African Journal of Medicine and medical sciences between 2004 and 2013. Problems of quasi or complete separation were described and were illustrated with the National Demographic and Health Survey dataset. A critical evaluation of articles that employed logistic regression was conducted. A total of 581 articles was reviewed, of which 40 (6.9%) used binary logistic regression. Twenty-four (60.0%) stated the use of logistic regression model in the methodology while none of the articles assessed model fit. Only 3 (12.5%) properly described the procedures. Of the 40 that used the logistic regression model, the problem of convergence occurred in 6 (15.0%) of the articles. Logistic regression tends to be poorly reported in studies published between 2004 and 2013. Our findings showed that the procedure may not be well understood by researchers since very few described the process in their reports and may be totally unaware of the problem of convergence or how to deal with it.

Effects of Nursing Home Residency on Diabetes Care in Individuals with Dementia: An Explorative Analysis Based on German Claims Data

PubMed Central

Schwarzkopf, Larissa; Holle, Rolf; Schunk, Michaela

2017-01-01

Aims This claims data-based study compares the intensity of diabetes care in community dwellers and nursing home residents with dementia. Methods Delivery of diabetes-related medical examinations (DRMEs) was compared via logistic regression in 1,604 community dwellers and 1,010 nursing home residents with dementia. The intra-individual effect of nursing home transfer was evaluated within mixed models. Results Delivery of DRMEs decreases with increasing care dependency, with more community-living individuals receiving DRMEs. Moreover, DRME provision decreases after nursing home transfer. Conclusion Dementia patients receive fewer DRMEs than recommended, especially in cases of higher care dependency and particularly in nursing homes. This suggests lacking awareness regarding the specific challenges of combined diabetes and dementia care. PMID:28413415

Associations between Responsible Beverage Service Laws and Binge Drinking and Alcohol-Impaired Driving

PubMed Central

Linde, Ann C.; Toomey, Traci L.; Wolfson, Julian; Lenk, Kathleen M.; Jones-Webb, Rhonda; Erickson, Darin J.

2017-01-01

We explored potential associations between the strength of state Responsible Beverage Service (RBS) laws and self-reported binge drinking and alcohol-impaired driving in the U.S. A multilevel logistic mixed-effects model was used, adjusting for potential confounders. Analyses were conducted on the overall BRFSS sample and drinkers only. Seven percent of BRFSS respondents lived in states with the strongest RBS laws, 15% reported binge drinking and 2% reported driving after having too much to drink at least once in the past 30 days. There was no evidence of a significant association between RBS law strength and self-reported binge drinking or alcohol-impaired driving. Future studies should include additional information about RBS laws and use a prospective research design. PMID:29225382

Are High-Lethality Suicide Attempters With Bipolar Disorder a Distinct Phenotype?

PubMed Central

Oquendo, Maria A.; Carballo, Juan Jose; Rajouria, Namita; Currier, Dianne; Tin, Adrienne; Merville, Jessica; Galfalvy, Hanga C.; Sher, Leo; Grunebaum, Michael F.; Burke, Ainsley K.; Mann, J. John

2013-01-01

Because Bipolar Disorder (BD) individuals making highly lethal suicide attempts have greater injury burden and risk for suicide, early identification is critical. BD patients were classified as high- or low-lethality attempters. High-lethality attempts required inpatient medical treatment. Mixed effects logistic regression models and permutation analyses examined correlations between lethality, number, and order of attempts. High-lethality attempters reported greater suicidal intent and more previous attempts. Multiple attempters showed no pattern of incremental lethality increase with subsequent attempts, but individuals with early high-lethality attempts more often made high-lethality attempts later. A subset of high-lethality attempters make only high-lethality attempts. However, presence of previous low-lethality attempts does not indicate that risk for more lethal, possibly successful, attempts is reduced. PMID:19590998

The association of health-related fitness with indicators of academic performance in Texas schools.

PubMed

Welk, Gregory J; Jackson, Allen W; Morrow, James R; Haskell, William H; Meredith, Marilu D; Cooper, Kenneth H

2010-09-01

This study examined the associations between indicators of health-related physical fitness (cardiovascular fitness and body mass index) and academic performance (Texas Assessment of Knowledge and Skills). Partial correlations were generally stronger for cardiovascular fitness than body mass index and consistently stronger in the middle school grades. Mixed-model regression analyses revealed modest associations between fitness and academic achievement after controlling for potentially confounding variables. The effects of fitness on academic achievement were positive but small. A separate logistic regression analysis indicated that higher fitness rates increased the odds of schools achieving exemplary/recognized school status within the state. School fitness attainment is an indicator of higher performing schools. Direction of causality cannot be inferred due to the cross-sectional nature of the data.

A development of logistics management models for the Space Transportation System

NASA Technical Reports Server (NTRS)

Carrillo, M. J.; Jacobsen, S. E.; Abell, J. B.; Lippiatt, T. F.

1983-01-01

A new analytic queueing approach was described which relates stockage levels, repair level decisions, and the project network schedule of prelaunch operations directly to the probability distribution of the space transportation system launch delay. Finite source population and limited repair capability were additional factors included in this logistics management model developed specifically for STS maintenance requirements. Data presently available to support logistics decisions were based on a comparability study of heavy aircraft components. A two-phase program is recommended by which NASA would implement an integrated data collection system, assemble logistics data from previous STS flights, revise extant logistics planning and resource requirement parameters using Bayes-Lin techniques, and adjust for uncertainty surrounding logistics systems performance parameters. The implementation of these recommendations can be expected to deliver more cost-effective logistics support.

The European Thoracic Surgery Database project: modelling the risk of in-hospital death following lung resection.

PubMed

Berrisford, Richard; Brunelli, Alessandro; Rocco, Gaetano; Treasure, Tom; Utley, Martin

2005-08-01

To identify pre-operative factors associated with in-hospital mortality following lung resection and to construct a risk model that could be used prospectively to inform decisions and retrospectively to enable fair comparisons of outcomes. Data were submitted to the European Thoracic Surgery Database from 27 units in 14 countries. We analysed data concerning all patients that had a lung resection. Logistic regression was used with a random sample of 60% of cases to identify pre-operative factors associated with in-hospital mortality and to build a model of risk. The resulting model was tested on the remaining 40% of patients. A second model based on age and ppoFEV1% was developed for risk of in-hospital death amongst tumour resection patients. Of the 3426 adult patients that had a first lung resection for whom mortality data were available, 66 died within the same hospital admission. Within the data used for model development, dyspnoea (according to the Medical Research Council classification), ASA (American Society of Anaesthesiologists) score, class of procedure and age were found to be significantly associated with in-hospital death in a multivariate analysis. The logistic model developed on these data displayed predictive value when tested on the remaining data. Two models of the risk of in-hospital death amongst adult patients undergoing lung resection have been developed. The models show predictive value and can be used to discern between high-risk and low-risk patients. Amongst the test data, the model developed for all diagnoses performed well at low risk, underestimated mortality at medium risk and overestimated mortality at high risk. The second model for resection of lung neoplasms was developed after establishing the performance of the first model and so could not be tested robustly. That said, we were encouraged by its performance over the entire range of estimated risk. The first of these two models could be regarded as an evaluation based on clinically available criteria while the second uses data obtained from objective measurement. We are optimistic that further model development and testing will provide a tool suitable for case mix adjustment.

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

A multimodal logistics service network design with time windows and environmental concerns

PubMed Central

Zhang, Dezhi; He, Runzhong; Wang, Zhongwei

2017-01-01

The design of a multimodal logistics service network with customer service time windows and environmental costs is an important and challenging issue. Accordingly, this work established a model to minimize the total cost of multimodal logistics service network design with time windows and environmental concerns. The proposed model incorporates CO2 emission costs to determine the optimal transportation mode combinations and investment selections for transfer nodes, which consider transport cost, transport time, carbon emission, and logistics service time window constraints. Furthermore, genetic and heuristic algorithms are proposed to set up the abovementioned optimal model. A numerical example is provided to validate the model and the abovementioned two algorithms. Then, comparisons of the performance of the two algorithms are provided. Finally, this work investigates the effects of the logistics service time windows and CO2 emission taxes on the optimal solution. Several important management insights are obtained. PMID:28934272

A multimodal logistics service network design with time windows and environmental concerns.

PubMed

Zhang, Dezhi; He, Runzhong; Li, Shuangyan; Wang, Zhongwei

2017-01-01

The design of a multimodal logistics service network with customer service time windows and environmental costs is an important and challenging issue. Accordingly, this work established a model to minimize the total cost of multimodal logistics service network design with time windows and environmental concerns. The proposed model incorporates CO2 emission costs to determine the optimal transportation mode combinations and investment selections for transfer nodes, which consider transport cost, transport time, carbon emission, and logistics service time window constraints. Furthermore, genetic and heuristic algorithms are proposed to set up the abovementioned optimal model. A numerical example is provided to validate the model and the abovementioned two algorithms. Then, comparisons of the performance of the two algorithms are provided. Finally, this work investigates the effects of the logistics service time windows and CO2 emission taxes on the optimal solution. Several important management insights are obtained.

Assessing intrinsic and specific vulnerability models ability to indicate groundwater vulnerability to groups of similar pesticides: A comparative study

USGS Publications Warehouse

Douglas, Steven; Dixon, Barnali; Griffin, Dale W.

2018-01-01

With continued population growth and increasing use of fresh groundwater resources, protection of this valuable resource is critical. A cost effective means to assess risk of groundwater contamination potential will provide a useful tool to protect these resources. Integrating geospatial methods offers a means to quantify the risk of contaminant potential in cost effective and spatially explicit ways. This research was designed to compare the ability of intrinsic (DRASTIC) and specific (Attenuation Factor; AF) vulnerability models to indicate groundwater vulnerability areas by comparing model results to the presence of pesticides from groundwater sample datasets. A logistic regression was used to assess the relationship between the environmental variables and the presence or absence of pesticides within regions of varying vulnerability. According to the DRASTIC model, more than 20% of the study area is very highly vulnerable. Approximately 30% is very highly vulnerable according to the AF model. When groundwater concentrations of individual pesticides were compared to model predictions, the results were mixed. Model predictability improved when concentrations of the group of similar pesticides were compared to model results. Compared to the DRASTIC model, the AF model more accurately predicts the distribution of the number of contaminated wells within each vulnerability class.

Disability and the Built Environment: An Investigation of Community and Neighborhood Land Uses and Participation for Physically Impaired Adults

PubMed Central

Botticello, Amanda L.; Rohrbach, Tanya; Cobbold, Nicolette

2014-01-01

Purpose There is a need for empirical support of the association between the built environment and disability-related outcomes. This study explores the associations between community and neighborhood land uses and community participation among adults with acquired physical disability. Methods Cross-sectional data from 508 community-living, chronically disabled adults in New Jersey were obtained from among participants in national Spinal Cord Injury Model Systems database. Participants’ residential addresses were geocoded to link individual survey data with Geographic Information Systems (GIS) data on land use and destinations. The influence of residential density, land use mix, destination counts, and open space on four domains of participation were modeled at two geographic scales—the neighborhood (i.e., half mile buffer) and community (i.e., five mile) using multivariate logistic regression. All analyses were adjusted for demographic and impairment-related differences. Results Living in communities with greater land use mix and more destinations was associated with a decreased likelihood of reporting optimum social and physical activity. Conversely, living in neighborhoods with large portions of open space was positively associated with the likelihood of reporting full physical, occupational, and social participation. Conclusions These findings suggest that the overall living conditions of the built environment may be relevant to social inclusion for persons with physical disabilities. PMID:24935467

The management challenge for household waste in emerging economies like Brazil: realistic source separation and activation of reverse logistics.

PubMed

Fehr, M

2014-09-01

Business opportunities in the household waste sector in emerging economies still evolve around the activities of bulk collection and tipping with an open material balance. This research, conducted in Brazil, pursued the objective of shifting opportunities from tipping to reverse logistics in order to close the balance. To do this, it illustrated how specific knowledge of sorted waste composition and reverse logistics operations can be used to determine realistic temporal and quantitative landfill diversion targets in an emerging economy context. Experimentation constructed and confirmed the recycling trilogy that consists of source separation, collection infrastructure and reverse logistics. The study on source separation demonstrated the vital difference between raw and sorted waste compositions. Raw waste contained 70% biodegradable and 30% inert matter. Source separation produced 47% biodegradable, 20% inert and 33% mixed material. The study on collection infrastructure developed the necessary receiving facilities. The study on reverse logistics identified private operators capable of collecting and processing all separated inert items. Recycling activities for biodegradable material were scarce and erratic. Only farmers would take the material as animal feed. No composting initiatives existed. The management challenge was identified as stimulating these activities in order to complete the trilogy and divert the 47% source-separated biodegradable discards from the landfills. © The Author(s) 2014.

Mixed-Amphetamine Salts Increase Abstinence From Marijuana in Patients With Co-Occurring Attention-Deficit/Hyperactivity Disorder and Cocaine Dependence

PubMed Central

Notzon, Daniel P.; Mariani, John J.; Pavlicova, Martina; Glass, Andrew; Mahony, Amy L.; Brooks, Daniel J.; Grabowski, John; Levin, Frances R.

2017-01-01

Background and Objectives The prevalence of ADHD is greater in substance use disorders than the general population, and ADHD and substance use disorders share neurobiological features such as dysregulation of reward circuitry. We tested the hypothesis that stimulants would decrease marijuana use in a randomized controlled trial of extended release mixed amphetamine salts (MAS-XR) for treatment of co-occurring ADHD and cocaine use disorders. Methods Marijuana users were defined as participants reporting use in the 30 days before study initiation, collected with timeline follow-back. The original 14-week trial utilized a 3-arm randomized design, comparing placebo, MAS-XR 60 mg, and MAS-XR 80 mg. For this analysis, both MAS-XR groups were combined, leaving n = 20 in the placebo group and n = 37 in the MAS-XR group. The primary outcome was proportion of subjects reporting any marijuana use per study week. Comparisons between groups were made using a logistic mixed effects model incorporating multiple predictors and modeling time-by-treatment interactions. Results There were no significant baseline differences in marijuana use frequency and quantity. There was a significant decrease in the proportion of participants using marijuana over time in the MAS-XR group, but no difference in the proportion of marijuana-use days over time. Discussion and Conclusions Treatment of ADHD and comorbid cocaine use disorders with MAS-XR is associated with increased weekly abstinence from marijuana but not with a decrease in the proportion of marijuana using days per week. Scientific Significance Stimulant treatment of ADHD and cocaine use disorders may diminish co-occurring cannabis use. PMID:28051838

Mixed-amphetamine salts increase abstinence from marijuana in patients with co-occurring attention-deficit/hyperactivity disorder and cocaine dependence.

PubMed

Notzon, Daniel P; Mariani, John J; Pavlicova, Martina; Glass, Andrew; Mahony, Amy L; Brooks, Daniel J; Grabowski, John; Levin, Frances R

2016-12-01

The prevalence of ADHD is greater in substance use disorders than the general population, and ADHD and substance use disorders share neurobiological features such as dysregulation of reward circuitry. We tested the hypothesis that stimulants would decrease marijuana use in a randomized controlled trial of extended release mixed amphetamine salts (MAS-XR) for treatment of co-occurring ADHD and cocaine use disorders. Marijuana users were defined as participants reporting use in the 30 days before study initiation, collected with timeline follow-back. The original 14-week trial utilized a 3-arm randomized design, comparing placebo, MAS-XR 60 mg, and MAS-XR 80 mg. For this analysis, both MAS-XR groups were combined, leaving n = 20 in the placebo group and n = 37 in the MAS-XR group. The primary outcome was proportion of subjects reporting any marijuana use per study week. Comparisons between groups were made using a logistic mixed effects model incorporating multiple predictors and modeling time-by-treatment interactions. There were no significant baseline differences in marijuana use frequency and quantity. There was a significant decrease in the proportion of participants using marijuana over time in the MAS-XR group, but no difference in the proportion of marijuana-use days over time. Treatment of ADHD and comorbid cocaine use disorders with MAS-XR is associated with increased weekly abstinence from marijuana but not with a decrease in the proportion of marijuana using days per week. Stimulant treatment of ADHD and cocaine use disorders may diminish co-occurring cannabis use. (Am J Addict 2016;25:666-672). © 2016 American Academy of Addiction Psychiatry.

Differentially private distributed logistic regression using private and public data

PubMed Central

2014-01-01

Background Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods sometimes introduce too much noise and make outputs less useful. Given available public data in medical research (e.g. from patients who sign open-consent agreements), we can design algorithms that use both public and private data sets to decrease the amount of noise that is introduced. Methodology In this paper, we modify the update step in Newton-Raphson method to propose a differentially private distributed logistic regression model based on both public and private data. Experiments and results We try our algorithm on three different data sets, and show its advantage over: (1) a logistic regression model based solely on public data, and (2) a differentially private distributed logistic regression model based on private data under various scenarios. Conclusion Logistic regression models built with our new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee. PMID:25079786

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

Pharmacodynamics and effectiveness of topical nitroglycerin at lowering blood pressure during autonomic dysreflexia.

PubMed

Solinsky, R; Bunnell, A E; Linsenmeyer, T A; Svircev, J N; Engle, A; Burns, S P

2017-10-01

Secondary analysis of prospectively collected observational data assessing the safety of an autonomic dysreflexia (AD) management protocol. To estimate the time to onset of action, time to full clinical effect (sustained systolic blood pressure (SBP) <160 mm Hg) and effectiveness of nitroglycerin ointment at lowering blood pressure for patients with spinal cord injuries experiencing AD. US Veterans Affairs inpatient spinal cord injury (SCI) unit. Episodes of AD recalcitrant to nonpharmacologic interventions that were given one to two inches of 2% topical nitroglycerin ointment were recorded. Pharmacodynamics as above and predictive characteristics (through a mixed multivariate logistic regression model) were calculated. A total of 260 episodes of pharmacologically managed AD were recorded in 56 individuals. Time to onset of action for nitroglycerin ointment was 9-11 min. Time to full clinical effect was 14-20 min. Topical nitroglycerin controlled SBP <160 mm Hg in 77.3% of pharmacologically treated AD episodes with the remainder requiring additional antihypertensive medications. A multivariate logistic regression model was unable to identify statistically significant factors to predict which patients would respond to nitroglycerin ointment (odds ratios 95% confidence intervals 0.29-4.93). The adverse event rate, entirely attributed to hypotension, was 3.6% with seven of the eight events resolving with close observation alone and one episode requiring normal saline. Nitroglycerin ointment has a rapid onset of action and time to full clinical effect with high efficacy and relatively low adverse event rate for patients with SCI experiencing AD.

Stages of syphilis in South China - a multilevel analysis of early diagnosis.

PubMed

Wong, Ngai Sze; Huang, Shujie; Zheng, Heping; Chen, Lei; Zhao, Peizhen; Tucker, Joseph D; Yang, Li Gang; Goh, Beng Tin; Yang, Bin

2017-01-31

Early diagnosis of syphilis and timely treatment can effectively reduce ongoing syphilis transmission and morbidity. We examined the factors associated with the early diagnosis of syphilis to inform syphilis screening strategic planning. In an observational study, we analyzed reported syphilis cases in Guangdong Province, China (from 2014 to mid-2015) accessed from the national case-based surveillance system. We categorized primary and secondary syphilis cases as early diagnosis and categorized latent and tertiary syphilis as delayed diagnosis. Univariate analyses and multivariable logistic regressions were performed to identify the factors associated with early diagnosis. We also examined the factors associated with early diagnosis at the individual and city levels in multilevel logistic regression models with cases nested by city (n = 21), adjusted for age at diagnosis and gender. Among 83,944 diagnosed syphilis cases, 22% were early diagnoses. The city-level early diagnosis rate ranged from 7 to 46%, consistent with substantial geographic variation as shown in the multilevel model. Early diagnosis was associated with cases presenting to specialist clinics for screening, being male and attaining higher education level. Cases received syphilis testing in institutions and hospitals, and diagnosed in hospitals were less likely to be in early diagnosis. At the city-level, cases living in a city equipped with more hospitals per capita were less likely to be early diagnosis. To enhance early diagnosis of syphilis, city-specific syphilis screening strategies with a mix of passive and client/provider-initiated testing might be a useful approach.

NASA Space Exploration Logistics Workshop Proceedings

NASA Technical Reports Server (NTRS)

deWeek, Oliver; Evans, William A.; Parrish, Joe; James, Sarah

2006-01-01

As NASA has embarked on a new Vision for Space Exploration, there is new energy and focus around the area of manned space exploration. These activities encompass the design of new vehicles such as the Crew Exploration Vehicle (CEV) and Crew Launch Vehicle (CLV) and the identification of commercial opportunities for space transportation services, as well as continued operations of the Space Shuttle and the International Space Station. Reaching the Moon and eventually Mars with a mix of both robotic and human explorers for short term missions is a formidable challenge in itself. How to achieve this in a safe, efficient and long-term sustainable way is yet another question. The challenge is not only one of vehicle design, launch, and operations but also one of space logistics. Oftentimes, logistical issues are not given enough consideration upfront, in relation to the large share of operating budgets they consume. In this context, a group of 54 experts in space logistics met for a two-day workshop to discuss the following key questions: 1. What is the current state-of the art in space logistics, in terms of architectures, concepts, technologies as well as enabling processes? 2. What are the main challenges for space logistics for future human exploration of the Moon and Mars, at the intersection of engineering and space operations? 3. What lessons can be drawn from past successes and failures in human space flight logistics? 4. What lessons and connections do we see from terrestrial analogies as well as activities in other areas, such as U.S. military logistics? 5. What key advances are required to enable long-term success in the context of a future interplanetary supply chain? These proceedings summarize the outcomes of the workshop, reference particular presentations, panels and breakout sessions, and record specific observations that should help guide future efforts.

Use and interpretation of logistic regression in habitat-selection studies

USGS Publications Warehouse

Keating, Kim A.; Cherry, Steve

2004-01-01

 Logistic regression is an important tool for wildlife habitat-selection studies, but the method frequently has been misapplied due to an inadequate understanding of the logistic model, its interpretation, and the influence of sampling design. To promote better use of this method, we review its application and interpretation under 3 sampling designs: random, case-control, and use-availability. Logistic regression is appropriate for habitat use-nonuse studies employing random sampling and can be used to directly model the conditional probability of use in such cases. Logistic regression also is appropriate for studies employing case-control sampling designs, but careful attention is required to interpret results correctly. Unless bias can be estimated or probability of use is small for all habitats, results of case-control studies should be interpreted as odds ratios, rather than probability of use or relative probability of use. When data are gathered under a use-availability design, logistic regression can be used to estimate approximate odds ratios if probability of use is small, at least on average. More generally, however, logistic regression is inappropriate for modeling habitat selection in use-availability studies. In particular, using logistic regression to fit the exponential model of Manly et al. (2002:100) does not guarantee maximum-likelihood estimates, valid probabilities, or valid likelihoods. We show that the resource selection function (RSF) commonly used for the exponential model is proportional to a logistic discriminant function. Thus, it may be used to rank habitats with respect to probability of use and to identify important habitat characteristics or their surrogates, but it is not guaranteed to be proportional to probability of use. Other problems associated with the exponential model also are discussed. We describe an alternative model based on Lancaster and Imbens (1996) that offers a method for estimating conditional probability of use in use-availability studies. Although promising, this model fails to converge to a unique solution in some important situations. Further work is needed to obtain a robust method that is broadly applicable to use-availability studies.

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.

Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

NASA Astrophysics Data System (ADS)

Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

2014-07-01

Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

An observational cohort study on persistency of internal teat sealant residues in milk after calving in dairy cows.

PubMed

Kabera, Fidèle; Dufour, Simon; Keefe, Greg; Roy, Jean-Philippe

2018-04-04

Our objectives were to evaluate the prevalence of quarters with an observable internal teat sealant (ITS) plug at first milking following calving and investigate persistency of ITS residues in milk after calving. An observational cohort study was carried out on 557 quarters of 156 cows treated with ITS in 6 farms in Quebec, Canada. The presence of an ITS plug at first milking and ITS residues in milk at each milking were observed by producers. The effects of various factors on the odds of observing an ITS plug and persistency of ITS residues in milk were studied using generalized logistic mixed and generalized negative binomial mixed models, respectively. Milk samples were taken on the day before dry-off and on 2 occasions after calving for bacterial identification to detect intramammary infection (IMI) using bacteriological culture followed by MALDI-TOF identification. The association between the absence of an ITS plug and the presence of new IMI was assessed using a mixed logistic regression model. Internal teat sealant plugs after calving were more often observed in rear quarters and in quarters receiving ITS alone at drying-off versus antimicrobial and ITS. We observed an average (standard deviation) persistency of 4.0 d (2.3 d). When an ITS plug was still present at first milking (83% of quarters), the elimination of ITS residues in milk after calving was significantly longer (4.5 d, on average) compared with 1.2 d when an ITS plug was absent. In cows with an ITS plug at calving, we observed a higher number of days of excretion in older cows. When a plug could not be observed, rear quarters, older cows, and cows with a long dry period duration excreted ITS residues for a significantly longer period. The lack of a significant association between the absence of a plug and the odds of new IMI at calving suggests that despite the loss of the plug, cows were still protected against new IMI. Although we were able to highlight some statistically significant risk factors explaining persistency of ITS residues following calving, observed differences were often relatively small and, perhaps, not clinically relevant. In conclusion, an ITS plug was present until first milking after calving for 83% quarters, quarters without an ITS plug at first milking appeared to have been protected from new IMI, and ITS residues could be observed in milk up to 12 d in milk. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

Applying Simulation and Logistics Modeling to Transportation Issues

DOT National Transportation Integrated Search

1995-08-15

This paper describes an application where transportation logistics and simulation tools are integrated to create a modeling environment for transportation planning. The Transportation Planning Model (TPM) is a tool developed for the Department of Ene...

The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model

PubMed Central

LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei

2017-01-01

Background: We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. Methods: We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. Results: For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Conclusion: Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers. PMID:28828316

The Virtual Research Lab: Research Outcome Expectations, Research Knowledge, and the Graduate Student Experience

ERIC Educational Resources Information Center

Stadtlander, Lee; Giles, Martha; Sickel, Amy

2013-01-01

This paper examines the complexities of working with student researchers in a virtual lab setting, logistics, and methods to resolve issues. To demonstrate the feasibility of a virtual lab, a mixed-methods study consisting of quantitative surveys and qualitative data examined changes in doctoral students' confidence as measured by research outcome…

Developing Appropriate Workforce Skills for Australia's Emerging Digital Economy: Working Paper

ERIC Educational Resources Information Center

Gekara, Victor; Molla, Alemayehu; Snell, Darryn; Karanasios, Stan; Thomas, Amanda

2017-01-01

This working paper is the first publication coming out of a project investigating the role of vocational education and training (VET) in developing digital skills in the Australian workforce, using two sectors as case studies--Transport and Logistics, and Public Safety and Correctional Services. The study employs a mixed method approach, combining…

Does the Perceived Neighborhood Reputation Contribute to Neighborhood Differences in Social Trust and Residential Wellbeing?

ERIC Educational Resources Information Center

Kullberg, Agneta; Timpka, Toomas; Svensson, Tommy; Karlsson, Nadine; Lindqvist, Kent

2010-01-01

The authors used a mixed methods approach to examine if the reputation of a housing area has bearing on residential wellbeing and social trust in three pairs of socioeconomically contrasting neighborhoods in a Swedish urban municipality. Multilevel logistic regression analyses were performed to examine associations between area reputation and…

Two models of inventory control with supplier selection in case of multiple sourcing: a case of Isfahan Steel Company

NASA Astrophysics Data System (ADS)

Rabieh, Masood; Soukhakian, Mohammad Ali; Mosleh Shirazi, Ali Naghi

2016-06-01

Selecting the best suppliers is crucial for a company's success. Since competition is a determining factor nowadays, reducing cost and increasing quality of products are two key criteria for appropriate supplier selection. In the study, first the inventories of agglomeration plant of Isfahan Steel Company were categorized through VED and ABC methods. Then the models to supply two important kinds of raw materials (inventories) were developed, considering the following items: (1) the optimal consumption composite of the materials, (2) the total cost of logistics, (3) each supplier's terms and conditions, (4) the buyer's limitations and (5) the consumption behavior of the buyers. Among diverse developed and tested models—using the company's actual data within three pervious years—the two new innovative models of mixed-integer non-linear programming type were found to be most suitable. The results of solving two models by lingo software (based on company's data in this particular case) were equaled. Comparing the results of the new models to the actual performance of the company revealed 10.9 and 7.1 % reduction in total procurement costs of the company in two consecutive years.

Joint Optimization of Distribution Network Design and Two-Echelon Inventory Control with Stochastic Demand and CO2 Emission Tax Charges.

PubMed

Li, Shuangyan; Li, Xialian; Zhang, Dezhi; Zhou, Lingyun

2017-01-01

This study develops an optimization model to integrate facility location and inventory control for a three-level distribution network consisting of a supplier, multiple distribution centers (DCs), and multiple retailers. The integrated model addressed in this study simultaneously determines three types of decisions: (1) facility location (optimal number, location, and size of DCs); (2) allocation (assignment of suppliers to located DCs and retailers to located DCs, and corresponding optimal transport mode choices); and (3) inventory control decisions on order quantities, reorder points, and amount of safety stock at each retailer and opened DC. A mixed-integer programming model is presented, which considers the carbon emission taxes, multiple transport modes, stochastic demand, and replenishment lead time. The goal is to minimize the total cost, which covers the fixed costs of logistics facilities, inventory, transportation, and CO2 emission tax charges. The aforementioned optimal model was solved using commercial software LINGO 11. A numerical example is provided to illustrate the applications of the proposed model. The findings show that carbon emission taxes can significantly affect the supply chain structure, inventory level, and carbon emission reduction levels. The delay rate directly affects the replenishment decision of a retailer.

Injury risk for matched front and rear seat car passengers by injury severity and crash type: An exploratory study.

PubMed

Mitchell, R J; Bambach, M R; Toson, Barbara

2015-09-01

The risk of serious injury or death has been found to be reduced for some front compared to rear seat car passengers in newer vehicles. However, differences in injury severity between car occupants by seating position has not been examined. This study examines the injury severity risk for rear compared to front seat car passengers. A retrospective matched-cohort analysis was conducted of vehicle crashes involving injured rear vs front seat car passengers identified in linked police-reported, hospitalisation and emergency department (ED) presentation records during 2001-2011 in New South Wales (NSW), Australia. Odds ratios were estimated using an ordinal logistic mixed model and logistic mixed models. There were 5419 front and 4588 rear seat passengers in 3681 vehicles. There was a higher odds of sustaining a higher injury severity as a rear-compared to a front seat car passenger, with a higher odds of rear seat passengers sustaining serious injuries compared to minimal injuries. Where the vehicle occupant was older, travelling in a vehicle manufactured between 1990 and 1996 or after 1997, where the airbag deployed, and where the vehicle was driven where the speed limit was ≥70km/h there was a higher odds of the rear passenger sustaining a higher injury severity then a front seated occupant. Rear seat car passengers are sustaining injuries of a higher severity compared to front seat passengers travelling in the same vehicle, as well as when travelling in newer vehicles and where the front seat occupant is shielded by an airbag deployed in the crash. Rear seat occupant protective mechanisms should be examined. Pre-hospital trauma management policies could influence whether an individual is transported to a hospital ED, thus it would be beneficial to have an objective measure of injury severity routinely available in ED records. Further examination of injury severity between rear and front seat passengers is warranted to examine less severe non-fatal injuries by car seating position and vehicle intrusion. Copyright © 2015 Elsevier Ltd. All rights reserved.

How important are venue-based HIV risks among male clients of female sex workers? A mixed methods analysis of the risk environment in nightlife venues in Tijuana, Mexico

PubMed Central

Goldenberg, Shira; Strathdee, Steffanie A.; Gallardo, Manuel; Nguyen, Lucie; Lozada, Remedios; Semple, Shirley J.; Patterson, Thomas L.

2011-01-01

In 2008, 400 males ≥ 18 years old who paid or traded for sex with a female sex worker (FSW) in Tijuana, Mexico, in the past 4 months completed surveys and HIV/STI testing; 30 also completed qualitative interviews. To analyze environmental HIV vulnerability among male clients of FSWs in Tijuana, Mexico, we used mixed methods to investigate correlates of clients who met FSWs in nightlife venues and clients’ perspectives on venue-based risks. Logistic regression identified micro-level correlates of meeting FSWs in nightlife venues, which were triangulated with clients’ narratives regarding macro-level influences. In a multivariate model, offering increased pay for unprotected sex and binge drinking were micro-level factors that were independently associated with meeting FSWs in nightlife venues versus other places. In qualitative interviews, clients characterized nightlife venues as high risk due to the following macro-level features: social norms dictating heavy alcohol consumption; economic exploitation by establishment owners; and poor enforcement of sex work regulations in nightlife venues. Structural interventions in nightlife venues are needed to address venue-based risks. PMID:21396875

Non-replication of the association between 5HTTLPR and response to psychological therapy for child anxiety disorders

PubMed Central

Lester, Kathryn J.; Roberts, Susanna; Keers, Robert; Coleman, Jonathan R. I.; Breen, Gerome; Wong, Chloe C. Y.; Xu, Xiaohui; Arendt, Kristian; Blatter-Meunier, Judith; Bögels, Susan; Cooper, Peter; Creswell, Cathy; Heiervang, Einar R.; Herren, Chantal; Hogendoorn, Sanne M.; Hudson, Jennifer L.; Krause, Karen; Lyneham, Heidi J.; McKinnon, Anna; Morris, Talia; Nauta, Maaike H.; Rapee, Ronald M.; Rey, Yasmin; Schneider, Silvia; Schneider, Sophie C.; Silverman, Wendy K.; Smith, Patrick; Thastum, Mikael; Thirlwall, Kerstin; Waite, Polly; Wergeland, Gro Janne; Eley, Thalia C.

2016-01-01

Background We previously reported an association between 5HTTLPR genotype and outcome following cognitive–behavioural therapy (CBT) in child anxiety (Cohort 1). Children homozygous for the low-expression short-allele showed more positive outcomes. Other similar studies have produced mixed results, with most reporting no association between genotype and CBT outcome. Aims To replicate the association between 5HTTLPR and CBT outcome in child anxiety from the Genes for Treatment study (GxT Cohort 2, n = 829). Method Logistic and linear mixed effects models were used to examine the relationship between 5HTTLPR and CBT outcomes. Mega-analyses using both cohorts were performed. Results There was no significant effect of 5HTTLPR on CBT outcomes in Cohort 2. Mega-analyses identified a significant association between 5HTTLPR and remission from all anxiety disorders at follow-up (odds ratio 0.45, P = 0.014), but not primary anxiety disorder outcomes. Conclusions The association between 5HTTLPR genotype and CBT outcome did not replicate. Short-allele homozygotes showed more positive treatment outcomes, but with small, non-significant effects. Future studies would benefit from utilising whole genome approaches and large, homogenous samples. PMID:26294368

How important are venue-based HIV risks among male clients of female sex workers? A mixed methods analysis of the risk environment in nightlife venues in Tijuana, Mexico.

PubMed

Goldenberg, Shira M; Strathdee, Steffanie A; Gallardo, Manuel; Nguyen, Lucie; Lozada, Remedios; Semple, Shirley J; Patterson, Thomas L

2011-05-01

In 2008, 400 males ≥18 years old who paid or traded for sex with a female sex worker (FSW) in Tijuana, Mexico, in the past 4 months completed surveys and HIV/STI testing; 30 also completed qualitative interviews. To analyze environmental sources of HIV vulnerability among male clients of FSWs in Tijuana, we used mixed methods to investigate correlates of clients who met FSWs in nightlife venues and clients' perspectives on venue-based HIV risk. Logistic regression identified micro-level correlates of meeting FSWs in nightlife venues, which were triangulated with clients' narratives regarding macro-level influences. In a multivariate model, offering increased pay for unprotected sex and binge drinking were micro-level factors that were independently associated with meeting FSWs in nightlife venues versus other places. In qualitative interviews, clients characterized nightlife venues as high risk due to the following macro-level features: social norms dictating heavy alcohol consumption; economic exploitation by establishment owners; and poor enforcement of sex work regulations in nightlife venues. Structural interventions in nightlife venues are needed to address venue-based risks. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling logistic performance in quantitative microbial risk assessment.

PubMed

Rijgersberg, Hajo; Tromp, Seth; Jacxsens, Liesbeth; Uyttendaele, Mieke

2010-01-01

In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage times, temperatures, gas conditions, and their distributions) are determined. However, the logistic chain with its queues (storages, shelves) and mechanisms for ordering products is usually not taken into account. As a consequence, storage times-mutually dependent in successive steps in the chain-cannot be described adequately. This may have a great impact on the tails of risk distributions. Because food safety risks are generally very small, it is crucial to model the tails of (underlying) distributions as accurately as possible. Logistic performance can be modeled by describing the underlying planning and scheduling mechanisms in discrete-event modeling. This is common practice in operations research, specifically in supply chain management. In this article, we present the application of discrete-event modeling in the context of a QMRA for Listeria monocytogenes in fresh-cut iceberg lettuce. We show the potential value of discrete-event modeling in QMRA by calculating logistic interventions (modifications in the logistic chain) and determining their significance with respect to food safety.

Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.

PubMed

Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio

2014-11-24

The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine stratification.

Contraception After Delivery Among Publicly Insured Women in Texas: Use Compared With Preference.

PubMed

Potter, Joseph E; Coleman-Minahan, Kate; White, Kari; Powers, Daniel A; Dillaway, Chloe; Stevenson, Amanda J; Hopkins, Kristine; Grossman, Daniel

2017-08-01

To assess women's preferences for contraception after delivery and to compare use with preferences. In a prospective cohort study of women aged 18-44 years who wanted to delay childbearing for at least 2 years, we interviewed 1,700 participants from eight hospitals in Texas immediately postpartum and at 3 and 6 months after delivery. At 3 months, we assessed contraceptive preferences by asking what method women would like to be using at 6 months. We modeled preference for highly effective contraception and use given preference according to childbearing intentions using mixed-effects logistic regression testing for variability across hospitals and differences between those with and without immediate postpartum long-acting reversible contraception (LARC) provision. Approximately 80% completed both the 3- and 6-month interviews (1,367/1,700). Overall, preferences exceeded use for both-LARC: 40.8% (n=547) compared with 21.9% (n=293) and sterilization: 36.1% (n=484) compared with 17.5% (n=235). In the mixed-effects logistic regression models, several demographic variables were associated with a preference for LARC among women who wanted more children, but there was no significant variability across hospitals. For women who wanted more children and had a LARC preference, use of LARC was higher in the hospital that offered immediate postpartum provision (P<.035) as it was for U.S.-born women (odds ratio [OR] 2.08, 95% CI 1.17-3.69) and women with public prenatal care providers (OR 2.04, 95% CI 1.13-3.69). In the models for those who wanted no more children, there was no significant variability in preferences for long-acting or permanent methods across hospitals. However, use given preference varied across hospitals (P<.001) and was lower for black women (OR 0.26, 95% CI 0.12-0.55) and higher for U.S.-born women (OR 2.32, 95% CI 1.36-3.96), those 30 years of age and older (OR 1.82, 95% CI 1.07-3.09), and those with public prenatal care providers (OR 2.04, 95% CI 1.18-3.51). Limited use of long-acting and permanent contraceptive methods after delivery is associated with indicators of health care provider and system-level barriers. Expansion of immediate postpartum LARC provision as well as contraceptive coverage for undocumented women could reduce the gap between preference and use.

Modeling Population Growth and Extinction

ERIC Educational Resources Information Center

Gordon, Sheldon P.

2009-01-01

The exponential growth model and the logistic model typically introduced in the mathematics curriculum presume that a population grows exclusively. In reality, species can also die out and more sophisticated models that take the possibility of extinction into account are needed. In this article, two extensions of the logistic model are considered,…

Optimization of Location-Routing Problem for Cold Chain Logistics Considering Carbon Footprint.

PubMed

Wang, Songyi; Tao, Fengming; Shi, Yuhe

2018-01-06

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location-routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network.

Exploration of preterm birth rates associated with different models of antenatal midwifery care in Scotland: Unmatched retrospective cohort analysis.

PubMed

Symon, Andrew; Winter, Clare; Cochrane, Lynda

2015-06-01

preterm birth represents a significant personal, clinical, organisational and financial burden. Strategies to reduce the preterm birth rate have had limited success. Limited evidence indicates that certain antenatal care models may offer some protection, although the causal mechanism is not understood. We sought to compare preterm birth rates for mixed-risk pregnant women accessing antenatal care organised at a freestanding midwifery unit (FMU) and mixed-risk pregnant women attending an obstetric unit (OU) with related community-based antenatal care. unmatched retrospective 4-year Scottish cohort analysis (2008-2011) of mixed-risk pregnant women accessing (i) FMU antenatal care (n=1107); (ii) combined community-based and OU antenatal care (n=7567). Data were accessed via the Information and Statistics Division of the NHS in Scotland. Aggregates analysis and binary logistic regression were used to compare the cohorts׳ rates of preterm birth; and of spontaneous labour onset, use of pharmacological analgesia, unassisted vertex birth, and low birth weight. Odds ratios were adjusted for age, parity, deprivation score and smoking status in pregnancy. after adjustment the 'mixed risk' FMU cohort had a statistically significantly reduced risk of preterm birth (5.1% [n=57] versus 7.7% [n=583]; AOR 0.73 [95% CI 0.55-0.98]; p=0.034). Differences in these secondary outcome measures were also statistically significant: spontaneous labour onset (FMU 83.9% versus OU 74.6%; AOR 1.74 [95% CI 1.46-2.08]; p<0.001); minimal intrapartum analgesia (FMU 53.7% versus OU 34.4%; AOR 2.17 [95% CI 1.90-2.49]; p<0.001); spontaneous vertex delivery (FMU 71.9% versus OU 63.5%; AOR 1.46 [95% CI 1.32-1.78]; p<0.001). Incidence of low birth weight was not statistically significant after adjustment for other variables. There was no significant difference in the rate of perinatal or neonatal death. given this study׳s methodological limitations, we can only claim associations between the care model and or chosen outcomes. Although both cohorts were mixed risk, differences in risk levels could have contributed to these findings. Nevertheless, the significant difference in preterm birth rates in this study resonates with other research, including the recent Cochrane review of midwife-led continuity models. Because of the multiplicity of risk factors for preterm birth we need to explore the salient features of the FMU model which may be contributing to this apparent protective effect. Because a randomised controlled trial would necessarily restrict choice to pregnant women, we feel that this option is problematic in exploring this further. We therefore plan to conduct a prospective matched cohort analysis together with a survey of unit practices and experiences. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

PubMed

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

TDP-43 stage, mixed pathologies, and clinical Alzheimer’s-type dementia

PubMed Central

James, Bryan D.; Wilson, Robert S.; Boyle, Patricia A.; Trojanowski, John Q.; Bennett, David A.; Schneider, Julie A.

2016-01-01

Hyperphosphorylated transactive response DNA-binding protein 43 (TDP-43, encoded by TARDBP) proteinopathy has recently been described in ageing and in association with cognitive impairment, especially in the context of Alzheimer’s disease pathology. To explore the role of mixed Alzheimer’s disease and TDP-43 pathologies in clinical Alzheimer’s-type dementia, we performed a comprehensive investigation of TDP-43, mixed pathologies, and clinical Alzheimer’s-type dementia in a large cohort of community-dwelling older subjects. We tested the hypotheses that TDP-43 with Alzheimer’s disease pathology is a common mixed pathology; is related to increased likelihood of expressing clinical Alzheimer’s-type dementia; and that TDP-43 pathologic stage is an important determinant of clinical Alzheimer’s-type dementia. Data came from 946 older adults with (n = 398) and without dementia (n = 548) from the Rush Memory and Aging Project and Religious Orders Study. TDP-43 proteinopathy (cytoplasmic inclusions) was present in 496 (52%) subjects, and the pattern of deposition was classified as stage 0 (none; 48%), stage 1 (amygdala; 18%), stage 2 (extension to hippocampus/entorhinal; 21%), or stage 3 (extension to neocortex; 14%). TDP-43 pathology combined with a pathologic diagnosis of Alzheimer’s disease was a common mixed pathology (37% of all participants), and the proportion of subjects with clinical Alzheimer’s-type dementia formerly labelled ‘pure pathologic diagnosis of Alzheimer’s disease’ was halved when TDP-43 was considered. In logistic regression models adjusted for age, sex, and education, TDP-43 pathology was associated with clinical Alzheimer’s-type dementia (odds ratio = 1.51, 95% confidence interval = 1.11, 2.05) independent of pathological Alzheimer’s disease (odds ratio = 4.30, 95% confidence interval = 3.08, 6.01) or other pathologies (infarcts, arteriolosclerosis, Lewy bodies, and hippocampal sclerosis). Mixed Alzheimer’s disease and TDP-43 pathologies were associated with higher odds of clinical Alzheimer’s-type dementia (odds ratio = 6.73, 95% confidence interval = 4.18, 10.85) than pathologic Alzheimer’s disease alone (odds ratio = 4.62, 95% confidence interval = 2.84, 7.52). In models examining TDP-43 stage, a dose-response relationship with clinical Alzheimer’s-type dementia was observed, and a significant association was observed starting at stage 2, extension beyond the amygdala. In this large sample from almost 1000 community participants, we observed that TDP-43 proteinopathy was very common, frequently mixed with pathological Alzheimer’s disease, and associated with a higher likelihood of the clinical expression of clinical Alzheimer’s-type dementia but only when extended beyond the amygdala. PMID:27694152

Research on reverse logistics location under uncertainty environment based on grey prediction

NASA Astrophysics Data System (ADS)

Zhenqiang, Bao; Congwei, Zhu; Yuqin, Zhao; Quanke, Pan

This article constructs reverse logistic network based on uncertain environment, integrates the reverse logistics network and distribution network, and forms a closed network. An optimization model based on cost is established to help intermediate center, manufacturing center and remanufacturing center make location decision. A gray model GM (1, 1) is used to predict the product holdings of the collection points, and then prediction results are carried into the cost optimization model and a solution is got. Finally, an example is given to verify the effectiveness and feasibility of the model.

Next day discharge rate has little use as a quality measure for individual physician performance.

PubMed

Inabnit, Christopher; Markwell, Stephen; Gruwell, Jack; Jaeger, Cassie; Millburg, Lance; Griffen, David

2018-06-18

Emergency Department (ED) physicians' next day discharge rate (NDDR), the percentage of patients who were admitted from the ED and subsequently discharged within the next calendar day was hypothesized as a potential measure for unnecessary admissions. The objective was to determine if NDDR has validity as a measure for quality of individual ED physician performance. Hospital admission data was obtained for thirty-six ED physicians for calendar year 2015. Funnel plots were used to identify NDDR outliers beyond 95% control limits. A mixed model logistic regression was built to investigate factors contributing to NDDR. To determine yearly variation, data from calendar years 2014 and 2016 were analyzed, again by funnel plots and logistic regression. Intraclass correlation coefficient was used to estimate the percent of total variation in NDDR attributable to individual ED physicians. NDDR varied significantly among ED physicians. Individual ED physician outliers in NDDR varied year to year. Individual ED physician contribution to NDDR variation was minimal, accounting for 1%. Years of experience in Emergency Medicine practice was not correlated with NDDR. NDDR does not appear to be a reliable independent quality measure for individual ED physician performance. The percent of variance attributable to the ED physician was 1%. Copyright © 2018. Published by Elsevier Inc.

How Do Clinicians Prefer Cultural Competence Training? Findings from the DSM-5 Cultural Formulation Interview Field Trial

PubMed Central

Aggarwal, Neil Krishan; Lam, Peter; Castillo, Enrico; Weiss, Mitchell G.; Diaz, Esperanza; Alarcón, Renato D.; van Dijk, Rob; Rohlof, Hans; Ndetei, David M.; Scalco, Monica; Aguilar-Gaxiola, Sergio; Bassiri, Kavoos; Deshpande, Smita; Groen, Simon; Jadhav, Sushrut; Kirmayer, Laurence J.; Paralikar, Vasudeo; Westermeyer, Joseph; Santos, Filipa; Vega-Dienstmaier, Johann; Anez, Luis; Boiler, Marit; Nicasio, Andel V.; Lewis-Fernández, Roberto

2015-01-01

Objective This study’s objective is to analyze training methods clinicians reported as most and least helpful during the DSM-5 Cultural Formulation Interview field trial, reasons why, and associations between demographic characteristics and method preferences. Method The authors used mixed methods to analyze interviews from 75 clinicians in five continents on their training preferences after a standardized training session and clinicians’ first administration of the Cultural Formulation Interview. Content analysis identified most and least helpful educational methods by reason. Bivariate and logistic regression analysis compared clinician characteristics to method preferences. Results Most frequently, clinicians named case-based behavioral simulations as “most helpful” and video as “least helpful” training methods. Bivariate and logistic regression models, first unadjusted and then clustered by country, found that each additional year of a clinician’s age was associated with a preference for behavioral simulations: OR=1.05 (95% CI: 1.01–1.10; p=0.025). Conclusions Most clinicians preferred active behavioral simulations in cultural competence training, and this effect was most pronounced among older clinicians. Effective training may be best accomplished through a combination of reviewing written guidelines, video demonstration, and behavioral simulations. Future work can examine the impact of clinician training satisfaction on patient symptoms and quality of life. PMID:26449983

Humanitarian response: improving logistics to save lives.

PubMed

McCoy, Jessica

2008-01-01

Each year, millions of people worldwide are affected by disasters, underscoring the importance of effective relief efforts. Many highly visible disaster responses have been inefficient and ineffective. Humanitarian agencies typically play a key role in disaster response (eg, procuring and distributing relief items to an affected population, assisting with evacuation, providing healthcare, assisting in the development of long-term shelter), and thus their efficiency is critical for a successful disaster response. The field of disaster and emergency response modeling is well established, but the application of such techniques to humanitarian logistics is relatively recent. This article surveys models of humanitarian response logistics and identifies promising opportunities for future work. Existing models analyze a variety of preparation and response decisions (eg, warehouse location and the distribution of relief supplies), consider both natural and manmade disasters, and typically seek to minimize cost or unmet demand. Opportunities to enhance the logistics of humanitarian response include the adaptation of models developed for general disaster response; the use of existing models, techniques, and insights from the literature on commercial supply chain management; the development of working partnerships between humanitarian aid organizations and private companies with expertise in logistics; and the consideration of behavioral factors relevant to a response. Implementable, realistic models that support the logistics of humanitarian relief can improve the preparation for and the response to disasters, which in turn can save lives.

Multinomial Logistic Regression Predicted Probability Map To Visualize The Influence Of Socio-Economic Factors On Breast Cancer Occurrence in Southern Karnataka

NASA Astrophysics Data System (ADS)

Madhu, B.; Ashok, N. C.; Balasubramanian, S.

2014-11-01

Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.

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.

A decision support model for investment on P2P lending platform.

PubMed

Zeng, Xiangxiang; Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace-Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone.

A decision support model for investment on P2P lending platform

PubMed Central

Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace—Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone. PMID:28877234

Measurement of faculty anesthesiologists' quality of clinical supervision has greater reliability when controlling for the leniency of the rating anesthesia resident: a retrospective cohort study.

PubMed

Dexter, Franklin; Ledolter, Johannes; Hindman, Bradley J

2017-06-01

Our department monitors the quality of anesthesiologists' clinical supervision and provides each anesthesiologist with periodic feedback. We hypothesized that greater differentiation among anesthesiologists' supervision scores could be obtained by adjusting for leniency of the rating resident. From July 1, 2013 to December 31, 2015, our department has utilized the de Oliveira Filho unidimensional nine-item supervision scale to assess the quality of clinical supervision provided by faculty as rated by residents. We examined all 13,664 ratings of the 97 anesthesiologists (ratees) by the 65 residents (raters). Testing for internal consistency among answers to questions (large Cronbach's alpha > 0.90) was performed to rule out that one or two questions accounted for leniency. Mixed-effects logistic regression was used to compare ratees while controlling for rater leniency vs using Student t tests without rater leniency. The mean supervision scale score was calculated for each combination of the 65 raters and nine questions. The Cronbach's alpha was very large (0.977). The mean score was calculated for each of the 3,421 observed combinations of resident and anesthesiologist. The logits of the percentage of scores equal to the maximum value of 4.00 were normally distributed (residents, P = 0.24; anesthesiologists, P = 0.50). There were 20/97 anesthesiologists identified as significant outliers (13 with below average supervision scores and seven with better than average) using the mixed-effects logistic regression with rater leniency entered as a fixed effect but not by Student's t test. In contrast, there were three of 97 anesthesiologists identified as outliers (all three above average) using Student's t tests but not by logistic regression with leniency. The 20 vs 3 was significant (P < 0.001). Use of logistic regression with leniency results in greater detection of anesthesiologists with significantly better (or worse) clinical supervision scores than use of Student's t tests (i.e., without adjustment for rater leniency).

Variability in age and size at maturation, reproductive longevity, and long-term growth dynamics for Kemp's ridley sea turtles in the Gulf of Mexico

PubMed Central

Goshe, Lisa R.; Coggins, Lewis; Shaver, Donna J.; Higgins, Ben; Landry, Andre M.; Bailey, Rhonda

2017-01-01

Effective management of protected sea turtle populations requires knowledge not only of mean values for demographic and life-history parameters, but also temporal and spatial trends, variability, and underlying causes. For endangered Kemp’s ridley sea turtles (Lepidochelys kempii), the need for baseline information of this type has been emphasized during attempts to understand causes underlying the recent truncation in the recovery trajectory for nesting females. To provide insight into variability in age and size at sexual maturation (ASM and SSM) and long-term growth patterns likely to influence population trends, we conducted skeletochronological analysis of humerus bones from 333 Kemp’s ridleys stranded throughout the Gulf of Mexico (GOM) from 1993 to 2010. Ranges of possible ASMs (6.8 to 21.8 yr) and SSMs (53.3 to 68.3 cm straightline carapace length (SCL)) estimated using the “rapprochement” skeletal growth mark associated with maturation were broad, supporting incorporation of a maturation schedule in Kemp’s ridley population models. Mean ASMs estimated from rapprochement and by fitting logistic, generalized additive mixed, and von Bertalanffy growth models to age and growth data ranged from 11 to 13 yr; confidence intervals for the logistic model predicted maturation of 95% of the population between 11.9 and 14.8 yr. Early juvenile somatic growth rates in the GOM were greater than those previously reported for the Atlantic, indicating potential for differences in maturation trajectories between regions. Finally, long-term, significant decreases in somatic growth response were found for both juveniles and adults, which could influence recruitment to the reproductive population and observed nesting population trends. PMID:28333937

Variability in age and size at maturation, reproductive longevity, and long-term growth dynamics for Kemp's ridley sea turtles in the Gulf of Mexico.

PubMed

Avens, Larisa; Goshe, Lisa R; Coggins, Lewis; Shaver, Donna J; Higgins, Ben; Landry, Andre M; Bailey, Rhonda

2017-01-01

Effective management of protected sea turtle populations requires knowledge not only of mean values for demographic and life-history parameters, but also temporal and spatial trends, variability, and underlying causes. For endangered Kemp's ridley sea turtles (Lepidochelys kempii), the need for baseline information of this type has been emphasized during attempts to understand causes underlying the recent truncation in the recovery trajectory for nesting females. To provide insight into variability in age and size at sexual maturation (ASM and SSM) and long-term growth patterns likely to influence population trends, we conducted skeletochronological analysis of humerus bones from 333 Kemp's ridleys stranded throughout the Gulf of Mexico (GOM) from 1993 to 2010. Ranges of possible ASMs (6.8 to 21.8 yr) and SSMs (53.3 to 68.3 cm straightline carapace length (SCL)) estimated using the "rapprochement" skeletal growth mark associated with maturation were broad, supporting incorporation of a maturation schedule in Kemp's ridley population models. Mean ASMs estimated from rapprochement and by fitting logistic, generalized additive mixed, and von Bertalanffy growth models to age and growth data ranged from 11 to 13 yr; confidence intervals for the logistic model predicted maturation of 95% of the population between 11.9 and 14.8 yr. Early juvenile somatic growth rates in the GOM were greater than those previously reported for the Atlantic, indicating potential for differences in maturation trajectories between regions. Finally, long-term, significant decreases in somatic growth response were found for both juveniles and adults, which could influence recruitment to the reproductive population and observed nesting population trends.

A simple tool to predict admission at the time of triage.

PubMed

Cameron, Allan; Rodgers, Kenneth; Ireland, Alastair; Jamdar, Ravi; McKay, Gerard A

2015-03-01

To create and validate a simple clinical score to estimate the probability of admission at the time of triage. This was a multicentre, retrospective, cross-sectional study of triage records for all unscheduled adult attendances in North Glasgow over 2 years. Clinical variables that had significant associations with admission on logistic regression were entered into a mixed-effects multiple logistic model. This provided weightings for the score, which was then simplified and tested on a separate validation group by receiving operator characteristic (ROC) analysis and goodness-of-fit tests. 215 231 presentations were used for model derivation and 107 615 for validation. Variables in the final model showing clinically and statistically significant associations with admission were: triage category, age, National Early Warning Score (NEWS), arrival by ambulance, referral source and admission within the last year. The resulting 6-variable score showed excellent admission/discharge discrimination (area under ROC curve 0.8774, 95% CI 0.8752 to 0.8796). Higher scores also predicted early returns for those who were discharged: the odds of subsequent admission within 28 days doubled for every 7-point increase (log odds=+0.0933 per point, p<0.0001). This simple, 6-variable score accurately estimates the probability of admission purely from triage information. Most patients could accurately be assigned to 'admission likely', 'admission unlikely', 'admission very unlikely' etc., by setting appropriate cut-offs. This could have uses in patient streaming, bed management and decision support. It also has the potential to control for demographics when comparing performance over time or between departments. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Patient Stratification Using Electronic Health Records from a Chronic Disease Management Program.

PubMed

Chen, Robert; Sun, Jimeng; Dittus, Robert S; Fabbri, Daniel; Kirby, Jacqueline; Laffer, Cheryl L; McNaughton, Candace D; Malin, Bradley

2016-01-04

The goal of this study is to devise a machine learning framework to assist care coordination programs in prognostic stratification to design and deliver personalized care plans and to allocate financial and medical resources effectively. This study is based on a de-identified cohort of 2,521 hypertension patients from a chronic care coordination program at the Vanderbilt University Medical Center. Patients were modeled as vectors of features derived from electronic health records (EHRs) over a six-year period. We applied a stepwise regression to identify risk factors associated with a decrease in mean arterial pressure of at least 2 mmHg after program enrollment. The resulting features were subsequently validated via a logistic regression classifier. Finally, risk factors were applied to group the patients through model-based clustering. We identified a set of predictive features that consisted of a mix of demographic, medication, and diagnostic concepts. Logistic regression over these features yielded an area under the ROC curve (AUC) of 0.71 (95% CI: [0.67, 0.76]). Based on these features, four clinically meaningful groups are identified through clustering - two of which represented patients with more severe disease profiles, while the remaining represented patients with mild disease profiles. Patients with hypertension can exhibit significant variation in their blood pressure control status and responsiveness to therapy. Yet this work shows that a clustering analysis can generate more homogeneous patient groups, which may aid clinicians in designing and implementing customized care programs. The study shows that predictive modeling and clustering using EHR data can be beneficial for providing a systematic, generalized approach for care providers to tailor their management approach based upon patient-level factors.

Linear Logistic Test Modeling with R

ERIC Educational Resources Information Center

Baghaei, Purya; Kubinger, Klaus D.

2015-01-01

The present paper gives a general introduction to the linear logistic test model (Fischer, 1973), an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014) functions to estimate the model and interpret its parameters. The…

Cancer patient experience, hospital performance and case mix: evidence from England.

PubMed

Abel, Gary A; Saunders, Catherine L; Lyratzopoulos, Georgios

2014-01-01

  This study aims to explore differences between crude and case mix-adjusted estimates of hospital performance with respect to the experience of cancer patients. This study analyzed the English 2011/2012 Cancer Patient Experience Survey covering all English National Health Service hospitals providing cancer treatment (n = 160). Logistic regression analysis was used to predict hospital performance for each of the 64 evaluative questions, adjusting for age, gender, ethnic group and cancer diagnosis. The degree of reclassification was explored across three categories (bottom 20%, middle 60% and top 20% of hospitals). There was high concordance between crude and adjusted ranks of hospitals (median Kendall's τ = 0.84; interquartile range: 0.82-0.88). Across all questions, a median of 5.0% (eight) of hospitals (interquartile range: 3.8-6.4%; six to ten hospitals) moved out of the extreme performance categories after case mix adjustment. In this context, patient case mix has only a small impact on measured hospital performance for cancer patient experience.

Turnover, staffing, skill mix, and resident outcomes in a national sample of US nursing homes.

PubMed

Trinkoff, Alison M; Han, Kihye; Storr, Carla L; Lerner, Nancy; Johantgen, Meg; Gartrell, Kyungsook

2013-12-01

The authors examined the relationship of staff turnover to selected nursing home quality outcomes, in the context of staffing and skill mix. Staff turnover is a serious concern in nursing homes as it has been found to adversely affect care. When employee turnover is minimized, better care quality is more likely in nursing homes. Data from the National Nursing Home Survey, a nationally representative sample of US nursing homes, were linked to Nursing Home Compare quality outcomes and analyzed using logistic regression. Nursing homes with high certified nursing assistant turnover had significantly higher odds of pressure ulcers, pain, and urinary tract infections even after controlling for staffing, skill mix, bed size, and ownership. Nurse turnover was associated with twice the odds of pressure ulcers, although this was attenuated when staffing was controlled. This study suggests turnover may be more important in explaining nursing home (NH) outcomes than staffing and skill mix and should therefore be given greater emphasis.

Estimation of key parameters in adaptive neuron model according to firing patterns based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yuan, Chunhua; Wang, Jiang; Yi, Guosheng

2017-03-01

Estimation of ion channel parameters is crucial to spike initiation of neurons. The biophysical neuron models have numerous ion channel parameters, but only a few of them play key roles in the firing patterns of the models. So we choose three parameters featuring the adaptation in the Ermentrout neuron model to be estimated. However, the traditional particle swarm optimization (PSO) algorithm is still easy to fall into local optimum and has the premature convergence phenomenon in the study of some problems. In this paper, we propose an improved method that uses a concave function and dynamic logistic chaotic mapping mixed to adjust the inertia weights of the fitness value, effectively improve the global convergence ability of the algorithm. The perfect predicting firing trajectories of the rebuilt model using the estimated parameters prove that only estimating a few important ion channel parameters can establish the model well and the proposed algorithm is effective. Estimations using two classic PSO algorithms are also compared to the improved PSO to verify that the algorithm proposed in this paper can avoid local optimum and quickly converge to the optimal value. The results provide important theoretical foundations for building biologically realistic neuron models.

Conservative management or gamma knife radiosurgery for vestibular schwannoma: tumor growth, symptoms, and quality of life.

PubMed

Breivik, Cathrine Nansdal; Nilsen, Roy Miodini; Myrseth, Erling; Pedersen, Paal Henning; Varughese, Jobin K; Chaudhry, Aqeel Asghar; Lund-Johansen, Morten

2013-07-01

There are few reports about the course of vestibular schwannoma (VS) patients following gamma knife radiosurgery (GKRS) compared with the course following conservative management (CM). In this study, we present prospectively collected data of 237 patients with unilateral VS extending outside the internal acoustic canal who received either GKRS (113) or CM (124). The aim was to measure the effect of GKRS compared with the natural course on tumor growth rate and hearing loss. Secondary end points were postinclusion additional treatment, quality of life (QoL), and symptom development. The patients underwent magnetic resonance imaging scans, clinical examination, and QoL assessment by SF-36 questionnaire. Statistics were performed by using Spearman correlation coefficient, Kaplan-Meier plot, Poisson regression model, mixed linear regression models, and mixed logistic regression models. Mean follow-up time was 55.0 months (26.1 standard deviation, range 10-132). Thirteen patients were lost to follow-up. Serviceable hearing was lost in 54 of 71 (76%) (CM) and 34 of 53 (64%) (GKRS) patients during the study period (not significant, log-rank test). There was a significant reduction in tumor volume over time in the GKRS group. The need for treatment following initial GKRS or CM differed at highly significant levels (log-rank test, P < .001). Symptom and QoL development did not differ significantly between the groups. In VS patients, GKRS reduces the tumor growth rate and thereby the incidence rate of new treatment about tenfold. Hearing is lost at similar rates in both groups. Symptoms and QoL seem not to be significantly affected by GKRS.

CERAMIC: Case-Control Association Testing in Samples with Related Individuals, Based on Retrospective Mixed Model Analysis with Adjustment for Covariates

PubMed Central

Zhong, Sheng; McPeek, Mary Sara

2016-01-01

We consider the problem of genetic association testing of a binary trait in a sample that contains related individuals, where we adjust for relevant covariates and allow for missing data. We propose CERAMIC, an estimating equation approach that can be viewed as a hybrid of logistic regression and linear mixed-effects model (LMM) approaches. CERAMIC extends the recently proposed CARAT method to allow samples with related individuals and to incorporate partially missing data. In simulations, we show that CERAMIC outperforms existing LMM and generalized LMM approaches, maintaining high power and correct type 1 error across a wider range of scenarios. CERAMIC results in a particularly large power increase over existing methods when the sample includes related individuals with some missing data (e.g., when some individuals with phenotype and covariate information have missing genotype), because CERAMIC is able to make use of the relationship information to incorporate partially missing data in the analysis while correcting for dependence. Because CERAMIC is based on a retrospective analysis, it is robust to misspecification of the phenotype model, resulting in better control of type 1 error and higher power than that of prospective methods, such as GMMAT, when the phenotype model is misspecified. CERAMIC is computationally efficient for genomewide analysis in samples of related individuals of almost any configuration, including small families, unrelated individuals and even large, complex pedigrees. We apply CERAMIC to data on type 2 diabetes (T2D) from the Framingham Heart Study. In a genome scan, 9 of the 10 smallest CERAMIC p-values occur in or near either known T2D susceptibility loci or plausible candidates, verifying that CERAMIC is able to home in on the important loci in a genome scan. PMID:27695091

The association of shift-level nurse staffing with adverse patient events.

PubMed

Patrician, Patricia A; Loan, Lori; McCarthy, Mary; Fridman, Moshe; Donaldson, Nancy; Bingham, Mona; Brosch, Laura R

2011-02-01

The objective of this study was to demonstrate the association between nurse staffing and adverse events at the shift level. Despite a growing body of research linking nurse staffing and patient outcomes, the relationship of staffing to patient falls and medication errors remains equivocal, possibly due to dependence on aggregated data. Thirteen military hospitals participated in creating a longitudinal nursing outcomes database to monitor nurse staffing, patient falls and medication errors, and other outcomes. Unit types were analyzed separately to stratify patient and nurse staffing characteristics. Bayesian hierarchical logistic regression modeling was used to examine associations between staffing and adverse events. RN skill mix, total nursing care hours, and experience, measured by a proxy variable, were associated with shift-level adverse events. Consideration must be given to nurse staffing and experience levels on every shift.

A mixing timescale model for TPDF simulations of turbulent premixed flames

DOE PAGES

Kuron, Michael; Ren, Zhuyin; Hawkes, Evatt R.; ...

2017-02-06

Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priorimore » assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. Here, the new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure. It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. Furthermore, the EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive scalar mixing across different flame regimes are appropriately accounted for.« less

A mixing timescale model for TPDF simulations of turbulent premixed flames

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

Kuron, Michael; Ren, Zhuyin; Hawkes, Evatt R.

Transported probability density function (TPDF) methods are an attractive modeling approach for turbulent flames as chemical reactions appear in closed form. However, molecular micro-mixing needs to be modeled and this modeling is considered a primary challenge for TPDF methods. In the present study, a new algebraic mixing rate model for TPDF simulations of turbulent premixed flames is proposed, which is a key ingredient in commonly used molecular mixing models. The new model aims to properly account for the transition in reactive scalar mixing rate behavior from the limit of turbulence-dominated mixing to molecular mixing behavior in flamelets. An a priorimore » assessment of the new model is performed using direct numerical simulation (DNS) data of a lean premixed hydrogen–air jet flame. The new model accurately captures the mixing timescale behavior in the DNS and is found to be a significant improvement over the commonly used constant mechanical-to-scalar mixing timescale ratio model. An a posteriori TPDF study is then performed using the same DNS data as a numerical test bed. The DNS provides the initial conditions and time-varying input quantities, including the mean velocity, turbulent diffusion coefficient, and modeled scalar mixing rate for the TPDF simulations, thus allowing an exclusive focus on the mixing model. Here, the new mixing timescale model is compared with the constant mechanical-to-scalar mixing timescale ratio coupled with the Euclidean Minimum Spanning Tree (EMST) mixing model, as well as a laminar flamelet closure. It is found that the laminar flamelet closure is unable to properly capture the mixing behavior in the thin reaction zones regime while the constant mechanical-to-scalar mixing timescale model under-predicts the flame speed. Furthermore, the EMST model coupled with the new mixing timescale model provides the best prediction of the flame structure and flame propagation among the models tested, as the dynamics of reactive scalar mixing across different flame regimes are appropriately accounted for.« less

Assessing map accuracy in a remotely sensed, ecoregion-scale cover map

USGS Publications Warehouse

Edwards, T.C.; Moisen, Gretchen G.; Cutler, D.R.

1998-01-01

Landscape- and ecoregion-based conservation efforts increasingly use a spatial component to organize data for analysis and interpretation. A challenge particular to remotely sensed cover maps generated from these efforts is how best to assess the accuracy of the cover maps, especially when they can exceed 1000 s/km2 in size. Here we develop and describe a methodological approach for assessing the accuracy of large-area cover maps, using as a test case the 21.9 million ha cover map developed for Utah Gap Analysis. As part of our design process, we first reviewed the effect of intracluster correlation and a simple cost function on the relative efficiency of cluster sample designs to simple random designs. Our design ultimately combined clustered and subsampled field data stratified by ecological modeling unit and accessibility (hereafter a mixed design). We next outline estimation formulas for simple map accuracy measures under our mixed design and report results for eight major cover types and the three ecoregions mapped as part of the Utah Gap Analysis. Overall accuracy of the map was 83.2% (SE=1.4). Within ecoregions, accuracy ranged from 78.9% to 85.0%. Accuracy by cover type varied, ranging from a low of 50.4% for barren to a high of 90.6% for man modified. In addition, we examined gains in efficiency of our mixed design compared with a simple random sample approach. In regard to precision, our mixed design was more precise than a simple random design, given fixed sample costs. We close with a discussion of the logistical constraints facing attempts to assess the accuracy of large-area, remotely sensed cover maps.

Using Dominance Analysis to Determine Predictor Importance in Logistic Regression

ERIC Educational Resources Information Center

Azen, Razia; Traxel, Nicole

2009-01-01

This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…

Logistics of a Lunar Based Solar Power Satellite Scenario

NASA Technical Reports Server (NTRS)

Melissopoulos, Stefanos

1995-01-01

A logistics system comprised of two orbital stations for the support of a 500 GW space power satellite scenario in a geostationary orbit was investigated in this study. A subsystem mass model, a mass flow model and a life cycle cost model were developed. The results regarding logistics cost and burden rates show that the transportation cost contributed the most (96%) to the overall cost of the scenario. The orbital stations at a geostationary and at a lunar orbit contributed 4 % to that cost.

Insulin resistance is associated with carotid intima-media thickness in non-diabetic subjects. A cross-sectional analysis of the ELSA-Brasil cohort baseline.

PubMed

Santos, Itamar S; Bittencourt, Márcio S; Goulart, Alessandra C; Schmidt, Maria Inês; Diniz, Maria de Fátima H S; Lotufo, Paulo A; Benseñor, Isabela M

2017-05-01

Epidemiological studies have analyzed the association between carotid intima-media thickness (CIMT) and insulin resistance, glucose levels or glycated hemoglobin with mixed results. We aimed to evaluate the association between CIMT and homeostasis model assessment - insulin resistance (HOMA-IR), fasting and post-load plasma glucose and glycated hemoglobin in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline. We included 8028 participants (aged 35-74 years) without diabetes or overt cardiovascular disease who had complete CIMT data at baseline. We built crude and adjusted linear and binary logistic models to evaluate the association between CIMT and (a) HOMA-IR; (b) fasting plasma glucose; (c) post-load plasma glucose; and (d) glycated hemoglobin. We also built post-hoc models, stratified by sex. In the fully-adjusted linear models, only the association between CIMT (in mm) and HOMA-IR remained significant (β = 0.004; 95% confidence interval [95%CI]:0.001 to 0.006). Consistent with these results, only the association between the highest age- sex- and race-specific CIMT quartile and HOMA-IR was significant in the adjusted logistic model (odds ratio [OR]:1.10; 95% CI:1.04-1.17). The association between HOMA-IR and the highest CIMT quartile remained significant in sex-specific analyses (OR:1.10; 95% CI:1.02-1.20 for men and OR:1.10; 95% CI:1.02-1.20 for women). We did not find an independent association between CIMT and glucose or glycated hemoglobin. We found a direct association between HOMA-IR and CIMT in a large sample of non-diabetic participants. Mechanisms unrelated to glucose homeostasis, as a direct effect of insulin on atherosclerosis, or medial hypertrophy, may be involved. Copyright © 2017 Elsevier B.V. All rights reserved.

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

PubMed

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

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.

An integrative fuzzy Kansei engineering and Kano model for logistics services

NASA Astrophysics Data System (ADS)

Hartono, M.; Chuan, T. K.; Prayogo, D. N.; Santoso, A.

2017-11-01

Nowadays, customer emotional needs (known as Kansei) in product and especially in services become a major concern. One of the emerging services is the logistics services. In obtaining a global competitive advantage, logistics services should understand and satisfy their customer affective impressions (Kansei). How to capture, model and analyze the customer emotions has been well structured by Kansei Engineering, equipped with Kano model to strengthen its methodology. However, its methodology lacks of the dynamics of customer perception. More specifically, there is a criticism of perceived scores on user preferences, in both perceived service quality and Kansei response, whether they represent an exact numerical value. Thus, this paper is proposed to discuss an approach of fuzzy Kansei in logistics service experiences. A case study in IT-based logistics services involving 100 subjects has been conducted. Its findings including the service gaps accompanied with prioritized improvement initiatives are discussed.

Logistics, electronic commerce, and the environment

NASA Astrophysics Data System (ADS)

Sarkis, Joseph; Meade, Laura; Talluri, Srinivas

2002-02-01

Organizations realize that a strong supporting logistics or electronic logistics (e-logistics) function is important from both commercial and consumer perspectives. The implications of e-logistics models and practices cover the forward and reverse logistics functions of organizations. They also have direct and profound impact on the natural environment. This paper will focus on a discussion of forward and reverse e-logistics and their relationship to the natural environment. After discussion of the many pertinent issues in these areas, directions of practice and implications for study and research are then described.

Binary logistic regression-Instrument for assessing museum indoor air impact on exhibits.

PubMed

Bucur, Elena; Danet, Andrei Florin; Lehr, Carol Blaziu; Lehr, Elena; Nita-Lazar, Mihai

2017-04-01

This paper presents a new way to assess the environmental impact on historical artifacts using binary logistic regression. The prediction of the impact on the exhibits during certain pollution scenarios (environmental impact) was calculated by a mathematical model based on the binary logistic regression; it allows the identification of those environmental parameters from a multitude of possible parameters with a significant impact on exhibitions and ranks them according to their severity effect. Air quality (NO 2 , SO 2 , O 3 and PM 2.5 ) and microclimate parameters (temperature, humidity) monitoring data from a case study conducted within exhibition and storage spaces of the Romanian National Aviation Museum Bucharest have been used for developing and validating the binary logistic regression method and the mathematical model. The logistic regression analysis was used on 794 data combinations (715 to develop of the model and 79 to validate it) by a Statistical Package for Social Sciences (SPSS 20.0). The results from the binary logistic regression analysis demonstrated that from six parameters taken into consideration, four of them present a significant effect upon exhibits in the following order: O 3 >PM 2.5 >NO 2 >humidity followed at a significant distance by the effects of SO 2 and temperature. The mathematical model, developed in this study, correctly predicted 95.1 % of the cumulated effect of the environmental parameters upon the exhibits. Moreover, this model could also be used in the decisional process regarding the preventive preservation measures that should be implemented within the exhibition space. The paper presents a new way to assess the environmental impact on historical artifacts using binary logistic regression. The mathematical model developed on the environmental parameters analyzed by the binary logistic regression method could be useful in a decision-making process establishing the best measures for pollution reduction and preventive preservation of exhibits.

Modelling biological Cr(VI) reduction in aquifer microcosm column systems.

PubMed

Molokwane, Pulane E; Chirwa, Evans M N

2013-01-01

Several chrome processing facilities in South Africa release hexavalent chromium (Cr(VI)) into groundwater resources. Pump-and-treat remediation processes have been implemented at some of the sites but have not been successful in reducing contamination levels. The current study is aimed at developing an environmentally friendly, cost-effective and self-sustained biological method to curb the spread of chromium at the contaminated sites. An indigenous Cr(VI)-reducing mixed culture of bacteria was demonstrated to reduce high levels of Cr(VI) in laboratory samples. The effect of Cr(VI) on the removal rate was evaluated at concentrations up to 400 mg/L. Following the detailed evaluation of fundamental processes for biological Cr(VI) reduction, a predictive model for Cr(VI) breakthrough through aquifer microcosm reactors was developed. The reaction rate in batch followed non-competitive rate kinetics with a Cr(VI) inhibition threshold concentration of approximately 99 mg/L. This study evaluates the application of the kinetic parameters determined in the batch reactors to the continuous flow process. The model developed from advection-reaction rate kinetics in a porous media fitted best the effluent Cr(VI) concentration. The model was also used to elucidate the logistic nature of biomass growth in the reactor systems.

Accounting for Slipping and Other False Negatives in Logistic Models of Student Learning

ERIC Educational Resources Information Center

MacLellan, Christopher J.; Liu, Ran; Koedinger, Kenneth R.

2015-01-01

Additive Factors Model (AFM) and Performance Factors Analysis (PFA) are two popular models of student learning that employ logistic regression to estimate parameters and predict performance. This is in contrast to Bayesian Knowledge Tracing (BKT) which uses a Hidden Markov Model formalism. While all three models tend to make similar predictions,…

Some Observations on the Identification and Interpretation of the 3PL IRT Model

ERIC Educational Resources Information Center

Azevedo, Caio Lucidius Naberezny

2009-01-01

The paper by Maris, G., & Bechger, T. (2009) entitled, "On the Interpreting the Model Parameters for the Three Parameter Logistic Model," addressed two important questions concerning the three parameter logistic (3PL) item response theory (IRT) model (and in a broader sense, concerning all IRT models). The first one is related to the model…

A High Resolution Ammunition Resupply Model.

DTIC Science & Technology

1982-03-01

LOU ............... 104 3. Requests for Resupply . . ........ 108 a. Weapon Systems . . . . . . . . . . . . 108 b. Platoon . ... 109 c. Company...essence, the fundamental question, "Can it be done?", is never adequately answered. B. LOGISTICS MODELS Current logistics models then, although...19 .._ " Development of a detailed model that responds to requests for ammunition resupply, maintains a simplified stockage system , and models the

Reverse logistics system planning for recycling computers hardware: A case study

NASA Astrophysics Data System (ADS)

Januri, Siti Sarah; Zulkipli, Faridah; Zahari, Siti Meriam; Shamsuri, Siti Hajar

2014-09-01

This paper describes modeling and simulation of reverse logistics networks for collection of used computers in one of the company in Selangor. The study focuses on design of reverse logistics network for used computers recycling operation. Simulation modeling, presented in this work allows the user to analyze the future performance of the network and to understand the complex relationship between the parties involved. The findings from the simulation suggest that the model calculates processing time and resource utilization in a predictable manner. In this study, the simulation model was developed by using Arena simulation package.

Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models.

PubMed

Lin, Chao-Cheng; Bai, Ya-Mei; Chen, Jen-Yeu; Hwang, Tzung-Jeng; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

2010-03-01

Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. A total of 383 patients with a diagnosis of schizophrenia or schizoaffective disorder (DSM-IV criteria) with SGA treatment for more than 6 months were investigated to determine whether they met the MetS criteria according to the International Diabetes Federation. The data for these patients were collected between March 2005 and September 2005. The input variables of ANN and logistic regression were limited to demographic and anthropometric data only. All models were trained by randomly selecting two-thirds of the patient data and were internally validated with the remaining one-third of the data. The models were then externally validated with data from 69 patients from another hospital, collected between March 2008 and June 2008. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of all models. Both the final ANN and logistic regression models had high accuracy (88.3% vs 83.6%), sensitivity (93.1% vs 86.2%), and specificity (86.9% vs 83.8%) to identify MetS in the internal validation set. The mean +/- SD AUC was high for both the ANN and logistic regression models (0.934 +/- 0.033 vs 0.922 +/- 0.035, P = .63). During external validation, high AUC was still obtained for both models. Waist circumference and diastolic blood pressure were the common variables that were left in the final ANN and logistic regression models. Our study developed accurate ANN and logistic regression models to detect MetS in patients with SGA treatment. The models are likely to provide a noninvasive tool for large-scale screening of MetS in this group of patients. (c) 2010 Physicians Postgraduate Press, Inc.

Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint

PubMed Central

Wang, Songyi; Tao, Fengming; Shi, Yuhe

2018-01-01

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location–routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network. PMID:29316639

An inexact reverse logistics model for municipal solid waste management systems.

PubMed

Zhang, Yi Mei; Huang, Guo He; He, Li

2011-03-01

This paper proposed an inexact reverse logistics model for municipal solid waste management systems (IRWM). Waste managers, suppliers, industries and distributors were involved in strategic planning and operational execution through reverse logistics management. All the parameters were assumed to be intervals to quantify the uncertainties in the optimization process and solutions in IRWM. To solve this model, a piecewise interval programming was developed to deal with Min-Min functions in both objectives and constraints. The application of the model was illustrated through a classical municipal solid waste management case. With different cost parameters for landfill and the WTE, two scenarios were analyzed. The IRWM could reflect the dynamic and uncertain characteristics of MSW management systems, and could facilitate the generation of desired management plans. The model could be further advanced through incorporating methods of stochastic or fuzzy parameters into its framework. Design of multi-waste, multi-echelon, multi-uncertainty reverse logistics model for waste management network would also be preferred. Copyright © 2010 Elsevier Ltd. All rights reserved.

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…

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.

MESSOC capabilities and results. [Model for Estimating Space Station Opertions Costs

NASA Technical Reports Server (NTRS)

Shishko, Robert

1990-01-01

MESSOC (Model for Estimating Space Station Operations Costs) is the result of a multi-year effort by NASA to understand and model the mature operations cost of Space Station Freedom. This paper focuses on MESSOC's ability to contribute to life-cycle cost analyses through its logistics equations and databases. Together, these afford MESSOC the capability to project not only annual logistics costs for a variety of Space Station scenarios, but critical non-cost logistics results such as annual Station maintenance crewhours, upweight/downweight, and on-orbit sparing availability as well. MESSOC results using current logistics databases and baseline scenario have already shown important implications for on-orbit maintenance approaches, space transportation systems, and international operations cost sharing.

Requirement analysis for the one-stop logistics management of fresh agricultural products

NASA Astrophysics Data System (ADS)

Li, Jun; Gao, Hongmei; Liu, Yuchuan

2017-08-01

Issues and concerns for food safety, agro-processing, and the environmental and ecological impact of food production have been attracted many research interests. Traceability and logistics management of fresh agricultural products is faced with the technological challenges including food product label and identification, activity/process characterization, information systems for the supply chain, i.e., from farm to table. Application of one-stop logistics service focuses on the whole supply chain process integration for fresh agricultural products is studied. A collaborative research project for the supply and logistics of fresh agricultural products in Tianjin was performed. Requirement analysis for the one-stop logistics management information system is studied. The model-driven business transformation, an approach uses formal models to explicitly define the structure and behavior of a business, is applied for the review and analysis process. Specific requirements for the logistic management solutions are proposed. Development of this research is crucial for the solution of one-stop logistics management information system integration platform for fresh agricultural products.

Two models for evaluating landslide hazards

USGS Publications Warehouse

Davis, J.C.; Chung, C.-J.; Ohlmacher, G.C.

2006-01-01

Two alternative procedures for estimating landslide hazards were evaluated using data on topographic digital elevation models (DEMs) and bedrock lithologies in an area adjacent to the Missouri River in Atchison County, Kansas, USA. The two procedures are based on the likelihood ratio model but utilize different assumptions. The empirical likelihood ratio model is based on non-parametric empirical univariate frequency distribution functions under an assumption of conditional independence while the multivariate logistic discriminant model assumes that likelihood ratios can be expressed in terms of logistic functions. The relative hazards of occurrence of landslides were estimated by an empirical likelihood ratio model and by multivariate logistic discriminant analysis. Predictor variables consisted of grids containing topographic elevations, slope angles, and slope aspects calculated from a 30-m DEM. An integer grid of coded bedrock lithologies taken from digitized geologic maps was also used as a predictor variable. Both statistical models yield relative estimates in the form of the proportion of total map area predicted to already contain or to be the site of future landslides. The stabilities of estimates were checked by cross-validation of results from random subsamples, using each of the two procedures. Cell-by-cell comparisons of hazard maps made by the two models show that the two sets of estimates are virtually identical. This suggests that the empirical likelihood ratio and the logistic discriminant analysis models are robust with respect to the conditional independent assumption and the logistic function assumption, respectively, and that either model can be used successfully to evaluate landslide hazards. ?? 2006.

An Extension of the Concept of Specific Objectivity.

ERIC Educational Resources Information Center

Irtel, Hans

1995-01-01

Comparisons of subjects are specifically objective if they do not depend on the items involved. Such comparisons are not restricted to the one-parameter logistic latent trait model but may also be defined within ordinal independence models and even within the two-parameter logistic model. (Author)

Artificial neural networks predict the incidence of portosplenomesenteric venous thrombosis in patients with acute pancreatitis.

PubMed

Fei, Y; Hu, J; Li, W-Q; Wang, W; Zong, G-Q

2017-03-01

Essentials Predicting the occurrence of portosplenomesenteric vein thrombosis (PSMVT) is difficult. We studied 72 patients with acute pancreatitis. Artificial neural networks modeling was more accurate than logistic regression in predicting PSMVT. Additional predictive factors may be incorporated into artificial neural networks. Objective To construct and validate artificial neural networks (ANNs) for predicting the occurrence of portosplenomesenteric venous thrombosis (PSMVT) and compare the predictive ability of the ANNs with that of logistic regression. Methods The ANNs and logistic regression modeling were constructed using simple clinical and laboratory data of 72 acute pancreatitis (AP) patients. The ANNs and logistic modeling were first trained on 48 randomly chosen patients and validated on the remaining 24 patients. The accuracy and the performance characteristics were compared between these two approaches by SPSS17.0 software. Results The training set and validation set did not differ on any of the 11 variables. After training, the back propagation network training error converged to 1 × 10 -20 , and it retained excellent pattern recognition ability. When the ANNs model was applied to the validation set, it revealed a sensitivity of 80%, specificity of 85.7%, a positive predictive value of 77.6% and negative predictive value of 90.7%. The accuracy was 83.3%. Differences could be found between ANNs modeling and logistic regression modeling in these parameters (10.0% [95% CI, -14.3 to 34.3%], 14.3% [95% CI, -8.6 to 37.2%], 15.7% [95% CI, -9.9 to 41.3%], 11.8% [95% CI, -8.2 to 31.8%], 22.6% [95% CI, -1.9 to 47.1%], respectively). When ANNs modeling was used to identify PSMVT, the area under receiver operating characteristic curve was 0.849 (95% CI, 0.807-0.901), which demonstrated better overall properties than logistic regression modeling (AUC = 0.716) (95% CI, 0.679-0.761). Conclusions ANNs modeling was a more accurate tool than logistic regression in predicting the occurrence of PSMVT following AP. More clinical factors or biomarkers may be incorporated into ANNs modeling to improve its predictive ability. © 2016 International Society on Thrombosis and Haemostasis.

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…

Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

PubMed

Schmidt, Amand F; Klungel, Olaf H; Groenwold, Rolf H H

2016-01-01

Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

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.

Prevalence, Risk Factors and Consequent Effect of Dystocia in Holstein Dairy Cows in Iran

PubMed Central

Atashi, Hadi; Abdolmohammadi, Alireza; Dadpasand, Mohammad; Asaadi, Anise

2012-01-01

The objective of this research was to determine the prevalence, risk factors and consequent effect of dystocia on lactation performance in Holstein dairy cows in Iran. The data set consisted of 55,577 calving records on 30,879 Holstein cows in 30 dairy herds for the period March 2000 to April 2009. Factors affecting dystocia were analyzed using multivariable logistic regression models through the maximum likelihood method in the GENMOD procedure. The effect of dystocia on lactation performance and factors affecting calf birth weight were analyzed using mixed linear model in the MIXED procedure. The average incidence of dystocia was 10.8% and the mean (SD) calf birth weight was 42.13 (5.42) kg. Primiparous cows had calves with lower body weight and were more likely to require assistance at parturition (p<0.05). Female calves had lower body weight, and had a lower odds ratio for dystocia than male calves (p<0.05). Twins had lower birth weight, and had a higher odds ratio for dystocia than singletons (p<0.05). Cows which gave birth to a calf with higher weight at birth experienced more calving difficulty (OR (95% CI) = 1.1(1.08–1.11). Total 305-d milk, fat and protein yield was 135 (23), 3.16 (0.80) and 6.52 (1.01) kg less, in cows that experienced dystocia at calving compared with those that did not (p<0.05). PMID:25049584

The Association Between Sexual Health and Physical, Mental, and Social Health in Adolescent Women.

PubMed

Hensel, Devon J; Nance, Jennifer; Fortenberry, J Dennis

2016-10-01

Developmental models link sexual well-being to physical, mental/emotional, and social well-being, yet little empirical literature evaluates these relationships in adolescents. Better understanding of how and when sexuality complements other aspects of health may yield important points to enhance existing health education and prevention efforts. Data were drawn from a 10-year longitudinal cohort study of sexual relationships and sexual behavior among adolescent women (N = 387; 14-17 years at enrollment). Sexual health data were drawn from quarterly partner-specific interviews and were linked to physical, mental/emotional, and social health information in annual questionnaires. Random intercept, mixed effects linear, ordinal logistic, or binary logistic regression were used to estimate the influence of sexual health on health and well-being outcomes (Stata, v.23, StataCorp, College Station, TX). All models controlled for participant age and race/ethnicity. Higher sexual health was significantly associated with less frequent nicotine and substance use, lower self-reported depression, lower thrill seeking, higher self-esteem, having fewer friends who use substances, higher religiosity, better social integration, lower frequency of delinquent behavior and crime, and more frequent community group membership. Sexual health was not associated with the number of friends who used cigarettes. Positive sexually related experiences in romantic relationships during adolescence may complement physical, mental/emotional, and social health. Addressing specific aspects of healthy sexual development during clinical encounters could dually help primary prevention and health education address other common adolescent health issues. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Implementation of Advanced Warehouses in a Hospital Environment - Case study

NASA Astrophysics Data System (ADS)

Costa, J.; Sameiro Carvalho, M.; Nobre, A.

2015-05-01

In Portugal, there is an increase of costs in the healthcare sector due to several factors such as the aging of the population, the increased demand for health care services and the increasing investment in new technologies. Thus, there is a need to reduce costs, by presenting the effective and efficient management of logistics supply systems with enormous potential to achieve savings in health care organizations without compromising the quality of the provided service, which is a critical factor, in this type of sector. In this research project the implementation of Advanced Warehouses has been studied, in the Hospital de Braga patient care units, based in a mix of replenishment systems approaches: the par level system, the two bin system and the consignment model. The logistics supply process is supported by information technology (IT), allowing a proactive replacement of products, based on the hospital services consumption records. The case study was developed in two patient care units, in order to study the impact of the operation of the three replenishment systems. Results showed that an important inventory holding costs reduction can be achieved in the patient care unit warehouses while increasing the service level and increasing control of incoming and stored materials with less human resources. The main conclusion of this work illustrates the possibility of operating multiple replenishment models, according to the types of materials that healthcare organizations deal with, so that they are able to provide quality health care services at a reduced cost and economically sustainable. The adoption of adequate IT has been shown critical for the success of the project.

The relationship between quality of work life and location of cross-training among obstetric nurses in urban northeastern Ontario, Canada: A population-based cross sectional study.

PubMed

Nowrouzi, Behdin; Lightfoot, Nancy; Carter, Lorraine; Larivière, Michel; Rukholm, Ellen; Schinke, Robert; Belanger-Gardner, Diane

2015-01-01

The purpose of this mixed methods study was to examine the quality of work life of registered nurses working in obstetrics at 4 hospitals in northeastern Ontario and explore demographic and occupational factors related to nurses' quality of work life (QWL). A stratified random sample of registered nurses (N = 111) selected from the 138 eligible registered nurses (80.4%) of staff in the labor, delivery, recovery, and postpartum areas at the 4 hospitals participated. Logistic regression analyses were used to consider QWL in relation to the following: 1) demographic factors, and 2) stress, employment status and educational attainment. In the logistic regression model, the odds of a higher quality of work life for nurses who were cross trained (nurses who can work across all areas of obstetrical care) were estimated to be 3.82 (odds ratio = 3.82, 95% confidence interval: 1.01-14.5) times the odds of a higher quality of work life for nurses who were not cross trained. This study highlights a relationship between quality of work life and associated factors including location of cross-training among obstetrical nurses in northeastern Ontario. These findings are supported by the qualitative interviews that examine in depth their relationship to QWL. Given the limited number of employment opportunities in the rural and remote regions, it is paramount that employers and employees work closely together in creating positive environments that promote nurses' QWL. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

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…

Predicting risk for portal vein thrombosis in acute pancreatitis patients: A comparison of radical basis function artificial neural network and logistic regression models.

PubMed

Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei

2017-06-01

To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (P<0.05). In addition, a comparison of the area under receiver operating characteristic curves of the two models showed a statistically significant difference (P<0.05). The RBF ANNs model is more likely to predict the occurrence of PVT induced by AP than logistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Scenario analysis and disaster preparedness for port and maritime logistics risk management.

PubMed

Kwesi-Buor, John; Menachof, David A; Talas, Risto

2016-08-01

System Dynamics (SD) modelling is used to investigate the impacts of policy interventions on industry actors' preparedness to mitigate risks and to recover from disruptions along the maritime logistics and supply chain network. The model suggests a bi-directional relation between regulation and industry actors' behaviour towards Disaster Preparedness (DP) in maritime logistics networks. The model also showed that the level of DP is highly contingent on forecast accuracy, technology change, attitude to risk prevention, port activities, and port environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

An analysis of respondent-driven sampling with injecting drug users in a high HIV prevalent state of India.

PubMed

Phukan, Sanjib Kumar; Medhi, Gajendra Kumar; Mahanta, Jagadish; Adhikary, Rajatashuvra; Thongamba, Gay; Paranjape, Ramesh S; Akoijam, Brogen S

2017-07-03

Personal networks are significant social spaces to spread of HIV or other blood-borne infections among hard-to-reach population, viz., injecting drug users, female sex workers, etc. Sharing of infected needles or syringes among drug users is one of the major routes of HIV transmission in Manipur, a high HIV prevalence state in India. This study was carried out to describe the network characteristics and recruitment patterns of injecting drug users and to assess the association of personal network with injecting risky behaviors in Manipur. A total of 821 injecting drug users were recruited into the study using respondent-driven sampling (RDS) from Bishnupur and Churachandpur districts of Manipur; data on demographic characteristics, HIV risk behaviors, and network size were collected from them. Transition probability matrices and homophily indices were used to describe the network characteristics, and recruitment patterns of injecting drug users. Univariate and multivariate binary logistic regression models were performed to analyze the association between the personal networks and sharing of needles or syringes. The average network size was similar in both the districts. Recruitment analysis indicates injecting drug users were mostly engaged in mixed age group setting for injecting practice. Ever married and new injectors showed lack of in-group ties. Younger injecting drug users had mainly recruited older injecting drug users from their personal network. In logistic regression analysis, higher personal network was found to be significantly associated with increased likelihood of injecting risky behaviors. Because of mixed personal network of new injectors and higher network density associated with HIV exposure, older injecting drug users may act as a link for HIV transmission or other blood-borne infections to new injectors and also to their sexual partners. The information from this study may be useful to understanding the network pattern of injecting drug users for enriching the HIV prevention in this region.

Strategies on the Implementation of China's Logistics Information Network

NASA Astrophysics Data System (ADS)

Dong, Yahui; Li, Wei; Guo, Xuwen

The economic globalization and trend of e-commerce network have determined that the logistics industry will be rapidly developed in the 21st century. In order to achieve the optimal allocation of resources, a worldwide rapid and sound customer service system should be established. The establishment of a corresponding modern logistics system is the inevitable choice of this requirement. It is also the inevitable choice for the development of modern logistics industry in China. The perfect combination of modern logistics and information network can better promote the development of the logistics industry. Through the analysis of Status of Logistics Industry in China, this paper summed up the domestic logistics enterprise logistics information system in the building of some common problems. According to logistics information systems planning methods and principles set out logistics information system to optimize the management model.

Improved Operational Readiness through Environmental Stress Screening

DTIC Science & Technology

1987-11-01

Rhoades of Gru-,.:an’s Field Marketing Department, and the cooperation of the ni- merous Air Force logistics centers and operational facilities visited...EQUIPMENT AGE * ENVIRONMENTAL MAINTENANCE EFFECT PROFILES DtATA * TAILORING DEFINTION MET HOD1OLOGY I 1GUIDELINE oi FIELD ESS IMPLEMENTATION GUIDELINW...any mixing or mismatching appeared, the data was eliminated completely. Figure 5 provides the annual historical trends of each case history equipment

Supply Chain Management: How the Curricula of the Top Ten Undergraduate Universities Meet the Practitioners' Knowledge Set

ERIC Educational Resources Information Center

Bahouth, Saba; Hartmann, David; Willis, Geoff

2014-01-01

The disciplines of logistics and supply chain management have the potential of having many areas of emphasis. Universities that have some kind of emphasis in this field have developed programs that depend on the need of potential employers and their own faculty mix. Several studies have previously looked at how universities deal with this field at…

Ramsay-Curve Item Response Theory for the Three-Parameter Logistic Item Response Model

ERIC Educational Resources Information Center

Woods, Carol M.

2008-01-01

In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters of a unidimensional item response model using marginal maximum likelihood estimation. This study evaluates RC-IRT for the three-parameter logistic (3PL) model with comparisons to the normal model and to the empirical…

On Interpreting the Model Parameters for the Three Parameter Logistic Model

ERIC Educational Resources Information Center

Maris, Gunter; Bechger, Timo

2009-01-01

This paper addresses two problems relating to the interpretability of the model parameters in the three parameter logistic model. First, it is shown that if the values of the discrimination parameters are all the same, the remaining parameters are nonidentifiable in a nontrivial way that involves not only ability and item difficulty, but also the…

[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.

Farmers’ Intentions to Implement Foot and Mouth Disease Control Measures in Ethiopia

PubMed Central

Jemberu, Wudu T.; Mourits, M. C. M.; Hogeveen, H.

2015-01-01

The objectives of this study were to explore farmers’ intentions to implement foot and mouth disease (FMD) control in Ethiopia, and to identify perceptions about the disease and its control measures that influence these intentions using the Health Belief Model (HBM) framework. Data were collected using questionnaires from 293 farmers in three different production systems. The influence of perceptions on the intentions to implement control measures were analyzed using binary logistic regression. The effect of socio-demographic and husbandry variables on perceptions that were found to significantly influence the intentions were analyzed using ordinal logistic regression. Almost all farmers (99%) intended to implement FMD vaccination free of charge. The majority of farmers in the pastoral (94%) and market oriented (92%) systems also had the intention to implement vaccination with charge but only 42% of the crop-livestock mixed farmers had the intention to do so. Only 2% of pastoral and 18% of crop-livestock mixed farmers had the intention to implement herd isolation and animal movement restriction continuously. These proportions increased to 11% for pastoral and 50% for crop-livestock mixed farmers when the measure is applied only during an outbreak. The majority of farmers in the market oriented system (>80%) had the intention to implement herd isolation and animal movement restriction measure, both continuously and during an outbreak. Among the HBM perception constructs, perceived barrier was found to be the only significant predictor of the intention to implement vaccination. Perceived susceptibility, perceived benefit and perceived barrier were the significant predictors of the intention for herd isolation and animal movement restriction measure. In turn, the predicting perceived barrier on vaccination control varied significantly with the production system and the age of farmers. The significant HBM perception predictors on herd isolation and animal movement restriction control were significantly influenced only by the type of production system. The results of this study indicate that farmers’ intentions to apply FMD control measures are variable among production systems, an insight which is relevant in the development of future control programs. Promotion programs aimed at increasing farmers’ motivation to participate in FMD control by charged vaccination or animal movement restriction should give attention to the perceived barriers influencing the intentions to apply these measures. PMID:26375391

Farmers' Intentions to Implement Foot and Mouth Disease Control Measures in Ethiopia.

PubMed

Jemberu, Wudu T; Mourits, M C M; Hogeveen, H

2015-01-01

The objectives of this study were to explore farmers' intentions to implement foot and mouth disease (FMD) control in Ethiopia, and to identify perceptions about the disease and its control measures that influence these intentions using the Health Belief Model (HBM) framework. Data were collected using questionnaires from 293 farmers in three different production systems. The influence of perceptions on the intentions to implement control measures were analyzed using binary logistic regression. The effect of socio-demographic and husbandry variables on perceptions that were found to significantly influence the intentions were analyzed using ordinal logistic regression. Almost all farmers (99%) intended to implement FMD vaccination free of charge. The majority of farmers in the pastoral (94%) and market oriented (92%) systems also had the intention to implement vaccination with charge but only 42% of the crop-livestock mixed farmers had the intention to do so. Only 2% of pastoral and 18% of crop-livestock mixed farmers had the intention to implement herd isolation and animal movement restriction continuously. These proportions increased to 11% for pastoral and 50% for crop-livestock mixed farmers when the measure is applied only during an outbreak. The majority of farmers in the market oriented system (>80%) had the intention to implement herd isolation and animal movement restriction measure, both continuously and during an outbreak. Among the HBM perception constructs, perceived barrier was found to be the only significant predictor of the intention to implement vaccination. Perceived susceptibility, perceived benefit and perceived barrier were the significant predictors of the intention for herd isolation and animal movement restriction measure. In turn, the predicting perceived barrier on vaccination control varied significantly with the production system and the age of farmers. The significant HBM perception predictors on herd isolation and animal movement restriction control were significantly influenced only by the type of production system. The results of this study indicate that farmers' intentions to apply FMD control measures are variable among production systems, an insight which is relevant in the development of future control programs. Promotion programs aimed at increasing farmers' motivation to participate in FMD control by charged vaccination or animal movement restriction should give attention to the perceived barriers influencing the intentions to apply these measures.

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.

Fungicide application practices and personal protective equipment use among orchard farmers in the agricultural health study.

PubMed

Hines, C J; Deddens, J A; Coble, J; Alavanja, M C R

2007-04-01

Fungicides are routinely applied to deciduous tree fruits for disease management. Seventy-four private orchard applicators enrolled in the Agricultural Health Study participated in the Orchard Fungicide Exposure Study in 2002-2003. During 144 days of observation, information was obtained on chemicals applied and applicator mixing, application, personal protective, and hygiene practices. At least half of the applicators had orchards with <100 trees. Air blast was the most frequent application method used (55%), followed by hand spray (44%). Rubber gloves were the most frequently worn protective equipment (68% mix; 59% apply), followed by respirators (45% mix; 49% apply), protective outerwear (36% mix; 37% apply), and rubber boots (35% mix; 36% apply). Eye protection was worn while mixing and applying on only 35% and 41% of the days, respectively. Bivariate analyses were performed using repeated logistic or repeated linear regression. Mean duration of mixing, pounds of captan applied, total acres sprayed, and number of tank mixes sprayed were greater for air blast than for hand spray (p < 0.05). Spraying from a tractor/vehicle without an enclosed cab was associated with wearing some type of coverall (p < 0.05). Applicators often did not wash their hands after mixing (77%), a finding not explained by glove use. Glove use during mixing was associated with younger age, while wearing long-sleeve shirts was associated with older age (p < 0.05 each). Self-reported unusually high fungicide exposures were more likely on days applicators performed repairs (p < 0.05). These data will be useful for evaluating fungicide exposure determinants among orchard applicators.

Modeling of pathogen survival during simulated gastric digestion.

PubMed

Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

2011-02-01

The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens.

Modeling of Pathogen Survival during Simulated Gastric Digestion ▿

PubMed Central

Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

2011-01-01

The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens. PMID:21131530

Simulating Sustainment for an Unmanned Logistics System Concept of Operation in Support of Distributed Operations

DTIC Science & Technology

2017-06-01

designed experiment to model and explore a ship-to-shore logistics process supporting dispersed units via three types of ULSs, which vary primarily in...systems, simulation, discrete event simulation, design of experiments, data analysis, simplekit, nearly orthogonal and balanced designs 15. NUMBER OF... designed experiment to model and explore a ship-to-shore logistics process supporting dispersed units via three types of ULSs, which vary primarily

Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

PubMed

Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

2007-09-01

Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

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.

Research challenges in municipal solid waste logistics management.

PubMed

Bing, Xiaoyun; Bloemhof, Jacqueline M; Ramos, Tania Rodrigues Pereira; Barbosa-Povoa, Ana Paula; Wong, Chee Yew; van der Vorst, Jack G A J

2016-02-01

During the last two decades, EU legislation has put increasing pressure on member countries to achieve specified recycling targets for municipal household waste. These targets can be obtained in various ways choosing collection methods, separation methods, decentral or central logistic systems, etc. This paper compares municipal solid waste (MSW) management practices in various EU countries to identify the characteristics and key issues from a waste management and reverse logistics point of view. Further, we investigate literature on modelling municipal solid waste logistics in general. Comparing issues addressed in literature with the identified issues in practice result in a research agenda for modelling municipal solid waste logistics in Europe. We conclude that waste recycling is a multi-disciplinary problem that needs to be considered at different decision levels simultaneously. A holistic view and taking into account the characteristics of different waste types are necessary when modelling a reverse supply chain for MSW recycling. Copyright © 2015 Elsevier Ltd. All rights reserved.

An analysis of tree mortality using high resolution remotely-sensed data for mixed-conifer forests in San Diego county

NASA Astrophysics Data System (ADS)

Freeman, Mary Pyott

ABSTRACT An Analysis of Tree Mortality Using High Resolution Remotely-Sensed Data for Mixed-Conifer Forests in San Diego County by Mary Pyott Freeman The montane mixed-conifer forests of San Diego County are currently experiencing extensive tree mortality, which is defined as dieback where whole stands are affected. This mortality is likely the result of the complex interaction of many variables, such as altered fire regimes, climatic conditions such as drought, as well as forest pathogens and past management strategies. Conifer tree mortality and its spatial pattern and change over time were examined in three components. In component 1, two remote sensing approaches were compared for their effectiveness in delineating dead trees, a spatial contextual approach and an OBIA (object based image analysis) approach, utilizing various dates and spatial resolutions of airborne image data. For each approach transforms and masking techniques were explored, which were found to improve classifications, and an object-based assessment approach was tested. In component 2, dead tree maps produced by the most effective techniques derived from component 1 were utilized for point pattern and vector analyses to further understand spatio-temporal changes in tree mortality for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Results indicate that conifer mortality was significantly clustered, increased substantially between 2002 and 2005, and was non-random with respect to tree species and diameter class sizes. In component 3, multiple environmental variables were used in Generalized Linear Model (GLM-logistic regression) and decision tree classifier model development, revealing the importance of climate and topographic factors such as precipitation and elevation, in being able to predict areas of high risk for tree mortality. The results from this study highlight the importance of multi-scale spatial as well as temporal analyses, in order to understand mixed-conifer forest structure, dynamics, and processes of decline, which can lead to more sustainable management of forests with continued natural and anthropogenic disturbance.

MixSIAR: advanced stable isotope mixing models in R

EPA Science Inventory

Background/Question/Methods The development of stable isotope mixing models has coincided with modeling products (e.g. IsoSource, MixSIR, SIAR), where methodological advances are published in parity with software packages. However, while mixing model theory has recently been ex...

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

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

Defraene, Gilles, E-mail: gilles.defraene@uzleuven.be; Van den Bergh, Laura; Al-Mamgani, Abrahim

2012-03-01

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including themore » most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions: Comparable prediction models were obtained with LKB, RS, and logistic NTCP models. Including clinical factors improved the predictive power of all models significantly.« less

Large unbalanced credit scoring using Lasso-logistic regression ensemble.

PubMed

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data.

Habitat features and predictive habitat modeling for the Colorado chipmunk in southern New Mexico

USGS Publications Warehouse

Rivieccio, M.; Thompson, B.C.; Gould, W.R.; Boykin, K.G.

2003-01-01

Two subspecies of Colorado chipmunk (state threatened and federal species of concern) occur in southern New Mexico: Tamias quadrivittatus australis in the Organ Mountains and T. q. oscuraensis in the Oscura Mountains. We developed a GIS model of potentially suitable habitat based on vegetation and elevation features, evaluated site classifications of the GIS model, and determined vegetation and terrain features associated with chipmunk occurrence. We compared GIS model classifications with actual vegetation and elevation features measured at 37 sites. At 60 sites we measured 18 habitat variables regarding slope, aspect, tree species, shrub species, and ground cover. We used logistic regression to analyze habitat variables associated with chipmunk presence/absence. All (100%) 37 sample sites (28 predicted suitable, 9 predicted unsuitable) were classified correctly by the GIS model regarding elevation and vegetation. For 28 sites predicted suitable by the GIS model, 18 sites (64%) appeared visually suitable based on habitat variables selected from logistic regression analyses, of which 10 sites (36%) were specifically predicted as suitable habitat via logistic regression. We detected chipmunks at 70% of sites deemed suitable via the logistic regression models. Shrub cover, tree density, plant proximity, presence of logs, and presence of rock outcrop were retained in the logistic model for the Oscura Mountains; litter, shrub cover, and grass cover were retained in the logistic model for the Organ Mountains. Evaluation of predictive models illustrates the need for multi-stage analyses to best judge performance. Microhabitat analyses indicate prospective needs for different management strategies between the subspecies. Sensitivities of each population of the Colorado chipmunk to natural and prescribed fire suggest that partial burnings of areas inhabited by Colorado chipmunks in southern New Mexico may be beneficial. These partial burnings may later help avoid a fire that could substantially reduce habitat of chipmunks over a mountain range.

Application of wireless sensor network technology in logistics information system

NASA Astrophysics Data System (ADS)

Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2017-04-01

This paper introduces the basic concepts of active RFID (WSN-ARFID) based on wireless sensor networks and analyzes the shortcomings of the existing RFID-based logistics monitoring system. Integrated wireless sensor network technology and the scrambling point of RFID technology. A new real-time logistics detection system based on WSN and RFID, a model of logistics system based on WSN-ARFID is proposed, and the feasibility of this technology applied to logistics field is analyzed.

Individual Differences in Boys’ and Girls’ Timing and Tempo of Puberty: Modeling Development With Nonlinear Growth Models

PubMed Central

Marceau, Kristine; Ram, Nilam; Houts, Renate M.; Grimm, Kevin J.; Susman, Elizabeth J.

2014-01-01

Pubertal development is a nonlinear process progressing from prepubescent beginnings through biological, physical, and psychological changes to full sexual maturity. To tether theoretical concepts of puberty with sophisticated longitudinal, analytical models capable of articulating pubertal development more accurately, we used nonlinear mixed-effects models to describe both the timing and tempo of pubertal development in the sample of 364 White boys and 373 White girls measured across 6 years as part of the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development. Individual differences in timing and tempo were extracted with models of logistic growth. Differential relations emerged for how boys’ and girls’ timing and tempo of development were related to physical characteristics (body mass index, height, and weight) and psychological outcomes (internalizing problems, externalizing problems, and risky sexual behavior). Timing and tempo are associated in boys but not girls. Pubertal timing and tempo are particularly important for predicting psychological outcomes in girls but only sparsely related to boys’ psychological outcomes. Results highlight the importance of considering the nonlinear nature of puberty and expand the repertoire of possibilities for examining important aspects of how and when pubertal processes contribute to development. PMID:21639623

Joint Optimization of Distribution Network Design and Two-Echelon Inventory Control with Stochastic Demand and CO2 Emission Tax Charges

PubMed Central

Li, Shuangyan; Li, Xialian; Zhang, Dezhi; Zhou, Lingyun

2017-01-01

This study develops an optimization model to integrate facility location and inventory control for a three-level distribution network consisting of a supplier, multiple distribution centers (DCs), and multiple retailers. The integrated model addressed in this study simultaneously determines three types of decisions: (1) facility location (optimal number, location, and size of DCs); (2) allocation (assignment of suppliers to located DCs and retailers to located DCs, and corresponding optimal transport mode choices); and (3) inventory control decisions on order quantities, reorder points, and amount of safety stock at each retailer and opened DC. A mixed-integer programming model is presented, which considers the carbon emission taxes, multiple transport modes, stochastic demand, and replenishment lead time. The goal is to minimize the total cost, which covers the fixed costs of logistics facilities, inventory, transportation, and CO2 emission tax charges. The aforementioned optimal model was solved using commercial software LINGO 11. A numerical example is provided to illustrate the applications of the proposed model. The findings show that carbon emission taxes can significantly affect the supply chain structure, inventory level, and carbon emission reduction levels. The delay rate directly affects the replenishment decision of a retailer. PMID:28103246

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.

The application of virtual reality systems as a support of digital manufacturing and logistics

NASA Astrophysics Data System (ADS)

Golda, G.; Kampa, A.; Paprocka, I.

2016-08-01

Modern trends in development of computer aided techniques are heading toward the integration of design competitive products and so-called "digital manufacturing and logistics", supported by computer simulation software. All phases of product lifecycle: starting from design of a new product, through planning and control of manufacturing, assembly, internal logistics and repairs, quality control, distribution to customers and after-sale service, up to its recycling or utilization should be aided and managed by advanced packages of product lifecycle management software. Important problems for providing the efficient flow of materials in supply chain management of whole product lifecycle, using computer simulation will be described on that paper. Authors will pay attention to the processes of acquiring relevant information and correct data, necessary for virtual modeling and computer simulation of integrated manufacturing and logistics systems. The article describes possibilities of use an applications of virtual reality software for modeling and simulation the production and logistics processes in enterprise in different aspects of product lifecycle management. The authors demonstrate effective method of creating computer simulations for digital manufacturing and logistics and show modeled and programmed examples and solutions. They pay attention to development trends and show options of the applications that go beyond enterprise.

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules

PubMed Central

Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules’ 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively. PMID:29228030

Logistic regression analysis of conventional ultrasonography, strain elastosonography, and contrast-enhanced ultrasound characteristics for the differentiation of benign and malignant thyroid nodules.

PubMed

Pang, Tiantian; Huang, Leidan; Deng, Yingyuan; Wang, Tianfu; Chen, Siping; Gong, Xuehao; Liu, Weixiang

2017-01-01

The aim of the study is to screen the significant sonographic features by logistic regression analysis and fit a model to diagnose thyroid nodules. A total of 525 pathological thyroid nodules were retrospectively analyzed. All the nodules underwent conventional ultrasonography (US), strain elastosonography (SE), and contrast -enhanced ultrasound (CEUS). Those nodules' 12 suspicious sonographic features were used to assess thyroid nodules. The significant features of diagnosing thyroid nodules were picked out by logistic regression analysis. All variables that were statistically related to diagnosis of thyroid nodules, at a level of p < 0.05 were embodied in a logistic regression analysis model. The significant features in the logistic regression model of diagnosing thyroid nodules were calcification, suspected cervical lymph node metastasis, hypoenhancement pattern, margin, shape, vascularity, posterior acoustic, echogenicity, and elastography score. According to the results of logistic regression analysis, the formula that could predict whether or not thyroid nodules are malignant was established. The area under the receiver operating curve (ROC) was 0.930 and the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 83.77%, 89.56%, 87.05%, 86.04%, and 87.79% respectively.

Victimization from Mental and Physical Bullying and Substance Use in Early Adolescence

PubMed Central

Tharp-Taylor, Shannah; Haviland, Amelia; D'Amico, Elizabeth J.

2009-01-01

Logistic regression analyses were used to assess the association between victimization from mental and physical bullying and use of alcohol, cigarettes, marijuana, and inhalants among middle school students. Self-report data were analyzed from 926 ethnically diverse sixth through eighth grade students (43% white, 26% Latino, 7% Asian American/Pacific Islander, 3% African American, 14% mixed ethnic origin, and 5% “other”) ages 11 – 14 years from southern California. Substance use was collected at two time points (fall 2004 and spring 2005) during an academic year. Models were run for each substance separately. Results supported an association between victimization from bullying and substance use. Youths who experienced each type of bullying (mental or physical) separately or in combination were more likely to report use of each substance in spring 2005. This finding held after controlling for gender, grade level, ethnicity and substance use in fall 2004. PMID:19398162

Improving regional development through aerotropolis conceptual design

NASA Astrophysics Data System (ADS)

Berawi, M. A.; Miraj, P.; Adhityo, A. D.; Sakti, G. R.

2017-12-01

The airport has a great role in the modern life and has been shown significant influence in shaping the layout and structure of the city. Along with the high growth of passenger and logistics activities, the airport has been developed into a city-based airport. Although airports in the world have commonly implemented this concept, most cities in Indonesia are not familiar and prefer the traditional approach by locating airport far from the city with limited consideration of urban expansion. This research will conduct a study to develop the most suitable model of the aero - city. The study will use a combination of quantitative and qualitative approaches. The results shows that Aerotropolis development required 1,446.9 Ha and divided into four components. Airport use 53.21% of the area for about 770 Ha, an industrial zone about 430.6 Ha (29.76%), Mixed - use area about 101.6% (7.03%) and supporting infrastructure about 144.7 Ha (10%).

Epidemiologic Trends of Rabies in Domestic Animals in Southern Thailand, 1994–2008

PubMed Central

Thiptara, Anyarat; Atwill, Edward R.; Kongkaew, Wandee; Chomel, Bruno B.

2011-01-01

Rabies and associated risk factors in dogs, cats and cattle (n = 3,454) in southern Thailand during 1994–2008 were evaluated by using a mixed-effect logistic regression model. Overall prevalence was 48%. In dogs, odds of being rabid were 1.7 times higher in unvaccinated dogs than in vaccinated dogs and two times higher in dogs with bite history than in dogs with no known bite history. Similarly, aggressive dogs were more likely to be rabid than non-aggressive dogs. In cattle, aggression, pharyngeal paralysis, hyperactivity, and depression were clinical signs associated with being rabid. Annual fluctuations of the species-specific prevalence of rabies is suggestive of a positive correlation between canine and either feline (r = 0.60, P = 0.05) or bovine rabies (r = 0.78, P = 0.004). Insufficient vaccination coverage led to maintenance of rabies, which could be easily controlled by increased vaccine coverage and public education. PMID:21734139

Epidemiologic trends of rabies in domestic animals in southern Thailand, 1994-2008.

PubMed

Thiptara, Anyarat; Atwill, Edward R; Kongkaew, Wandee; Chomel, Bruno B

2011-07-01

Rabies and associated risk factors in dogs, cats and cattle (n = 3,454) in southern Thailand during 1994-2008 were evaluated by using a mixed-effect logistic regression model. Overall prevalence was 48%. In dogs, odds of being rabid were 1.7 times higher in unvaccinated dogs than in vaccinated dogs and two times higher in dogs with bite history than in dogs with no known bite history. Similarly, aggressive dogs were more likely to be rabid than non-aggressive dogs. In cattle, aggression, pharyngeal paralysis, hyperactivity, and depression were clinical signs associated with being rabid. Annual fluctuations of the species-specific prevalence of rabies is suggestive of a positive correlation between canine and either feline (r = 0.60, P = 0.05) or bovine rabies (r = 0.78, P = 0.004). Insufficient vaccination coverage led to maintenance of rabies, which could be easily controlled by increased vaccine coverage and public education.

Activity and dietary habits of mothers and children: close ties.

PubMed

Greenberg, Robert S; Ariza, Adolfo J; Binns, Helen J

2010-11-01

To examine associations between activity and dietary habits reported by mothers for themselves and their children aged 2 to 11 years. Cross-sectional, consecutive samples of parents at 13 primary care practices were surveyed on health behaviors. Survey questions were used to define 5 "healthy" habits: low-fat milk choice; low fast food use; low weekend screen time; low juice/sweet drinks intake; and high-frequency physical activity. Mixed-effects logistic regression models were applied. Responses from a socioeconomically diverse group of 2115 mothers were analyzed. For each healthy behavior self-reported by the mother, the odds of the healthy behavior being reported for the child were significantly higher (range: odds ratio [OR] = 3.2 for high-frequency physical activity to OR = 19.7 for low-fat milk choice). Mothers and children often have similar health habits. The impact of clinician counseling for children may be strengthened by promotion of healthy habits for their mothers.

Factors associated with the serological prevalence of Salmonella enterica in Greek finishing swineherds.

PubMed Central

Leontides, L. S.; Grafanakis, E.; Genigeorgis, C.

2003-01-01

Blood samples were taken from 50 finishing pigs at 90-105 kg in each of 59 randomly selected farrow-to-finish herds. The sera were tested for antibodies to Salmonella enterica by the Danish mix-ELISA. Samples with an optical density of > 10% were considered to be positive. Associations between the odds of seropositivity of pigs and possible risk factors were evaluated in multivariable logistic regression models. The results of the analysis indicated that pigs fed non-pelleted dry or wet ration had 11 (P = 0.0004) or 9 (P = 0.02) times, respectively, lower odds of seropositivity than those fed pelleted ration. The risk of seropositivity was 4 (P = 0.0006) times higher in pigs fed a combination of chlortetracycline, procaine penicillin and sulphamethazine during fattening than in those fed an approved growth promotor or a probiotic. PMID:12948357

Colour and emotion: children also associate red with negative valence.

PubMed

Gil, Sandrine; Le Bigot, Ludovic

2016-11-01

The association of colour with emotion constitutes a growing field of research, as it can affect how humans process their environment. Although there has been increasing interest in the association of red with negative valence in adults, little is known about how it develops. We therefore tested the red-negative association in children for the first time. Children aged 5-10 years performed a face categorization task in the form of a card-sorting task. They had to judge whether ambiguous faces shown against three different colour backgrounds (red, grey, green) seemed to 'feel good' or 'feel bad'. Results of logistic mixed models showed that - as previously demonstrated in adults - children across the age range provided significantly more 'feel bad' responses when the faces were given a red background. This finding is discussed in relation to colour-emotion association theories. © 2015 John Wiley & Sons Ltd.

Using Logistic Regression to Predict the Probability of Debris Flows in Areas Burned by Wildfires, Southern California, 2003-2006

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.; Michael, John A.; Helsel, Dennis R.

2008-01-01

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

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…

Graded Response Model Based on the Logistic Positive Exponent Family of Models for Dichotomous Responses

ERIC Educational Resources Information Center

Samejima, Fumiko

2008-01-01

Samejima ("Psychometrika "65:319--335, 2000) proposed the logistic positive exponent family of models (LPEF) for dichotomous responses in the unidimensional latent space. The objective of the present paper is to propose and discuss a graded response model that is expanded from the LPEF, in the context of item response theory (IRT). This…

Locally Dependent Linear Logistic Test Model with Person Covariates

ERIC Educational Resources Information Center

Ip, Edward H.; Smits, Dirk J. M.; De Boeck, Paul

2009-01-01

The article proposes a family of item-response models that allow the separate and independent specification of three orthogonal components: item attribute, person covariate, and local item dependence. Special interest lies in extending the linear logistic test model, which is commonly used to measure item attributes, to tests with embedded item…

A Bayesian Semiparametric Item Response Model with Dirichlet Process Priors

ERIC Educational Resources Information Center

Miyazaki, Kei; Hoshino, Takahiro

2009-01-01

In Item Response Theory (IRT), item characteristic curves (ICCs) are illustrated through logistic models or normal ogive models, and the probability that examinees give the correct answer is usually a monotonically increasing function of their ability parameters. However, since only limited patterns of shapes can be obtained from logistic models…

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…

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.

Assessment of the value of repeated point-prevalence surveys for analyzing the trend in nosocomial infections.

PubMed

Sartor, Catherine; Delchambre, Anne; Pascal, Laurence; Drancourt, Michel; De Micco, Philippe; Sambuc, Roland

2005-04-01

To assess the value of repeated point-prevalence surveys in measuring the trend in nosocomial infections after adjustment for case mix. A 3,500-bed teaching facility composed of 4 acute care hospitals. From May 1992 to June 1996, eight point-prevalence surveys of nosocomial infections were performed in the hospitals using a sampling process. The trend of adjusted nosocomial infection rates was studied for the four surveys that collected data on indwelling catheters. Adjusted rates were calculated using a logistic regression model and a direct standardization method. From 1992 to 1996, a total of 20,238 patients were included in the 8 point-prevalence surveys. The nosocomial infection rate decreased from 8.6% in 1992 to 5% in 1996 (P < .001). The analysis of adjusted nosocomial infection rates included 9,600 patients. Four independent risk factors were identified: length of stay greater than 12 days, hospitalization in an intensive care unit, presence of an indwelling urinary catheter, and history of a surgical procedure. After adjustment for case mix, the nosocomial infection rate still showed a downward trend (from 7.2% in 1993 to 5.1% in 1996; P = .02). Adjusted prevalence rates of nosocomial infections showed a significant downward trend during the period of this study.

Optimizing the Logistics of Anaerobic Digestion of Manure

NASA Astrophysics Data System (ADS)

Ghafoori, Emad; Flynn, Peter C.

Electrical power production from the combustion of biogas from anaerobic digestion (AD) of manure is a means of recovering energy from animal waste. We evaluate the lowest cost method of moving material to and from centralized AD plants serving multiple confined feeding operations. Two areas are modeled, Lethbridge County, Alberta, Canada, an area of concentrated beef cattle feedlots, and Red Deer County, Alberta, a mixed-farming area with hog, dairy, chicken and beef cattle farms, and feedlots. We evaluate two types of AD plant: ones that return digestate to the source confined feeding operation for land spreading (current technology), and ones that process digestate to produce solid fertilizer and a dischargeable water stream (technology under development). We evaluate manure and digestate trucking, trucking of manure with return of digestate by pipelines, and pipelining of manure plus digestate. We compare the overall cost of power from these scenarios to farm or feedlot-based AD units. For a centralized AD plant with digestate return for land spreading the most economical transport option for manure plus digestate is by truck for the mixed-farming area and by pipelines for the concentrated feedlot area. For a centralized AD plant with digestate processing, the most economical transport option is trucking of manure for both cases.

Effect of genetic ancestry to the risk of susceptibility to gastric cancer in a mixed population of the Brazilian Amazon.

PubMed

da Silva, Ellen Moreno; Fernandes, Marianne Rodrigues; de Carvalho, Darlen Cardoso; Leitao, Luciana Pereira Colares; Cavalcante, Giovanna Chaves; Pereira, Esdras Edgar Batista; Modesto, Antônio André Conde; Guerreiro, João Farias; de Assumpção, Paulo Pimentel; Dos Santos, Sidney Emanuel Batista; Dos Santos, Ney Pereira Carneiro

2017-11-29

Global literature describes differences in the incidence of gastric cancer among populations. For instance, Europeans have lower incidence rates of gastric cancer in relation to Latin and Asian populations, particularly Korean and Japanese populations. However, only a few studies have been able to verify the occurrence of gastric cancer in admixed populations with high interethnic degree mix, such as the Brazilian Amazon region. We observed an increase in European ancestry in the control group compared to the case group (47% vs. 41%). Using increments of 10%, compared to categorical distribution of European ancestry in the sample, we found a difference in the contribution between cases and controls (p = 0.03). Multiple logistic regression was performed to determine the influence of European ancestry in susceptibility to gastric cancer in the sample. According to the adopted model, for each 10% increase in European ancestry, there is a 20% decrease chance of developing gastric cancer (P = 0.0121; OR = 0.81; 95% CI 0.54-0.83). Overall, the results suggest that a greater contribution of European ancestry can be a protective factor for the development of gastric cancer in the studied Amazon population. It can help to establish protocols able to predict susceptibility to gastric cancer in admixed populations.

Variations in hospitalization rates among nursing home residents: the role of discretionary hospitalizations.

PubMed

Carter, Mary W

2003-08-01

To examine variations in hospitalization rates among nursing home residents associated with discretionary hospitalization practices. Quarterly Medicaid case-mix reimbursement data from the state of Massachusetts served as the core data source for this study, which was linked with data from the Medicare Provider Analysis and Review file (MEDPAR) to specify hospitalization status, nursing facility attribute data from the state of Massachusetts to specify facility-level organizational and structural attributes, and data from the Area Resource File (ARF) to specify area market-level attributes. Data spans three years (1991-1993) to produce a longitudinal analytical file containing 72,319 person-quarter-level observations. Two-step, multivariate logistic regression models were estimated for highly discretionary hospitalizations versus those containing less discretion, and low discretionary hospitalizations versus those containing greater amounts of physician discretion. Findings indicate that facility case-mix levels and area hospital bed supply levels contribute to variations in hospitalization rates among nursing home residents. Highly discretionary hospitalizations appear to be most sensitive to patient diagnoses best described as chronic, ambulatory care sensitive conditions. Findings suggest that defining hospitalizations simply in terms of whether an event occurs versus otherwise may obscure valuable information regarding the contribution of various risk factors to highly discretionary versus low discretionary hospitalization rates.

The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

PubMed

Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

2017-12-28

Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which obtained the highest precision. All adjustment strategies through logistic regression were biased for causal effect estimation, while IPW-based-MSM could always obtain unbiased estimation when the adjusted set satisfied G-admissibility. Thus, IPW-based-MSM was recommended to adjust for confounders set.

London Measure of Unplanned Pregnancy: guidance for its use as an outcome measure

PubMed Central

Hall, Jennifer A; Barrett, Geraldine; Copas, Andrew; Stephenson, Judith

2017-01-01

Background The London Measure of Unplanned Pregnancy (LMUP) is a psychometrically validated measure of the degree of intention of a current or recent pregnancy. The LMUP is increasingly being used worldwide, and can be used to evaluate family planning or preconception care programs. However, beyond recommending the use of the full LMUP scale, there is no published guidance on how to use the LMUP as an outcome measure. Ordinal logistic regression has been recommended informally, but studies published to date have all used binary logistic regression and dichotomized the scale at different cut points. There is thus a need for evidence-based guidance to provide a standardized methodology for multivariate analysis and to enable comparison of results. This paper makes recommendations for the regression method for analysis of the LMUP as an outcome measure. Materials and methods Data collected from 4,244 pregnant women in Malawi were used to compare five regression methods: linear, logistic with two cut points, and ordinal logistic with either the full or grouped LMUP score. The recommendations were then tested on the original UK LMUP data. Results There were small but no important differences in the findings across the regression models. Logistic regression resulted in the largest loss of information, and assumptions were violated for the linear and ordinal logistic regression. Consequently, robust standard errors were used for linear regression and a partial proportional odds ordinal logistic regression model attempted. The latter could only be fitted for grouped LMUP score. Conclusion We recommend the linear regression model with robust standard errors to make full use of the LMUP score when analyzed as an outcome measure. Ordinal logistic regression could be considered, but a partial proportional odds model with grouped LMUP score may be required. Logistic regression is the least-favored option, due to the loss of information. For logistic regression, the cut point for un/planned pregnancy should be between nine and ten. These recommendations will standardize the analysis of LMUP data and enhance comparability of results across studies. PMID:28435343

Workplace gender composition and psychological distress: the importance of the psychosocial work environment.

PubMed

Elwér, Sofia; Johansson, Klara; Hammarström, Anne

2014-03-10

Health consequences of the gender segregated labour market have previously been demonstrated in the light of gender composition of occupations and workplaces, with somewhat mixed results. Associations between the gender composition and health status have been suggested to be shaped by the psychosocial work environment. The present study aims to analyse how workplace gender composition is related to psychological distress and to explore the importance of the psychosocial work environment for psychological distress at workplaces with different gender compositions. The study population consisted of participants from the Northern Swedish Cohort with a registered workplace in 2007 when the participants were 42 years old (N=795). Questionnaire data were supplemented with register data on the gender composition of the participants' workplaces divided into three groups: workplaces with more women, mixed workplaces, and workplaces with more men. Associations between psychological distress and gender composition were analysed with multivariate logistic regression analysis adjusting for socioeconomic position, previous psychological distress, psychosocial work environment factors and gender. Logistic regression analyses (including interaction terms for gender composition and each work environment factor) were also used to assess differential associations between psychosocial work factor and psychological distress according to gender composition. Working at workplaces with a mixed gender composition was related to a higher likelihood of psychological distress compared to workplaces with more men, after adjustments for socioeconomic position, psychological distress at age 21, psychosocial work environment factors and gender. Psychosocial work environment factors did not explain the association between gender composition and psychological distress. The association between gender composition and psychological distress cannot be explained by differences in the perception of the psychosocial work environment and thus the work environment hypothesis is not supported. Workplaces with a mixed gender composition needs further research attention to explain the negative development of psychological distress during working life for both women and men at these workplaces.

Workplace gender composition and psychological distress: the importance of the psychosocial work environment

PubMed Central

2014-01-01

Background Health consequences of the gender segregated labour market have previously been demonstrated in the light of gender composition of occupations and workplaces, with somewhat mixed results. Associations between the gender composition and health status have been suggested to be shaped by the psychosocial work environment. The present study aims to analyse how workplace gender composition is related to psychological distress and to explore the importance of the psychosocial work environment for psychological distress at workplaces with different gender compositions. Methods The study population consisted of participants from the Northern Swedish Cohort with a registered workplace in 2007 when the participants were 42 years old (N = 795). Questionnaire data were supplemented with register data on the gender composition of the participants’ workplaces divided into three groups: workplaces with more women, mixed workplaces, and workplaces with more men. Associations between psychological distress and gender composition were analysed with multivariate logistic regression analysis adjusting for socioeconomic position, previous psychological distress, psychosocial work environment factors and gender. Logistic regression analyses (including interaction terms for gender composition and each work environment factor) were also used to assess differential associations between psychosocial work factor and psychological distress according to gender composition. Results Working at workplaces with a mixed gender composition was related to a higher likelihood of psychological distress compared to workplaces with more men, after adjustments for socioeconomic position, psychological distress at age 21, psychosocial work environment factors and gender. Psychosocial work environment factors did not explain the association between gender composition and psychological distress. Conclusions The association between gender composition and psychological distress cannot be explained by differences in the perception of the psychosocial work environment and thus the work environment hypothesis is not supported. Workplaces with a mixed gender composition needs further research attention to explain the negative development of psychological distress during working life for both women and men at these workplaces. PMID:24612791

Hierarchical Bayesian Logistic Regression to forecast metabolic control in type 2 DM patients.

PubMed

Dagliati, Arianna; Malovini, Alberto; Decata, Pasquale; Cogni, Giulia; Teliti, Marsida; Sacchi, Lucia; Cerra, Carlo; Chiovato, Luca; Bellazzi, Riccardo

2016-01-01

In this work we present our efforts in building a model able to forecast patients' changes in clinical conditions when repeated measurements are available. In this case the available risk calculators are typically not applicable. We propose a Hierarchical Bayesian Logistic Regression model, which allows taking into account individual and population variability in model parameters estimate. The model is used to predict metabolic control and its variation in type 2 diabetes mellitus. In particular we have analyzed a population of more than 1000 Italian type 2 diabetic patients, collected within the European project Mosaic. The results obtained in terms of Matthews Correlation Coefficient are significantly better than the ones gathered with standard logistic regression model, based on data pooling.

The Space Station Freedom - International cooperation and innovation in space safety

NASA Technical Reports Server (NTRS)

Rodney, George A.

1989-01-01

The Space Station Freedom (SSF) being developed by the United States, European Space Agency (ESA), Japan, and Canada poses novel safety challenges in design, operations, logistics, and program management. A brief overview discloses many features that make SSF a radical departure from earlier low earth orbit (LEO) space stations relative to safety management: size and power levels; multiphase manned assembly; 30-year planned lifetime, with embedded 'hooks and scars' forevolution; crew size and skill-mix variability; sustained logistical dependence; use of man, robotics and telepresence for on-orbit maintenance of station and free-flyer systems; closed-environment recycling; use of automation and expert systems; long-term operation of collocated life-sciences and materials-science experiments, requiring control and segregation of hazardous and chemically incompatible materials; and materials aging in space.

Adaptation of clinical prediction models for application in local settings.

PubMed

Kappen, Teus H; Vergouwe, Yvonne; van Klei, Wilton A; van Wolfswinkel, Leo; Kalkman, Cor J; Moons, Karel G M

2012-01-01

When planning to use a validated prediction model in new patients, adequate performance is not guaranteed. For example, changes in clinical practice over time or a different case mix than the original validation population may result in inaccurate risk predictions. To demonstrate how clinical information can direct updating a prediction model and development of a strategy for handling missing predictor values in clinical practice. A previously derived and validated prediction model for postoperative nausea and vomiting was updated using a data set of 1847 patients. The update consisted of 1) changing the definition of an existing predictor, 2) reestimating the regression coefficient of a predictor, and 3) adding a new predictor to the model. The updated model was then validated in a new series of 3822 patients. Furthermore, several imputation models were considered to handle real-time missing values, so that possible missing predictor values could be anticipated during actual model use. Differences in clinical practice between our local population and the original derivation population guided the update strategy of the prediction model. The predictive accuracy of the updated model was better (c statistic, 0.68; calibration slope, 1.0) than the original model (c statistic, 0.62; calibration slope, 0.57). Inclusion of logistical variables in the imputation models, besides observed patient characteristics, contributed to a strategy to deal with missing predictor values at the time of risk calculation. Extensive knowledge of local, clinical processes provides crucial information to guide the process of adapting a prediction model to new clinical practices.

A simple approximation of moments of the quasi-equilibrium distribution of an extended stochastic theta-logistic model with non-integer powers.

PubMed

Bhowmick, Amiya Ranjan; Bandyopadhyay, Subhadip; Rana, Sourav; Bhattacharya, Sabyasachi

2016-01-01

The stochastic versions of the logistic and extended logistic growth models are applied successfully to explain many real-life population dynamics and share a central body of literature in stochastic modeling of ecological systems. To understand the randomness in the population dynamics of the underlying processes completely, it is important to have a clear idea about the quasi-equilibrium distribution and its moments. Bartlett et al. (1960) took a pioneering attempt for estimating the moments of the quasi-equilibrium distribution of the stochastic logistic model. Matis and Kiffe (1996) obtain a set of more accurate and elegant approximations for the mean, variance and skewness of the quasi-equilibrium distribution of the same model using cumulant truncation method. The method is extended for stochastic power law logistic family by the same and several other authors (Nasell, 2003; Singh and Hespanha, 2007). Cumulant truncation and some alternative methods e.g. saddle point approximation, derivative matching approach can be applied if the powers involved in the extended logistic set up are integers, although plenty of evidence is available for non-integer powers in many practical situations (Sibly et al., 2005). In this paper, we develop a set of new approximations for mean, variance and skewness of the quasi-equilibrium distribution under more general family of growth curves, which is applicable for both integer and non-integer powers. The deterministic counterpart of this family of models captures both monotonic and non-monotonic behavior of the per capita growth rate, of which theta-logistic is a special case. The approximations accurately estimate the first three order moments of the quasi-equilibrium distribution. The proposed method is illustrated with simulated data and real data from global population dynamics database. Copyright © 2015 Elsevier Inc. All rights reserved.

Research and application of genetic algorithm in path planning of logistics distribution vehicle

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

The core of the logistics distribution system is the vehicle routing planning, research path planning problem, provide a better solution has become an important issue. In order to provide the decision support for logistics and distribution operations, this paper studies the problem of vehicle routing with capacity constraints (CVRP). By establishing a mathematical model, the genetic algorithm is used to plan the path of the logistics vehicle to meet the minimum logistics and transportation costs.

Analysis of Jingdong Mall Logistics Distribution Model

NASA Astrophysics Data System (ADS)

Shao, Kang; Cheng, Feng

In recent years, the development of electronic commerce in our country to speed up the pace. The role of logistics has been highlighted, more and more electronic commerce enterprise are beginning to realize the importance of logistics in the success or failure of the enterprise. In this paper, the author take Jingdong Mall for example, performing a SWOT analysis of their current situation of self-built logistics system, find out the problems existing in the current Jingdong Mall logistics distribution and give appropriate recommendations.

Assessing a cross-border logistics policy using a performance measurement system framework: the case of Hong Kong and the Pearl River Delta region

NASA Astrophysics Data System (ADS)

Wong, David W. C.; Choy, K. L.; Chow, Harry K. H.; Lin, Canhong

2014-06-01

For the most rapidly growing economic entity in the world, China, a new logistics operation called the indirect cross-border supply chain model has recently emerged. The primary idea of this model is to reduce logistics costs by storing goods at a bonded warehouse with low storage cost in certain Chinese regions, such as the Pearl River Delta (PRD). This research proposes a performance measurement system (PMS) framework to assess the direct and indirect cross-border supply chain models. The PMS covers four categories including cost, time, quality and flexibility in the assessment of the performance of direct and indirect models. Furthermore, a survey was conducted to investigate the logistics performance of third party logistics (3PLs) at the PRD regions, including Guangzhou, Shenzhen and Hong Kong. The significance of the proposed PMS framework allows 3PLs accurately pinpoint the weakness and strengths of it current operations policy at four major performance measurement categories. Hence, this helps 3PLs further enhance the competitiveness and operations efficiency through better resources allocation at the area of warehousing and transportation.

Complementary nonparametric analysis of covariance for logistic regression in a randomized clinical trial setting.

PubMed

Tangen, C M; Koch, G G

1999-03-01

In the randomized clinical trial setting, controlling for covariates is expected to produce variance reduction for the treatment parameter estimate and to adjust for random imbalances of covariates between the treatment groups. However, for the logistic regression model, variance reduction is not obviously obtained. This can lead to concerns about the assumptions of the logistic model. We introduce a complementary nonparametric method for covariate adjustment. It provides results that are usually compatible with expectations for analysis of covariance. The only assumptions required are based on randomization and sampling arguments. The resulting treatment parameter is a (unconditional) population average log-odds ratio that has been adjusted for random imbalance of covariates. Data from a randomized clinical trial are used to compare results from the traditional maximum likelihood logistic method with those from the nonparametric logistic method. We examine treatment parameter estimates, corresponding standard errors, and significance levels in models with and without covariate adjustment. In addition, we discuss differences between unconditional population average treatment parameters and conditional subpopulation average treatment parameters. Additional features of the nonparametric method, including stratified (multicenter) and multivariate (multivisit) analyses, are illustrated. Extensions of this methodology to the proportional odds model are also made.

An order insertion scheduling model of logistics service supply chain considering capacity and time factors.

PubMed

Liu, Weihua; Yang, Yi; Wang, Shuqing; Liu, Yang

2014-01-01

Order insertion often occurs in the scheduling process of logistics service supply chain (LSSC), which disturbs normal time scheduling especially in the environment of mass customization logistics service. This study analyses order similarity coefficient and order insertion operation process and then establishes an order insertion scheduling model of LSSC with service capacity and time factors considered. This model aims to minimize the average unit volume operation cost of logistics service integrator and maximize the average satisfaction degree of functional logistics service providers. In order to verify the viability and effectiveness of our model, a specific example is numerically analyzed. Some interesting conclusions are obtained. First, along with the increase of completion time delay coefficient permitted by customers, the possible inserting order volume first increases and then trends to be stable. Second, supply chain performance reaches the best when the volume of inserting order is equal to the surplus volume of the normal operation capacity in mass service process. Third, the larger the normal operation capacity in mass service process is, the bigger the possible inserting order's volume will be. Moreover, compared to increasing the completion time delay coefficient, improving the normal operation capacity of mass service process is more useful.

TDP-43 stage, mixed pathologies, and clinical Alzheimer's-type dementia.

PubMed

James, Bryan D; Wilson, Robert S; Boyle, Patricia A; Trojanowski, John Q; Bennett, David A; Schneider, Julie A

2016-11-01

Hyperphosphorylated transactive response DNA-binding protein 43 (TDP-43, encoded by TARDBP ) proteinopathy has recently been described in ageing and in association with cognitive impairment, especially in the context of Alzheimer's disease pathology. To explore the role of mixed Alzheimer's disease and TDP-43 pathologies in clinical Alzheimer's-type dementia, we performed a comprehensive investigation of TDP-43, mixed pathologies, and clinical Alzheimer's-type dementia in a large cohort of community-dwelling older subjects. We tested the hypotheses that TDP-43 with Alzheimer's disease pathology is a common mixed pathology; is related to increased likelihood of expressing clinical Alzheimer's-type dementia; and that TDP-43 pathologic stage is an important determinant of clinical Alzheimer's-type dementia. Data came from 946 older adults with ( n = 398) and without dementia ( n = 548) from the Rush Memory and Aging Project and Religious Orders Study. TDP-43 proteinopathy (cytoplasmic inclusions) was present in 496 (52%) subjects, and the pattern of deposition was classified as stage 0 (none; 48%), stage 1 (amygdala; 18%), stage 2 (extension to hippocampus/entorhinal; 21%), or stage 3 (extension to neocortex; 14%). TDP-43 pathology combined with a pathologic diagnosis of Alzheimer's disease was a common mixed pathology (37% of all participants), and the proportion of subjects with clinical Alzheimer's-type dementia formerly labelled 'pure pathologic diagnosis of Alzheimer's disease' was halved when TDP-43 was considered. In logistic regression models adjusted for age, sex, and education, TDP-43 pathology was associated with clinical Alzheimer's-type dementia (odds ratio = 1.51, 95% confidence interval = 1.11, 2.05) independent of pathological Alzheimer's disease (odds ratio = 4.30, 95% confidence interval = 3.08, 6.01) or other pathologies (infarcts, arteriolosclerosis, Lewy bodies, and hippocampal sclerosis). Mixed Alzheimer's disease and TDP-43 pathologies were associated with higher odds of clinical Alzheimer's-type dementia (odds ratio = 6.73, 95% confidence interval = 4.18, 10.85) than pathologic Alzheimer's disease alone (odds ratio = 4.62, 95% confidence interval = 2.84, 7.52). In models examining TDP-43 stage, a dose-response relationship with clinical Alzheimer's-type dementia was observed, and a significant association was observed starting at stage 2, extension beyond the amygdala. In this large sample from almost 1000 community participants, we observed that TDP-43 proteinopathy was very common, frequently mixed with pathological Alzheimer's disease, and associated with a higher likelihood of the clinical expression of clinical Alzheimer's-type dementia but only when extended beyond the amygdala. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Logistics modelling: improving resource management and public information strategies in Florida.

PubMed

Walsh, Daniel M; Van Groningen, Chuck; Craig, Brian

2011-10-01

One of the most time-sensitive and logistically-challenging emergency response operations today is to provide mass prophylaxis to every man, woman and child in a community within 48 hours of a bioterrorism attack. To meet this challenge, federal, state and local public health departments in the USA have joined forces to develop, test and execute large-scale bioterrorism response plans. This preparedness and response effort is funded through the US Centers for Disease Control and Prevention's Cities Readiness Initiative, a programme dedicated to providing oral antibiotics to an entire population within 48 hours of a weaponised inhalation anthrax attack. This paper will demonstrate how the State of Florida used a logistics modelling tool to improve its CRI mass prophylaxis plans. Special focus will be on how logistics modelling strengthened Florida's resource management policies and validated its public information strategies.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Army-Marine Integration, Volume 2, Number 10-55. Observations, Insights, and Lessons

DTIC Science & Technology

2010-08-01

can be tailored to combat any enemy force worldwide. The effectiveness of this revolutionary concept was displayed, and its fundamentals reinforced...evolved in Iraq’s western sector and the insurgents changed strategy, the sustainment demands required of coalition forces changed. The fundamentals of...of the MEU, and contracted civilian logistics within the area of operations. Getting the right mix of capabilities at each location was fundamental

Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble

PubMed Central

Wang, Hong; Xu, Qingsong; Zhou, Lifeng

2015-01-01

Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data. PMID:25706988

Modelling the growth of plants with a uniform growth logistics.

PubMed

Kilian, H G; Bartkowiak, D; Kazda, M; Kaufmann, D

2014-05-21

The increment model has previously been used to describe the growth of plants in general. Here, we examine how the same logistics enables the development of different superstructures. Data from the literature are analyzed with the increment model. Increments are growth-invariant molecular clusters, treated as heuristic particles. This approach formulates the law of mass action for multi-component systems, describing the general properties of superstructures which are optimized via relaxation processes. The daily growth patterns of hypocotyls can be reproduced implying predetermined growth invariant model parameters. In various species, the coordinated formation and death of fine roots are modeled successfully. Their biphasic annual growth follows distinct morphological programs but both use the same logistics. In tropical forests, distributions of the diameter in breast height of trees of different species adhere to the same pattern. Beyond structural fluctuations, competition and cooperation within and between the species may drive optimization. All superstructures of plants examined so far could be reproduced with our approach. With genetically encoded growth-invariant model parameters (interaction with the environment included) perfect morphological development runs embedded in the uniform logistics of the increment model. Copyright © 2014 Elsevier Ltd. All rights reserved.

An Efficient Alternative Mixed Randomized Response Procedure

ERIC Educational Resources Information Center

Singh, Housila P.; Tarray, Tanveer A.

2015-01-01

In this article, we have suggested a new modified mixed randomized response (RR) model and studied its properties. It is shown that the proposed mixed RR model is always more efficient than the Kim and Warde's mixed RR model. The proposed mixed RR model has also been extended to stratified sampling. Numerical illustrations and graphical…

To Use or Not to Use--(The One- or Three-Parameter Logistic Model) That Is the Question.

ERIC Educational Resources Information Center

Reckase, Mark D.

Definition of the issues to the use of latent trait models, specifically one- and three-parameter logistic models, in conjunction with multi-level achievement batteries, forms the basis of this paper. Research results related to these issues are also documented in an attempt to provide a rational basis for model selection. The application of the…

Quantifying the effect of mixing on the mean age of air in CCMVal-2 and CCMI-1 models

NASA Astrophysics Data System (ADS)

Dietmüller, Simone; Eichinger, Roland; Garny, Hella; Birner, Thomas; Boenisch, Harald; Pitari, Giovanni; Mancini, Eva; Visioni, Daniele; Stenke, Andrea; Revell, Laura; Rozanov, Eugene; Plummer, David A.; Scinocca, John; Jöckel, Patrick; Oman, Luke; Deushi, Makoto; Kiyotaka, Shibata; Kinnison, Douglas E.; Garcia, Rolando; Morgenstern, Olaf; Zeng, Guang; Stone, Kane Adam; Schofield, Robyn

2018-05-01

The stratospheric age of air (AoA) is a useful measure of the overall capabilities of a general circulation model (GCM) to simulate stratospheric transport. Previous studies have reported a large spread in the simulation of AoA by GCMs and coupled chemistry-climate models (CCMs). Compared to observational estimates, simulated AoA is mostly too low. Here we attempt to untangle the processes that lead to the AoA differences between the models and between models and observations. AoA is influenced by both mean transport by the residual circulation and two-way mixing; we quantify the effects of these processes using data from the CCM inter-comparison projects CCMVal-2 (Chemistry-Climate Model Validation Activity 2) and CCMI-1 (Chemistry-Climate Model Initiative, phase 1). Transport along the residual circulation is measured by the residual circulation transit time (RCTT). We interpret the difference between AoA and RCTT as additional aging by mixing. Aging by mixing thus includes mixing on both the resolved and subgrid scale. We find that the spread in AoA between the models is primarily caused by differences in the effects of mixing and only to some extent by differences in residual circulation strength. These effects are quantified by the mixing efficiency, a measure of the relative increase in AoA by mixing. The mixing efficiency varies strongly between the models from 0.24 to 1.02. We show that the mixing efficiency is not only controlled by horizontal mixing, but by vertical mixing and vertical diffusion as well. Possible causes for the differences in the models' mixing efficiencies are discussed. Differences in subgrid-scale mixing (including differences in advection schemes and model resolutions) likely contribute to the differences in mixing efficiency. However, differences in the relative contribution of resolved versus parameterized wave forcing do not appear to be related to differences in mixing efficiency or AoA.

Examination of environmentally friendly "green" logistics behavior of managers in the pharmaceutical sector using the Theory of Planned Behavior.

PubMed

Arslan, Miray; Şar, Sevgi

2017-12-11

Logistics activities play a prominent role in enabling manufacturers, distribution channels, and pharmacies to work in harmony. Nowadays these activities have become increasingly striking in the pharmaceutical industry and seen as a development area for this sector. Additionally, green practices are beginning to be more attracting particularly in decreasing costs and increasing image of pharmaceutical companies. The main objective of this study was modeling green logistics (GL) behavior of the managers in the pharmaceutical sector in the theory of planned behavior (TPB) frame via structural equation modeling (SEM). A measurement tool was developed according to TPB. Exploratory factor analysis was conducted to determine subfactors of GL behavior. In the second step, confirmatory factor analysis (CFA) was conducted for confirming whether there is a relationship between the observed variables and their underlying latent constructs. Finally, structural equation model was conducted to specify the relationships between latent variables. In the proposed green logistics behavior (GLB) model, the positive effect of environmental attitude towards GL, perceived behavioral control related GL, and subjective norm about GL on intention towards GL were found statistically significant. Nevertheless, the effect of attitude towards costs of GL on intention towards GL was not found statistically significant. Intention towards GL has been found to have a positive statistically significant effect on the GL behavior. Based on the results of this study, it is possible to say that TPB is an appropriate theory for modeling green logistics behavior of managers. This model can be seen as a guide to the companies in the pharmaceutical sector to participate in green logistics. Copyright © 2017 Elsevier Inc. All rights reserved.

[Primary branch size of Pinus koraiensis plantation: a prediction based on linear mixed effect model].

PubMed

Dong, Ling-Bo; Liu, Zhao-Gang; Li, Feng-Ri; Jiang, Li-Chun

2013-09-01

By using the branch analysis data of 955 standard branches from 60 sampled trees in 12 sampling plots of Pinus koraiensis plantation in Mengjiagang Forest Farm in Heilongjiang Province of Northeast China, and based on the linear mixed-effect model theory and methods, the models for predicting branch variables, including primary branch diameter, length, and angle, were developed. Considering tree effect, the MIXED module of SAS software was used to fit the prediction models. The results indicated that the fitting precision of the models could be improved by choosing appropriate random-effect parameters and variance-covariance structure. Then, the correlation structures including complex symmetry structure (CS), first-order autoregressive structure [AR(1)], and first-order autoregressive and moving average structure [ARMA(1,1)] were added to the optimal branch size mixed-effect model. The AR(1) improved the fitting precision of branch diameter and length mixed-effect model significantly, but all the three structures didn't improve the precision of branch angle mixed-effect model. In order to describe the heteroscedasticity during building mixed-effect model, the CF1 and CF2 functions were added to the branch mixed-effect model. CF1 function improved the fitting effect of branch angle mixed model significantly, whereas CF2 function improved the fitting effect of branch diameter and length mixed model significantly. Model validation confirmed that the mixed-effect model could improve the precision of prediction, as compare to the traditional regression model for the branch size prediction of Pinus koraiensis plantation.

The creation and evaluation of a model to simulate the probability of conception in seasonal-calving pasture-based dairy heifers.

PubMed

Fenlon, Caroline; O'Grady, Luke; Butler, Stephen; Doherty, Michael L; Dunnion, John

2017-01-01

Herd fertility in pasture-based dairy farms is a key driver of farm economics. Models for predicting nulliparous reproductive outcomes are rare, but age, genetics, weight, and BCS have been identified as factors influencing heifer conception. The aim of this study was to create a simulation model of heifer conception to service with thorough evaluation. Artificial Insemination service records from two research herds and ten commercial herds were provided to build and evaluate the models. All were managed as spring-calving pasture-based systems. The factors studied were related to age, genetics, and time of service. The data were split into training and testing sets and bootstrapping was used to train the models. Logistic regression (with and without random effects) and generalised additive modelling were selected as the model-building techniques. Two types of evaluation were used to test the predictive ability of the models: discrimination and calibration. Discrimination, which includes sensitivity, specificity, accuracy and ROC analysis, measures a model's ability to distinguish between positive and negative outcomes. Calibration measures the accuracy of the predicted probabilities with the Hosmer-Lemeshow goodness-of-fit, calibration plot and calibration error. After data cleaning and the removal of services with missing values, 1396 services remained to train the models and 597 were left for testing. Age, breed, genetic predicted transmitting ability for calving interval, month and year were significant in the multivariate models. The regression models also included an interaction between age and month. Year within herd was a random effect in the mixed regression model. Overall prediction accuracy was between 77.1% and 78.9%. All three models had very high sensitivity, but low specificity. The two regression models were very well-calibrated. The mean absolute calibration errors were all below 4%. Because the models were not adept at identifying unsuccessful services, they are not suggested for use in predicting the outcome of individual heifer services. Instead, they are useful for the comparison of services with different covariate values or as sub-models in whole-farm simulations. The mixed regression model was identified as the best model for prediction, as the random effects can be ignored and the other variables can be easily obtained or simulated.

Use of Midlevel Practitioners to Achieve Labor Cost Savings in the Primary Care Practice of an MCO

PubMed Central

Roblin, Douglas W; Howard, David H; Becker, Edmund R; Kathleen Adams, E; Roberts, Melissa H

2004-01-01

Objective To estimate the savings in labor costs per primary care visit that might be realized from increased use of physician assistants (PAs) and nurse practitioners (NPs) in the primary care practices of a managed care organization (MCO). Study Setting/Data Sources Twenty-six capitated primary care practices of a group model MCO. Data on approximately two million visits provided by 206 practitioners were extracted from computerized visit records for 1997–2000. Computerized payroll ledgers were the source of annual labor costs per practice from 1997–2000. Study Design Likelihood of a visit attended by a PA/NP versus MD was modeled using logistic regression, with practice fixed effects, by department (adult medicine, pediatrics) and year. Parameter estimates and practice fixed effects from these regressions were used to predict the proportion of PA/NP visits per practice per year given a standard case mix. Least squares regressions, with practice fixed effects, were used to estimate the association of this standardized predicted proportion of PA/NP visits with average annual practitioner and total labor costs per visit, controlling for other practice characteristics. Results On average, PAs/NPs attended one in three adult medicine visits and one in five pediatric medicine visits. Likelihood of a PA/NP visit was significantly higher than average among patients presenting with minor acute illness (e.g., acute pharyngitis). In adult medicine, likelihood of a PA/NP visit was lower than average among older patients. Practitioner labor costs per visit and total labor costs per visit were lower (p<.01 and p=.08, respectively) among practices with greater use of PAs/NPs, standardized for case mix. Conclusions Primary care practices that used more PAs/NPs in care delivery realized lower practitioner labor costs per visit than practices that used less. Future research should investigate the cost savings and cost-effectiveness potential of delivery designs that change staffing mix and division of labor among clinical disciplines. PMID:15149481

Model selection for logistic regression models

NASA Astrophysics Data System (ADS)

Duller, Christine

2012-09-01

Model selection for logistic regression models decides which of some given potential regressors have an effect and hence should be included in the final model. The second interesting question is whether a certain factor is heterogeneous among some subsets, i.e. whether the model should include a random intercept or not. In this paper these questions will be answered with classical as well as with Bayesian methods. The application show some results of recent research projects in medicine and business administration.

Filtering data from the collaborative initial glaucoma treatment study for improved identification of glaucoma progression.

PubMed

Schell, Greggory J; Lavieri, Mariel S; Stein, Joshua D; Musch, David C

2013-12-21

Open-angle glaucoma (OAG) is a prevalent, degenerate ocular disease which can lead to blindness without proper clinical management. The tests used to assess disease progression are susceptible to process and measurement noise. The aim of this study was to develop a methodology which accounts for the inherent noise in the data and improve significant disease progression identification. Longitudinal observations from the Collaborative Initial Glaucoma Treatment Study (CIGTS) were used to parameterize and validate a Kalman filter model and logistic regression function. The Kalman filter estimates the true value of biomarkers associated with OAG and forecasts future values of these variables. We develop two logistic regression models via generalized estimating equations (GEE) for calculating the probability of experiencing significant OAG progression: one model based on the raw measurements from CIGTS and another model based on the Kalman filter estimates of the CIGTS data. Receiver operating characteristic (ROC) curves and associated area under the ROC curve (AUC) estimates are calculated using cross-fold validation. The logistic regression model developed using Kalman filter estimates as data input achieves higher sensitivity and specificity than the model developed using raw measurements. The mean AUC for the Kalman filter-based model is 0.961 while the mean AUC for the raw measurements model is 0.889. Hence, using the probability function generated via Kalman filter estimates and GEE for logistic regression, we are able to more accurately classify patients and instances as experiencing significant OAG progression. A Kalman filter approach for estimating the true value of OAG biomarkers resulted in data input which improved the accuracy of a logistic regression classification model compared to a model using raw measurements as input. This methodology accounts for process and measurement noise to enable improved discrimination between progression and nonprogression in chronic diseases.

A Bayesian goodness of fit test and semiparametric generalization of logistic regression with measurement data.

PubMed

Schörgendorfer, Angela; Branscum, Adam J; Hanson, Timothy E

2013-06-01

Logistic regression is a popular tool for risk analysis in medical and population health science. With continuous response data, it is common to create a dichotomous outcome for logistic regression analysis by specifying a threshold for positivity. Fitting a linear regression to the nondichotomized response variable assuming a logistic sampling model for the data has been empirically shown to yield more efficient estimates of odds ratios than ordinary logistic regression of the dichotomized endpoint. We illustrate that risk inference is not robust to departures from the parametric logistic distribution. Moreover, the model assumption of proportional odds is generally not satisfied when the condition of a logistic distribution for the data is violated, leading to biased inference from a parametric logistic analysis. We develop novel Bayesian semiparametric methodology for testing goodness of fit of parametric logistic regression with continuous measurement data. The testing procedures hold for any cutoff threshold and our approach simultaneously provides the ability to perform semiparametric risk estimation. Bayes factors are calculated using the Savage-Dickey ratio for testing the null hypothesis of logistic regression versus a semiparametric generalization. We propose a fully Bayesian and a computationally efficient empirical Bayesian approach to testing, and we present methods for semiparametric estimation of risks, relative risks, and odds ratios when parametric logistic regression fails. Theoretical results establish the consistency of the empirical Bayes test. Results from simulated data show that the proposed approach provides accurate inference irrespective of whether parametric assumptions hold or not. Evaluation of risk factors for obesity shows that different inferences are derived from an analysis of a real data set when deviations from a logistic distribution are permissible in a flexible semiparametric framework. © 2013, The International Biometric Society.

Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

NASA Astrophysics Data System (ADS)

Yilmaz, Işık

2009-06-01

The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

Nursing home quality: a comparative analysis using CMS Nursing Home Compare data to examine differences between rural and nonrural facilities.

PubMed

Lutfiyya, May Nawal; Gessert, Charles E; Lipsky, Martin S

2013-08-01

Advances in medicine and an aging US population suggest that there will be an increasing demand for nursing home services. Although nursing homes are highly regulated and scrutinized, their quality remains a concern and may be a greater issue to those living in rural communities. Despite this, few studies have investigated differences in the quality of nursing home care across the rural-urban continuum. The purpose of this study was to compare the quality of rural and nonrural nursing homes by using aggregated rankings on multiple quality measures calculated by the Centers for Medicare and Medicaid Services and reported on their Nursing Home Compare Web site. Independent-sample t tests were performed to compare the mean ratings on the reported quality measures of rural and nonrural nursing homes. A linear mixed binary logistic regression model controlling for state was performed to determine if the covariates of ownership, number of beds, and geographic locale were associated with a higher overall quality rating. Of the 15,177 nursing homes included in the study sample, 69.2% were located in nonrural areas and 30.8% in rural areas. The t test analysis comparing the overall, health inspection, staffing, and quality measure ratings of rural and nonrural nursing homes yielded statistically significant results for 3 measures, 2 of which (overall ratings and health inspections) favored rural nursing homes. Although a higher percentage of nursing homes (44.8%-42.2%) received a 4-star or higher rating, regression analysis using an overall rating of 4 stars or higher as the dependent variable revealed that when controlling for state and adjusting for size and ownership, rural nursing homes were less likely to have a 4-star or higher rating when compared with nonrural nursing homes (OR = .901, 95% CI 0.824-0.986). Mixed model logistic regression analysis suggested that rural nursing home quality was not comparable to that of nonrural nursing homes. When controlling for state and adjusting for nursing home size and ownership, rural nursing homes were not as likely to earn a 4-or higher star quality rating as nonrural nursing homes. Copyright © 2013 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.

Determinants and consequences of short birth interval in rural Bangladesh: a cross-sectional study.

PubMed

de Jonge, Hendrik C C; Azad, Kishwar; Seward, Nadine; Kuddus, Abdul; Shaha, Sanjit; Beard, James; Costello, Anthony; Houweling, Tanja A J; Fottrell, Ed

2014-12-24

Short birth intervals are known to have negative effects on pregnancy outcomes. We analysed data from a large population surveillance system in rural Bangladesh to identify predictors of short birth interval and determine consequences of short intervals on pregnancy outcomes. The study was conducted in three districts of Bangladesh - Bogra, Moulavibazar and Faridpur (population 282,643, 54,668 women of reproductive age). We used data between January 2010 and June 2011 from a key informant surveillance system that recorded all births, deaths and stillbirths. Short birth interval was defined as an interval between consecutive births of less than 33 months. Initially, risk factors of a short birth interval were determined using a multivariate mixed effects logistic regression model. Independent risk factors were selected using a priori knowledge from literature review. An adjusted mixed effects logistic regression model was then used to determine the effect of up to 21-, 21-32-, 33-44- and 45-month and higher birth-to-birth intervals on pregnancy outcomes controlling for confounders selected through a directed acyclic graph. We analysed 5,571 second or higher order deliveries. Average birth interval was 55 months and 1368/5571 women (24.6%) had a short birth interval (<33 months). Younger women (AOR 1.11 95% CI 1.08-1.15 per year increase in age), women who started their reproductive life later (AOR 0.95, 0.92-0.98 per year) and those who achieve higher order parities were less likely to experience short birth intervals (AOR 0.28, 0.19-0.41 parity 4 compared to 1). Women who were socioeconomically disadvantaged were more likely to experience a short birth interval (AOR 1.42, 1.22-1.65) and a previous adverse outcome was an important determinant of interval (AOR 2.10, 1.83-2.40). Very short birth intervals of less than 21 months were associated with increased stillbirth rate (AOR 2.13, 95% CI 1.28-3.53) and neonatal mortality (AOR 2.28 95% CI 1.28-4.05). Birth spacing remains a reproductive health problem in Bangladesh. Disadvantaged women are more likely to experience short birth intervals and to have increased perinatal deaths. Research into causal pathways and strategies to improve spacing between pregnancies should be intensified.

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.

[Study on the multilevel and longitudinal association between red meat consumption and changes in body mass index, body weight and risk of incident overweight among Chinese adults].

PubMed

Wang, Zhi-hong; Zhang, Bing; Wang, Hui-jun; Zhang, Ji-guo; DU, Wen-wen; Su, Chang; Zhang, Ji; Zhai, Feng-ying

2013-07-01

To examine the longitudinal association between red meat consumption and changes in body mass index(BMI), body weight and overweight risk in Chinese adults. Data from the open, prospective cohort study 'China Health and Nutrition Survey' (CHNS), 18 006 adults(47.5% males)were chosen as the study subjects who participated in at least one wave of survey between 1991 and 2009. Three-level(community-individual-measure occasion) mixed effect modeling was performed to investigate the effect of red meat consumption on BMI, body weight changes and risk of overweight. The average daily red meat intake was assessed using consecutive 3 d 24 h recalls. In general, participants with higher red meat intake appeared to be those with younger age, higher personal income and higher education level, lower physical activities, higher total energy intake, smokers and alcohol drinkers. 3-level mixed-effects linear regression models showed that red meat intake was positively associated with changes in BMI and body weight. Compared to those who consumed no red meat, men and women in the highest quartile of red meat intake showed an increase of 0.17(95% CI:0.08-0.26, P < 0.0001)and 0.12 kg/m(2) (95%CI:0.02-0.22, P < 0.05) on BMI and increase of 596 g (95%CI:329-864, P < 0.0001) and 400 g (95%CI:164-636, P < 0.0001) on body weight, respectively, after adjustment for potential confounders (age, income, education, smoking, alcohol, physical activity level, community urbanization index and total energy intake). After adjustment for above confounders and baseline BMI, results from the 3-level mixed effect logistic model indicated that the odds ratios of being overweight in males and females who had the highest quartile of red meat intake were 1.21 (95%CI:1.01-1.46, P < 0.05)and 1.18(95% CI:1.01-1.37, P < 0.05) in comparison with non-consumers of red meat, respectively. Higher red meat intake was associated with increased BMI and body weight, as well as increased overweight risk.

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

[Calculating Pearson residual in logistic regressions: a comparison between SPSS and SAS].

PubMed

Xu, Hao; Zhang, Tao; Li, Xiao-song; Liu, Yuan-yuan

2015-01-01

To compare the results of Pearson residual calculations in logistic regression models using SPSS and SAS. We reviewed Pearson residual calculation methods, and used two sets of data to test logistic models constructed by SPSS and STATA. One model contained a small number of covariates compared to the number of observed. The other contained a similar number of covariates as the number of observed. The two software packages produced similar Pearson residual estimates when the models contained a similar number of covariates as the number of observed, but the results differed when the number of observed was much greater than the number of covariates. The two software packages produce different results of Pearson residuals, especially when the models contain a small number of covariates. Further studies are warranted.

Vehicle Scheduling Schemes for Commercial and Emergency Logistics Integration

PubMed Central

Li, Xiaohui; Tan, Qingmei

2013-01-01

In modern logistics operations, large-scale logistics companies, besides active participation in profit-seeking commercial business, also play an essential role during an emergency relief process by dispatching urgently-required materials to disaster-affected areas. Therefore, an issue has been widely addressed by logistics practitioners and caught researchers' more attention as to how the logistics companies achieve maximum commercial profit on condition that emergency tasks are effectively and performed satisfactorily. In this paper, two vehicle scheduling models are proposed to solve the problem. One is a prediction-related scheme, which predicts the amounts of disaster-relief materials and commercial business and then accepts the business that will generate maximum profits; the other is a priority-directed scheme, which, firstly groups commercial and emergency business according to priority grades and then schedules both types of business jointly and simultaneously by arriving at the maximum priority in total. Moreover, computer-based simulations are carried out to evaluate the performance of these two models by comparing them with two traditional disaster-relief tactics in China. The results testify the feasibility and effectiveness of the proposed models. PMID:24391724

Vehicle scheduling schemes for commercial and emergency logistics integration.

PubMed

Li, Xiaohui; Tan, Qingmei

2013-01-01

In modern logistics operations, large-scale logistics companies, besides active participation in profit-seeking commercial business, also play an essential role during an emergency relief process by dispatching urgently-required materials to disaster-affected areas. Therefore, an issue has been widely addressed by logistics practitioners and caught researchers' more attention as to how the logistics companies achieve maximum commercial profit on condition that emergency tasks are effectively and performed satisfactorily. In this paper, two vehicle scheduling models are proposed to solve the problem. One is a prediction-related scheme, which predicts the amounts of disaster-relief materials and commercial business and then accepts the business that will generate maximum profits; the other is a priority-directed scheme, which, firstly groups commercial and emergency business according to priority grades and then schedules both types of business jointly and simultaneously by arriving at the maximum priority in total. Moreover, computer-based simulations are carried out to evaluate the performance of these two models by comparing them with two traditional disaster-relief tactics in China. The results testify the feasibility and effectiveness of the proposed models.

A Multi-Stage Reverse Logistics Network Problem by Using Hybrid Priority-Based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lee, Jeong-Eun; Gen, Mitsuo; Rhee, Kyong-Gu

Today remanufacturing problem is one of the most important problems regarding to the environmental aspects of the recovery of used products and materials. Therefore, the reverse logistics is gaining become power and great potential for winning consumers in a more competitive context in the future. This paper considers the multi-stage reverse Logistics Network Problem (m-rLNP) while minimizing the total cost, which involves reverse logistics shipping cost and fixed cost of opening the disassembly centers and processing centers. In this study, we first formulate the m-rLNP model as a three-stage logistics network model. Following for solving this problem, we propose a Genetic Algorithm pri (GA) with priority-based encoding method consisting of two stages, and introduce a new crossover operator called Weight Mapping Crossover (WMX). Additionally also a heuristic approach is applied in the 3rd stage to ship of materials from processing center to manufacturer. Finally numerical experiments with various scales of the m-rLNP models demonstrate the effectiveness and efficiency of our approach by comparing with the recent researches.

A continuous mixing model for pdf simulations and its applications to combusting shear flows

NASA Technical Reports Server (NTRS)

Hsu, A. T.; Chen, J.-Y.

1991-01-01

The problem of time discontinuity (or jump condition) in the coalescence/dispersion (C/D) mixing model is addressed in this work. A C/D mixing model continuous in time is introduced. With the continuous mixing model, the process of chemical reaction can be fully coupled with mixing. In the case of homogeneous turbulence decay, the new model predicts a pdf very close to a Gaussian distribution, with finite higher moments also close to that of a Gaussian distribution. Results from the continuous mixing model are compared with both experimental data and numerical results from conventional C/D models.

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.

Contemporary New Zealand coefficients for the Trauma Injury Severity Score: TRISS(NZ).

PubMed

Schluter, Philip J; Cameron, Cate M; Davey, Tamzyn M; Civil, Ian; Orchard, Jodie; Dansey, Rangi; Hamill, James; Naylor, Helen; James, Carolyn; Dorrian, Jenny; Christey, Grant; Pollard, Cliff; McClure, Rod J

2009-09-11

To develop local contemporary coefficients for the Trauma Injury Severity Score in New Zealand, TRISS(NZ), and to evaluate their performance at predicting survival against the original TRISS coefficients. Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until presentation at Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Coefficients were estimated using ordinary and multilevel mixed-effects logistic regression models. 1735 eligible patients were identified, 1672 (96%) injured from a blunt mechanism and 63 (4%) from a penetrating mechanism. For blunt mechanism trauma, 1250 (75%) were male and average age was 38 years (range: 15-94 years). TRISS information was available for 1565 patients of whom 204 (13%) died. Area under the Receiver Operating Characteristic (ROC) curves was 0.901 (95%CI: 0.879-0.923) for the TRISS(NZ) model and 0.890 (95% CI: 0.866-0.913) for TRISS (P<0.001). Insufficient data were available to determine coefficients for penetrating mechanism TRISS(NZ) models. Both TRISS models accurately predicted survival for blunt mechanism trauma. However, TRISS(NZ) coefficients were statistically superior to TRISS coefficients. A strong case exists for replacing TRISS coefficients in the New Zealand benchmarking software with these updated TRISS(NZ) estimates.

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...

A multicriteria decision making approach based on fuzzy theory and credibility mechanism for logistics center location selection.

PubMed

Wang, Bowen; Xiong, Haitao; Jiang, Chengrui

2014-01-01

As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.

A Multicriteria Decision Making Approach Based on Fuzzy Theory and Credibility Mechanism for Logistics Center Location Selection

PubMed Central

Wang, Bowen; Jiang, Chengrui

2014-01-01

As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center. PMID:25215319

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

PubMed

Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

2013-01-01

In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

A Collection of Technical Papers

NASA Technical Reports Server (NTRS)

1995-01-01

Papers presented at the 6th Space Logistics Symposium covered such areas as: The International Space Station; The Hubble Space Telescope; Launch site computer simulation; Integrated logistics support; The Baikonur Cosmodrome; Probabalistic tools for high confidence repair; A simple space station rescue vehicle; Integrated Traffic Model for the International Space Station; Packaging the maintenance shop; Leading edge software support; Storage information management system; Consolidated maintenance inventory logistics planning; Operation concepts for a single stage to orbit vehicle; Mission architecture for human lunar exploration; Logistics of a lunar based solar power satellite scenario; Just in time in space; NASA acquisitions/logistics; Effective transition management; Shuttle logistics; and Revitalized space operations through total quality control management.

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

Forest biomass supply logistics for a power plant using the discrete-event simulation approach

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

Mobini, Mahdi; Sowlati, T.; Sokhansanj, Shahabaddine

This study investigates the logistics of supplying forest biomass to a potential power plant. Due to the complexities in such a supply logistics system, a simulation model based on the framework of Integrated Biomass Supply Analysis and Logistics (IBSAL) is developed in this study to evaluate the cost of delivered forest biomass, the equilibrium moisture content, and carbon emissions from the logistics operations. The model is applied to a proposed case of 300 MW power plant in Quesnel, BC, Canada. The results show that the biomass demand of the power plant would not be met every year. The weighted averagemore » cost of delivered biomass to the gate of the power plant is about C$ 90 per dry tonne. Estimates of equilibrium moisture content of delivered biomass and CO2 emissions resulted from the processes are also provided.« less

A New TS Algorithm for Solving Low-Carbon Logistics Vehicle Routing Problem with Split Deliveries by Backpack-From a Green Operation Perspective.

PubMed

Xia, Yangkun; Fu, Zhuo; Tsai, Sang-Bing; Wang, Jiangtao

2018-05-10

In order to promote the development of low-carbon logistics and economize logistics distribution costs, the vehicle routing problem with split deliveries by backpack is studied. With the help of the model of classical capacitated vehicle routing problem, in this study, a form of discrete split deliveries was designed in which the customer demand can be split only by backpack. A double-objective mathematical model and the corresponding adaptive tabu search (TS) algorithm were constructed for solving this problem. By embedding the adaptive penalty mechanism, and adopting the random neighborhood selection strategy and reinitialization principle, the global optimization ability of the new algorithm was enhanced. Comparisons with the results in the literature show the effectiveness of the proposed algorithm. The proposed method can save the costs of low-carbon logistics and reduce carbon emissions, which is conducive to the sustainable development of low-carbon logistics.

Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease.

PubMed

Abraham, Gad; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

2013-02-01

A central goal of medical genetics is to accurately predict complex disease from genotypes. Here, we present a comprehensive analysis of simulated and real data using lasso and elastic-net penalized support-vector machine models, a mixed-effects linear model, a polygenic score, and unpenalized logistic regression. In simulation, the sparse penalized models achieved lower false-positive rates and higher precision than the other methods for detecting causal SNPs. The common practice of prefiltering SNP lists for subsequent penalized modeling was examined and shown to substantially reduce the ability to recover the causal SNPs. Using genome-wide SNP profiles across eight complex diseases within cross-validation, lasso and elastic-net models achieved substantially better predictive ability in celiac disease, type 1 diabetes, and Crohn's disease, and had equivalent predictive ability in the rest, with the results in celiac disease strongly replicating between independent datasets. We investigated the effect of linkage disequilibrium on the predictive models, showing that the penalized methods leverage this information to their advantage, compared with methods that assume SNP independence. Our findings show that sparse penalized approaches are robust across different disease architectures, producing as good as or better phenotype predictions and variance explained. This has fundamental ramifications for the selection and future development of methods to genetically predict human disease. © 2012 WILEY PERIODICALS, INC.

Personalized glucose-insulin model based on signal analysis.

PubMed

Goede, Simon L; de Galan, Bastiaan E; Leow, Melvin Khee Shing

2017-04-21

Glucose plasma measurements for diabetes patients are generally presented as a glucose concentration-time profile with 15-60min time scale intervals. This limited resolution obscures detailed dynamic events of glucose appearance and metabolism. Measurement intervals of 15min or more could contribute to imperfections in present diabetes treatment. High resolution data from mixed meal tolerance tests (MMTT) for 24 type 1 and type 2 diabetes patients were used in our present modeling. We introduce a model based on the physiological properties of transport, storage and utilization. This logistic approach follows the principles of electrical network analysis and signal processing theory. The method mimics the physiological equivalent of the glucose homeostasis comprising the meal ingestion, absorption via the gastrointestinal tract (GIT) to the endocrine nexus between the liver, pancreatic alpha and beta cells. This model demystifies the metabolic 'black box' by enabling in silico simulations and fitting of individual responses to clinical data. Five-minute intervals MMTT data measured from diabetic subjects result in two independent model parameters that characterize the complete glucose system response at a personalized level. From the individual data measurements, we obtain a model which can be analyzed with a standard electrical network simulator for diagnostics and treatment optimization. The insulin dosing time scale can be accurately adjusted to match the individual requirements of characterized diabetic patients without the physical burden of treatment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

Tennis Elbow Diagnosis Using Equivalent Uniform Voltage to Fit the Logistic and the Probit Diseased Probability Models

PubMed Central

Lin, Wei-Chun; Lin, Shu-Yuan; Wu, Li-Fu; Guo, Shih-Sian; Huang, Hsiang-Jui; Chao, Pei-Ju

2015-01-01

To develop the logistic and the probit models to analyse electromyographic (EMG) equivalent uniform voltage- (EUV-) response for the tenderness of tennis elbow. In total, 78 hands from 39 subjects were enrolled. In this study, surface EMG (sEMG) signal is obtained by an innovative device with electrodes over forearm region. The analytical endpoint was defined as Visual Analog Score (VAS) 3+ tenderness of tennis elbow. The logistic and the probit diseased probability (DP) models were established for the VAS score and EMG absolute voltage-time histograms (AVTH). TV50 is the threshold equivalent uniform voltage predicting a 50% risk of disease. Twenty-one out of 78 samples (27%) developed VAS 3+ tenderness of tennis elbow reported by the subject and confirmed by the physician. The fitted DP parameters were TV50 = 153.0 mV (CI: 136.3–169.7 mV), γ 50 = 0.84 (CI: 0.78–0.90) and TV50 = 155.6 mV (CI: 138.9–172.4 mV), m = 0.54 (CI: 0.49–0.59) for logistic and probit models, respectively. When the EUV ≥ 153 mV, the DP of the patient is greater than 50% and vice versa. The logistic and the probit models are valuable tools to predict the DP of VAS 3+ tenderness of tennis elbow. PMID:26380281

Quantitative microbial risk assessment for Escherichia coli O157:H7, Salmonella enterica, and Listeria monocytogenes in leafy green vegetables consumed at salad bars, based on modeling supply chain logistics.

PubMed

Tromp, S O; Rijgersberg, H; Franz, E

2010-10-01

Quantitative microbial risk assessments do not usually account for the planning and ordering mechanisms (logistics) of a food supply chain. These mechanisms and consumer demand determine the storage and delay times of products. The aim of this study was to quantitatively assess the difference between simulating supply chain logistics (MOD) and assuming fixed storage times (FIX) in microbial risk estimation for the supply chain of fresh-cut leafy green vegetables destined for working-canteen salad bars. The results of the FIX model were previously published (E. Franz, S. O. Tromp, H. Rijgersberg, and H. J. van der Fels-Klerx, J. Food Prot. 73:274-285, 2010). Pathogen growth was modeled using stochastic discrete-event simulation of the applied logistics concept. The public health effects were assessed by conducting an exposure assessment and risk characterization. The relative growths of Escherichia coli O157 (17%) and Salmonella enterica (15%) were identical in the MOD and FIX models. In contrast, the relative growth of Listeria monocytogenes was considerably higher in the MOD model (1,156%) than in the FIX model (194%). The probability of L. monocytogenes infection in The Netherlands was higher in the MOD model (5.18×10(-8)) than in the FIX model (1.23×10(-8)). The risk of listeriosis-induced fetal mortality in the perinatal population increased from 1.24×10(-4) (FIX) to 1.66×10(-4) (MOD). Modeling the probabilistic nature of supply chain logistics is of additional value for microbial risk assessments regarding psychrotrophic pathogens in food products for which time and temperature are the postharvest preventive measures in guaranteeing food safety.

Organizational Learning, Strategic Flexibility and Business Model Innovation: An Empirical Research Based on Logistics Enterprises

NASA Astrophysics Data System (ADS)

Bao, Yaodong; Cheng, Lin; Zhang, Jian

Using the data of 237 Jiangsu logistics firms, this paper empirically studies the relationship among organizational learning capability, business model innovation, strategic flexibility. The results show as follows; organizational learning capability has positive impacts on business model innovation performance; strategic flexibility plays mediating roles on the relationship between organizational learning capability and business model innovation; interaction among strategic flexibility, explorative learning and exploitative learning play significant roles in radical business model innovation and incremental business model innovation.

A time dependent mixing model to close PDF equations for transport in heterogeneous aquifers

NASA Astrophysics Data System (ADS)

Schüler, L.; Suciu, N.; Knabner, P.; Attinger, S.

2016-10-01

Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the concentration variance, used in moment methods. The mixing model, describing the transport of the PDF in concentration space, is essential for both methods. Finding a satisfactory mixing model is still an open question and due to the rather elaborate PDF methods, a difficult undertaking. Both the PDF equation and the concentration variance equation depend on the same mixing model. This connection is used to find and test an improved mixing model for the much easier to handle concentration variance. Subsequently, this mixing model is transferred to the PDF equation and tested. The newly proposed mixing model yields significantly improved results for both variance modelling and PDF modelling.

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…

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.

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.

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.

Unifying error structures in commonly used biotracer mixing models.

PubMed

Stock, Brian C; Semmens, Brice X

2016-10-01

Mixing models are statistical tools that use biotracers to probabilistically estimate the contribution of multiple sources to a mixture. These biotracers may include contaminants, fatty acids, or stable isotopes, the latter of which are widely used in trophic ecology to estimate the mixed diet of consumers. Bayesian implementations of mixing models using stable isotopes (e.g., MixSIR, SIAR) are regularly used by ecologists for this purpose, but basic questions remain about when each is most appropriate. In this study, we describe the structural differences between common mixing model error formulations in terms of their assumptions about the predation process. We then introduce a new parameterization that unifies these mixing model error structures, as well as implicitly estimates the rate at which consumers sample from source populations (i.e., consumption rate). Using simulations and previously published mixing model datasets, we demonstrate that the new error parameterization outperforms existing models and provides an estimate of consumption. Our results suggest that the error structure introduced here will improve future mixing model estimates of animal diet. © 2016 by the Ecological Society of America.

Lagrangian mixed layer modeling of the western equatorial Pacific

NASA Technical Reports Server (NTRS)

Shinoda, Toshiaki; Lukas, Roger

1995-01-01

Processes that control the upper ocean thermohaline structure in the western equatorial Pacific are examined using a Lagrangian mixed layer model. The one-dimensional bulk mixed layer model of Garwood (1977) is integrated along the trajectories derived from a nonlinear 1 1/2 layer reduced gravity model forced with actual wind fields. The Global Precipitation Climatology Project (GPCP) data are used to estimate surface freshwater fluxes for the mixed layer model. The wind stress data which forced the 1 1/2 layer model are used for the mixed layer model. The model was run for the period 1987-1988. This simple model is able to simulate the isothermal layer below the mixed layer in the western Pacific warm pool and its variation. The subduction mechanism hypothesized by Lukas and Lindstrom (1991) is evident in the model results. During periods of strong South Equatorial Current, the warm and salty mixed layer waters in the central Pacific are subducted below the fresh shallow mixed layer in the western Pacific. However, this subduction mechanism is not evident when upwelling Rossby waves reach the western equatorial Pacific or when a prominent deepening of the mixed layer occurs in the western equatorial Pacific or when a prominent deepening of the mixed layer occurs in the western equatorial Pacific due to episodes of strong wind and light precipitation associated with the El Nino-Southern Oscillation. Comparison of the results between the Lagrangian mixed layer model and a locally forced Eulerian mixed layer model indicated that horizontal advection of salty waters from the central Pacific strongly affects the upper ocean salinity variation in the western Pacific, and that this advection is necessary to maintain the upper ocean thermohaline structure in this region.

Stop consonant voicing in young children's speech: Evidence from a cross-sectional study

NASA Astrophysics Data System (ADS)

Ganser, Emily

There are intuitive reasons to believe that speech-sound acquisition and language acquisition should be related in development. Surprisingly, only recently has research begun to parse just how the two might be related. This study investigated possible correlations between speech-sound acquisition and language acquisition, as part of a large-scale, longitudinal study of the relationship between different types of phonological development and vocabulary growth in the preschool years. Productions of voiced and voiceless stop-initial words were recorded from 96 children aged 28-39 months. Voice Onset Time (VOT, in ms) for each token context was calculated. A mixed-model logistic regression was calculated which predicted whether the sound was intended to be voiced or voiceless based on its VOT. This model estimated the slopes of the logistic function for each child. This slope was referred to as Robustness of Contrast (based on Holliday, Reidy, Beckman, and Edwards, 2015), defined as being the degree of categorical differentiation between the production of two speech sounds or classes of sounds, in this case, voiced and voiceless stops. Results showed a wide range of slopes for individual children, suggesting that slope-derived Robustness of Contrast could be a viable means of measuring a child's acquisition of the voicing contrast. Robustness of Contrast was then compared to traditional measures of speech and language skills to investigate whether there was any correlation between the production of stop voicing and broader measures of speech and language development. The Robustness of Contrast measure was found to correlate with all individual measures of speech and language, suggesting that it might indeed be predictive of later language skills.

Appraisal of levels and patterns of occupational exposure to 1,3-butadiene.

PubMed

Scarselli, Alberto; Corfiati, Marisa; Di Marzi, Davide; Iavicoli, Sergio

2017-09-01

Objectives 1,3-butadiene is classified as carcinogenic to human by inhalation and the association with leukemia has been observed in several epidemiological studies. The aim of this study was to evaluate data about occupational exposure levels to 1,3-butadiene in the Italian working force. Methods Airborne concentrations of 1,3-butadiene were extracted from the Italian database on occupational exposure to carcinogens in the period 1996-2015. Descriptive statistics were calculated for exposure-related variables. An analysis through linear mixed model was performed to determine factors influencing the exposure level. The probability of exceeding the exposure limit was predicted using a mixed-effects logistic model. Concurrent exposures with other occupational carcinogens were investigated using the two-step cluster analysis. Results The total number of exposure measurements selected was 23 885, with an overall arithmetic mean of 0.12 mg/m3. The economic sector with the highest number of measurements was manufacturing of chemicals (18 744). The most predictive variables of the exposure level resulted to be the occupational group and its interaction with the measurement year. The highest likelihood of exceeding the exposure limit was found in the manufacture of coke and refined petroleum products. Concurrent exposures were frequently detected, mainly with benzene, acrylonitrile and ethylene dichloride, and three main clusters were identified. Conclusions Exposure to 1,3-butadiene occurs in a wide variety of activity sectors and occupational groups. The use of several statistical analysis methods applied to occupational exposure databases can help to identify exposure situations at high risk for workers' health and better target preventive interventions and research projects.

Disassortative Age-Mixing Does Not Explain Differences in HIV Prevalence between Young White and Black MSM: Findings from Four Studies

PubMed Central

Grey, Jeremy Alexander; Rothenberg, Richard B.; Sullivan, Patrick Sean; Rosenberg, Eli Samuel

2015-01-01

Objective Age disassortativity is one hypothesis for HIV disparities between Black and White MSM. We examined differences in age mixing by race and the effect of partner age difference on the association between race and HIV status. Design We used data from four studies of MSM. Participants reported information about recent sexual partners, including age, race, and sexual behavior. Two studies were online with a US sample and two focused on MSM in Atlanta. Methods We computed concordance correlation coefficients (CCCs) by race across strata of partner type, participant HIV status, condom use, and number of partners. We used Wilcoxon rank-sum tests to compare Black and White MSM on partner age differences across five age groups. Finally, we used logistic regression models using race, age, and partner age difference to determine the odds ratio of HIV-positive serostatus. Results Of 48 CCC comparisons, Black MSM were more age-disassortative than White MSM in only two. Furthermore, of 20 comparisons of median partner age, Black and White MSM differed in two age groups. One indicated larger age gaps among the Black MSM (18-19). Prevalent HIV infection was associated with race and age. Including partner age difference in the model resulted in a 2% change in the relative odds of infection among Black MSM. Conclusions Partner age disassortativity and partner age differences do not differ by race. Partner age difference offers little predictive value in understanding prevalent HIV infection among Black and White MSM, including diagnosis of HIV-positive status among self-reported HIV-negative individuals. PMID:26090814

Are there nutritional and other benefits associated with family meals among at-risk youth?

PubMed

Fulkerson, Jayne A; Kubik, Martha Y; Story, Mary; Lytle, Leslie; Arcan, Chrisa

2009-10-01

The literature suggests positive associations between family dinner frequency and dietary practices and psychosocial well-being, and inverse associations between family dinner frequency and overweight status among general adolescent populations. The present study aims to examine these associations among a population of adolescents at-risk of academic failure. A racially diverse sample of adolescents (n = 145, 52% male, 61% nonwhite) from six alternative high schools (AHS) completed surveys and had their heights and weights measured by trained research staff. Mixed-model logistic regression analyses assessed associations between family dinner frequency and overweight status, healthy and unhealthy weight management, and food insecurity, whereas mixed linear models assessed associations with breakfast consumption, fruit and vegetable consumption, high-fat food intake, fast food intake, substance use, and depressive symptoms. Analyses adjusted for race/ethnicity, age, gender, socioeconomic status, and the random effect of school. Family dinner frequency was positively associated with breakfast consumption and fruit intake (p < .01 and p < .05, respectively), and inversely associated with depressive symptoms (p < .05). Adolescents who reported never eating family dinner were significantly more likely to be overweight (odds ratio [OR] = 2.8, confidence interval [CI] = 1.1-6.9) and food insecure (OR = 6.0, CI = 2.2-16.4) than adolescents who reported five to seven family meals per week. In this at-risk sample of youth, some, but not all of the benefits of family meals found in other studies were apparent. Intervention programs to increase the availability and affordability of healthful foods and promote family meals for families of AHS students may be beneficial.

Does progressive resistance and balance exercise reduce falls in residential aged care? Randomized controlled trial protocol for the SUNBEAM program.

PubMed

Hewitt, Jennifer; Refshauge, Kathryn M; Goodall, Stephen; Henwood, Timothy; Clemson, Lindy

2014-01-01

Falls are common among older adults. It is reported that approximately 60% of residents of aged care facilities fall each year. This is a major cause of morbidity and mortality, and a significant burden for health care providers and the health system. Among community dwelling older adults, exercise appears to be an effective countermeasure, but data are limited and inconsistent among studies in residents of aged care communities. This trial has been designed to evaluate whether the SUNBEAM program (Strength and Balance Exercise in Aged Care) reduces falls in residents of aged care facilities. Is the program more effective and cost-effective than usual care for the prevention of falls? Single-blinded, two group, cluster randomized trial. 300 residents, living in 20 aged care facilities. Progressive resistance and balance training under the guidance of a physiotherapist for 6 months, then facility-guided maintenance training for 6 months. Usual care. Number of falls, number of fallers, quality of life, mobility, balance, fear of falling, cognitive well-being, resource use, and cost-effectiveness. Measurements will be taken at baseline, 6 months, and 12 months. The number of falls will be analyzed using a Poisson mixed model. A logistic mixed model will be used to analyze the number of residents who fall during the study period. Intention-to-treat analysis will be used. This study addresses a significant shortcoming in aged care research, and has potential to impact upon a substantial health care problem. Outcomes will be used to inform care providers, and guide health care policies.

Genetic contribution to patent ductus arteriosus in the premature newborn.

PubMed

Bhandari, Vineet; Zhou, Gongfu; Bizzarro, Matthew J; Buhimschi, Catalin; Hussain, Naveed; Gruen, Jeffrey R; Zhang, Heping

2009-02-01

The most common congenital heart disease in the newborn population, patent ductus arteriosus, accounts for significant morbidity in preterm newborns. In addition to prematurity and environmental factors, we hypothesized that genetic factors play a significant role in this condition. The objective of this study was to quantify the contribution of genetic factors to the variance in liability for patent ductus arteriosus in premature newborns. A retrospective study (1991-2006) from 2 centers was performed by using zygosity data from premature twins born at < or =36 weeks' gestational age and surviving beyond 36 weeks' postmenstrual age. Patent ductus arteriosus was diagnosed by echocardiography at each center. Mixed-effects logistic regression was used to assess the effect of specific covariates. Latent variable probit modeling was then performed to estimate the heritability of patent ductus arteriosus, and mixed-effects probit modeling was used to quantify the genetic component. We obtained data from 333 dizygotic twin pairs and 99 monozygotic twin pairs from 2 centers (Yale University and University of Connecticut). Data on chorioamnionitis, antenatal steroids, gestational age, body weight, gender, respiratory distress syndrome, patent ductus arteriosus, necrotizing enterocolitis, oxygen supplementation, and bronchopulmonary dysplasia were comparable between monozygotic and dizygotic twins. We found that gestational age, respiratory distress syndrome, and institution were significant covariates for patent ductus arteriosus. After controlling for specific covariates, genetic factors or the shared environment accounted for 76.1% of the variance in liability for patent ductus arteriosus. Preterm patent ductus arteriosus is highly familial (contributed to by genetic and environmental factors), with the effect being mainly environmental, after controlling for known confounders.

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2009-01-01

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

An Order Insertion Scheduling Model of Logistics Service Supply Chain Considering Capacity and Time Factors

PubMed Central

Yang, Yi; Wang, Shuqing; Liu, Yang

2014-01-01

Order insertion often occurs in the scheduling process of logistics service supply chain (LSSC), which disturbs normal time scheduling especially in the environment of mass customization logistics service. This study analyses order similarity coefficient and order insertion operation process and then establishes an order insertion scheduling model of LSSC with service capacity and time factors considered. This model aims to minimize the average unit volume operation cost of logistics service integrator and maximize the average satisfaction degree of functional logistics service providers. In order to verify the viability and effectiveness of our model, a specific example is numerically analyzed. Some interesting conclusions are obtained. First, along with the increase of completion time delay coefficient permitted by customers, the possible inserting order volume first increases and then trends to be stable. Second, supply chain performance reaches the best when the volume of inserting order is equal to the surplus volume of the normal operation capacity in mass service process. Third, the larger the normal operation capacity in mass service process is, the bigger the possible inserting order's volume will be. Moreover, compared to increasing the completion time delay coefficient, improving the normal operation capacity of mass service process is more useful. PMID:25276851

Over the Beach. US Army Amphibious Operations in the Korean War

DTIC Science & Technology

2008-01-01

target of nuclear attack would result in a large and continuing requirement for logistics-over-the­ shore (LOTS) and amphibious resupply operations...Army Ram Fleet, initially under Porter’s control and later under General Ulysses S. Grant, the brigade conducted operations with mixed results until...same period, the Marine Corps underwent changes that would ultimately result in the adoption of landing force operations as its primary mission. The

Miscibility and Thermodynamics of Mixing of Different Models of Formamide and Water in Computer Simulation.

PubMed

Kiss, Bálint; Fábián, Balázs; Idrissi, Abdenacer; Szőri, Milán; Jedlovszky, Pál

2017-07-27

The thermodynamic changes that occur upon mixing five models of formamide and three models of water, including the miscibility of these model combinations itself, is studied by performing Monte Carlo computer simulations using an appropriately chosen thermodynamic cycle and the method of thermodynamic integration. The results show that the mixing of these two components is close to the ideal mixing, as both the energy and entropy of mixing turn out to be rather close to the ideal term in the entire composition range. Concerning the energy of mixing, the OPLS/AA_mod model of formamide behaves in a qualitatively different way than the other models considered. Thus, this model results in negative, while the other ones in positive energy of mixing values in combination with all three water models considered. Experimental data supports this latter behavior. Although the Helmholtz free energy of mixing always turns out to be negative in the entire composition range, the majority of the model combinations tested either show limited miscibility, or, at least, approach the miscibility limit very closely in certain compositions. Concerning both the miscibility and the energy of mixing of these model combinations, we recommend the use of the combination of the CHARMM formamide and TIP4P water models in simulations of water-formamide mixtures.

An Evaluation of Hierarchical Bayes Estimation for the Two- Parameter Logistic Model.

ERIC Educational Resources Information Center

Kim, Seock-Ho

Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item parameters. Simulated data sets were analyzed using two different Bayes estimation procedures, the two-stage hierarchical Bayes estimation (HB2) and the marginal Bayesian with known hyperparameters (MB), and marginal maximum…

Applying the Principles of Specific Objectivity and of Generalizability to the Measurement of Change.

ERIC Educational Resources Information Center

Fischer, Gerhard H.

1987-01-01

A natural parameterization and formalization of the problem of measuring change in dichotomous data is developed. Mathematically-exact definitions of specific objectivity are presented, and the basic structures of the linear logistic test model and the linear logistic model with relaxed assumptions are clarified. (SLD)

Multivariate logistic regression analysis of postoperative complications and risk model establishment of gastrectomy for gastric cancer: A single-center cohort report.

PubMed

Zhou, Jinzhe; Zhou, Yanbing; Cao, Shougen; Li, Shikuan; Wang, Hao; Niu, Zhaojian; Chen, Dong; Wang, Dongsheng; Lv, Liang; Zhang, Jian; Li, Yu; Jiao, Xuelong; Tan, Xiaojie; Zhang, Jianli; Wang, Haibo; Zhang, Bingyuan; Lu, Yun; Sun, Zhenqing

2016-01-01

Reporting of surgical complications is common, but few provide information about the severity and estimate risk factors of complications. If have, but lack of specificity. We retrospectively analyzed data on 2795 gastric cancer patients underwent surgical procedure at the Affiliated Hospital of Qingdao University between June 2007 and June 2012, established multivariate logistic regression model to predictive risk factors related to the postoperative complications according to the Clavien-Dindo classification system. Twenty-four out of 86 variables were identified statistically significant in univariate logistic regression analysis, 11 significant variables entered multivariate analysis were employed to produce the risk model. Liver cirrhosis, diabetes mellitus, Child classification, invasion of neighboring organs, combined resection, introperative transfusion, Billroth II anastomosis of reconstruction, malnutrition, surgical volume of surgeons, operating time and age were independent risk factors for postoperative complications after gastrectomy. Based on logistic regression equation, p=Exp∑BiXi / (1+Exp∑BiXi), multivariate logistic regression predictive model that calculated the risk of postoperative morbidity was developed, p = 1/(1 + e((4.810-1.287X1-0.504X2-0.500X3-0.474X4-0.405X5-0.318X6-0.316X7-0.305X8-0.278X9-0.255X10-0.138X11))). The accuracy, sensitivity and specificity of the model to predict the postoperative complications were 86.7%, 76.2% and 88.6%, respectively. This risk model based on Clavien-Dindo grading severity of complications system and logistic regression analysis can predict severe morbidity specific to an individual patient's risk factors, estimate patients' risks and benefits of gastric surgery as an accurate decision-making tool and may serve as a template for the development of risk models for other surgical groups.

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.

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.

Estimating the Probability of Rare Events Occurring Using a Local Model Averaging.

PubMed

Chen, Jin-Hua; Chen, Chun-Shu; Huang, Meng-Fan; Lin, Hung-Chih

2016-10-01

In statistical applications, logistic regression is a popular method for analyzing binary data accompanied by explanatory variables. But when one of the two outcomes is rare, the estimation of model parameters has been shown to be severely biased and hence estimating the probability of rare events occurring based on a logistic regression model would be inaccurate. In this article, we focus on estimating the probability of rare events occurring based on logistic regression models. Instead of selecting a best model, we propose a local model averaging procedure based on a data perturbation technique applied to different information criteria to obtain different probability estimates of rare events occurring. Then an approximately unbiased estimator of Kullback-Leibler loss is used to choose the best one among them. We design complete simulations to show the effectiveness of our approach. For illustration, a necrotizing enterocolitis (NEC) data set is analyzed. © 2016 Society for Risk Analysis.

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.

A flavor symmetry model for bilarge leptonic mixing and the lepton masses

NASA Astrophysics Data System (ADS)

Ohlsson, Tommy; Seidl, Gerhart

2002-11-01

We present a model for leptonic mixing and the lepton masses based on flavor symmetries and higher-dimensional mass operators. The model predicts bilarge leptonic mixing (i.e., the mixing angles θ12 and θ23 are large and the mixing angle θ13 is small) and an inverted hierarchical neutrino mass spectrum. Furthermore, it approximately yields the experimental hierarchical mass spectrum of the charged leptons. The obtained values for the leptonic mixing parameters and the neutrino mass squared differences are all in agreement with atmospheric neutrino data, the Mikheyev-Smirnov-Wolfenstein large mixing angle solution of the solar neutrino problem, and consistent with the upper bound on the reactor mixing angle. Thus, we have a large, but not close to maximal, solar mixing angle θ12, a nearly maximal atmospheric mixing angle θ23, and a small reactor mixing angle θ13. In addition, the model predicts θ 12≃ {π}/{4}-θ 13.

Microbiological risk from minimally processed packaged salads in the Dutch food chain.

PubMed

Pielaat, Annemarie; van Leusden, Frans M; Wijnands, Lucas M

2014-03-01

The objective of this study was to evaluate the microbial hazard associated with the consumption of mixed salads produced under standard conditions. The presence of Salmonella, Campylobacter spp., and Escherichia coli O157 in the Dutch production chain of mixed salads was determined. Microbial prevalence and concentration data from a microbiological surveillance study were used as inputs for the quantitative microbial risk assessment. Chain logistics, production figures, and consumption patterns were combined with the survey data for the risk assessment chain approach. The results of the sample analysis were used to track events from contamination through human illness. Wide 95% confidence intervals around the mean were found for estimated annual numbers of illnesses resulting from the consumption of mixed salads contaminated with Salmonella Typhimurium DT104 (0 to 10,300 cases), Campylobacter spp. (0 to 92,000 cases), or E. coli (0 to 800 cases). The main sources of uncertainty are the lack of decontamination data (i.e., produce washing during processing) and an appropriate dose-response relationship.

Clinical, polysomnographic, and CPAP titration features of obstructive sleep apnea: Mixed versus purely obstructive type.

PubMed

Lee, Sang-Ahm; Lee, Gha-Hyun; Chung, Yoo-Sam; Kim, Woo Sung

2015-08-15

To determine whether obstructive sleep apnea syndrome (OSAS) patients with mixed sleep apnea (MSA) have different clinical, polysomnographic, and continuous positive airway pressure (CPAP) titration findings compared to OSAS patients without MSA. We retrospectively reviewed the records of OSAS patients who had undergone CPAP titration and categorized them into pure-OSA and mixed-OSA groups. Demographic features, daytime sleepiness, and apnea severity were compared between the two groups using univariate and multivariate analyses. CPAP titration findings were also compared between the two groups. One hundred and ninety-five subjects (n=126 pure-OSA; n=69 mixed-OSA) were included in the analysis. Compared to the pure-OSA group, the mixed-OSA group had a higher percentage of males (p=0.003) and a higher body mass index (p=0.044), Epworth Sleepiness Scale score (p=0.028), and apnea-hypopnea index (AHI) (p<0.001). In logistic regression analysis, older age, male sex, and higher body mass index were independently associated with mixed-OSA before PSG study. When using AHI as a covariable, the higher AHI with older age, male sex, and daytime sleepiness was independently related to mixed-OSA. The mixed-OSA group had a higher percentage of patients with complex sleep apnea, a lower percentage of patients with optimal titration, and a higher titrated pressure than the pure-OSA group. Severe OSA, older age, male sex, obesity, and daytime sleepiness were related to mixed-OSA. Complex sleep apnea, less optimal titration, and a higher titrated CPAP were also associated with MSA in OSAS patients. Copyright © 2015 Elsevier B.V. All rights reserved.

Building a Decision Support System for Inpatient Admission Prediction With the Manchester Triage System and Administrative Check-in Variables.

PubMed

Zlotnik, Alexander; Alfaro, Miguel Cuchí; Pérez, María Carmen Pérez; Gallardo-Antolín, Ascensión; Martínez, Juan Manuel Montero

2016-05-01

The usage of decision support tools in emergency departments, based on predictive models, capable of estimating the probability of admission for patients in the emergency department may give nursing staff the possibility of allocating resources in advance. We present a methodology for developing and building one such system for a large specialized care hospital using a logistic regression and an artificial neural network model using nine routinely collected variables available right at the end of the triage process.A database of 255.668 triaged nonobstetric emergency department presentations from the Ramon y Cajal University Hospital of Madrid, from January 2011 to December 2012, was used to develop and test the models, with 66% of the data used for derivation and 34% for validation, with an ordered nonrandom partition. On the validation dataset areas under the receiver operating characteristic curve were 0.8568 (95% confidence interval, 0.8508-0.8583) for the logistic regression model and 0.8575 (95% confidence interval, 0.8540-0. 8610) for the artificial neural network model. χ Values for Hosmer-Lemeshow fixed "deciles of risk" were 65.32 for the logistic regression model and 17.28 for the artificial neural network model. A nomogram was generated upon the logistic regression model and an automated software decision support system with a Web interface was built based on the artificial neural network model.

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.

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.…

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…

A Model for Logistics Systems Engineering Management Education in Europe.

ERIC Educational Resources Information Center

Naim, M.; Lalwani, C.; Fortuin, L.; Schmidt, T.; Taylor, J.; Aronsson, H.

2000-01-01

Presents the need for a systems and process perspective of logistics, and develops a template for a logistics education course. The template addresses functional, process, and supply chain needs and was developed by a number of university partners with core skills in different traditional disciplines. (Contains 31 references.) (Author/WRM)

A Methodology for Generating Placement Rules that Utilizes Logistic Regression

ERIC Educational Resources Information Center

Wurtz, Keith

2008-01-01

The purpose of this article is to provide the necessary tools for institutional researchers to conduct a logistic regression analysis and interpret the results. Aspects of the logistic regression procedure that are necessary to evaluate models are presented and discussed with an emphasis on cutoff values and choosing the appropriate number of…

Mixed Membership Distributions with Applications to Modeling Multiple Strategy Usage

ERIC Educational Resources Information Center

Galyardt, April

2012-01-01

This dissertation examines two related questions. "How do mixed membership models work?" and "Can mixed membership be used to model how students use multiple strategies to solve problems?". Mixed membership models have been used in thousands of applications from text and image processing to genetic microarray analysis. Yet…

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.

An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry.

PubMed

Tung, Feng-Cheng; Chang, Su-Chao; Chou, Chi-Min

2008-05-01

Ever since National Health Insurance was introduced in 1995, the number of insurants increased to over 96% from 50 to 60%, with a continuous satisfaction rating of about 70%. However, the premium accounted for 5.77% of GDP in 2001 and the Bureau of National Health Insurance had pressing financial difficulties, so it reformed its expenditure systems, such as fee for service, capitation, case payment and the global budget system in order to control the rising medical costs. Since the change in health insurance policy, most hospitals attempted to reduce their operating expenses and improve efficiency. Introducing the electronic logistics information system is one way of reducing the cost of the department of central warehouse and the nursing stations. Hence, the study proposes a technology acceptance research model and examines how nurses' acceptance of the e-logistics information system has been affected in the medical industry. This research combines innovation diffusion theory, technology acceptance model and added two research parameters, trust and perceived financial cost to propose a new hybrid technology acceptance model. Taking Taiwan's medical industry as an experimental example, this paper studies nurses' acceptance of the electronic logistics information system. The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to examine the reliability and validity of the measurement model. The results of the survey strongly support the new hybrid technology acceptance model in predicting nurses' intention to use the electronic logistics information system. The study shows that 'compatibility', 'perceived usefulness', 'perceived ease of use', and 'trust' all have great positive influence on 'behavioral intention to use'. On the other hand 'perceived financial cost' has great negative influence on behavioral intention to use.

Alternative approach to modeling bacterial lag time, using logistic regression as a function of time, temperature, pH, and sodium chloride concentration.

PubMed

Koseki, Shige; Nonaka, Junko

2012-09-01

The objective of this study was to develop a probabilistic model to predict the end of lag time (λ) during the growth of Bacillus cereus vegetative cells as a function of temperature, pH, and salt concentration using logistic regression. The developed λ model was subsequently combined with a logistic differential equation to simulate bacterial numbers over time. To develop a novel model for λ, we determined whether bacterial growth had begun, i.e., whether λ had ended, at each time point during the growth kinetics. The growth of B. cereus was evaluated by optical density (OD) measurements in culture media for various pHs (5.5 ∼ 7.0) and salt concentrations (0.5 ∼ 2.0%) at static temperatures (10 ∼ 20°C). The probability of the end of λ was modeled using dichotomous judgments obtained at each OD measurement point concerning whether a significant increase had been observed. The probability of the end of λ was described as a function of time, temperature, pH, and salt concentration and showed a high goodness of fit. The λ model was validated with independent data sets of B. cereus growth in culture media and foods, indicating acceptable performance. Furthermore, the λ model, in combination with a logistic differential equation, enabled a simulation of the population of B. cereus in various foods over time at static and/or fluctuating temperatures with high accuracy. Thus, this newly developed modeling procedure enables the description of λ using observable environmental parameters without any conceptual assumptions and the simulation of bacterial numbers over time with the use of a logistic differential equation.

Neural network modeling for surgical decisions on traumatic brain injury patients.

PubMed

Li, Y C; Liu, L; Chiu, W T; Jian, W S

2000-01-01

Computerized medical decision support systems have been a major research topic in recent years. Intelligent computer programs were implemented to aid physicians and other medical professionals in making difficult medical decisions. This report compares three different mathematical models for building a traumatic brain injury (TBI) medical decision support system (MDSS). These models were developed based on a large TBI patient database. This MDSS accepts a set of patient data such as the types of skull fracture, Glasgow Coma Scale (GCS), episode of convulsion and return the chance that a neurosurgeon would recommend an open-skull surgery for this patient. The three mathematical models described in this report including a logistic regression model, a multi-layer perceptron (MLP) neural network and a radial-basis-function (RBF) neural network. From the 12,640 patients selected from the database. A randomly drawn 9480 cases were used as the training group to develop/train our models. The other 3160 cases were in the validation group which we used to evaluate the performance of these models. We used sensitivity, specificity, areas under receiver-operating characteristics (ROC) curve and calibration curves as the indicator of how accurate these models are in predicting a neurosurgeon's decision on open-skull surgery. The results showed that, assuming equal importance of sensitivity and specificity, the logistic regression model had a (sensitivity, specificity) of (73%, 68%), compared to (80%, 80%) from the RBF model and (88%, 80%) from the MLP model. The resultant areas under ROC curve for logistic regression, RBF and MLP neural networks are 0.761, 0.880 and 0.897, respectively (P < 0.05). Among these models, the logistic regression has noticeably poorer calibration. This study demonstrated the feasibility of applying neural networks as the mechanism for TBI decision support systems based on clinical databases. The results also suggest that neural networks may be a better solution for complex, non-linear medical decision support systems than conventional statistical techniques such as logistic regression.

Dynamics of a stochastic HIV-1 infection model with logistic growth

NASA Astrophysics Data System (ADS)

Jiang, Daqing; Liu, Qun; Shi, Ningzhong; Hayat, Tasawar; Alsaedi, Ahmed; Xia, Peiyan

2017-03-01

This paper is concerned with a stochastic HIV-1 infection model with logistic growth. Firstly, by constructing suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence of ergodic stationary distribution of the solution to the HIV-1 infection model. Then we obtain sufficient conditions for extinction of the infection. The stationary distribution shows that the infection can become persistent in vivo.

Enhancement of the Logistics Battle Command Model: Architecture Upgrades and Attrition Module Development

DTIC Science & Technology

2017-01-05

module. 15. SUBJECT TERMS Logistics, attrition, discrete event simulation, Simkit, LBC 16. SECURITY CLASSIFICATION OF: Unclassified 17. LIMITATION...stochastics, and discrete event model programmed in Java building largely on the Simkit library. The primary purpose of the LBC model is to support...equations makes them incompatible with the discrete event construct of LBC. Bullard further advances this methodology by developing a stochastic

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…

Effects of Precipitation on Ocean Mixed-Layer Temperature and Salinity as Simulated in a 2-D Coupled Ocean-Cloud Resolving Atmosphere Model

NASA Technical Reports Server (NTRS)

Li, Xiaofan; Sui, C.-H.; Lau, K-M.; Adamec, D.

1999-01-01

A two-dimensional coupled ocean-cloud resolving atmosphere model is used to investigate possible roles of convective scale ocean disturbances induced by atmospheric precipitation on ocean mixed-layer heat and salt budgets. The model couples a cloud resolving model with an embedded mixed layer-ocean circulation model. Five experiment are performed under imposed large-scale atmospheric forcing in terms of vertical velocity derived from the TOGA COARE observations during a selected seven-day period. The dominant variability of mixed-layer temperature and salinity are simulated by the coupled model with imposed large-scale forcing. The mixed-layer temperatures in the coupled experiments with 1-D and 2-D ocean models show similar variations when salinity effects are not included. When salinity effects are included, however, differences in the domain-mean mixed-layer salinity and temperature between coupled experiments with 1-D and 2-D ocean models could be as large as 0.3 PSU and 0.4 C respectively. Without fresh water effects, the nocturnal heat loss over ocean surface causes deep mixed layers and weak cooling rates so that the nocturnal mixed-layer temperatures tend to be horizontally-uniform. The fresh water flux, however, causes shallow mixed layers over convective areas while the nocturnal heat loss causes deep mixed layer over convection-free areas so that the mixed-layer temperatures have large horizontal fluctuations. Furthermore, fresh water flux exhibits larger spatial fluctuations than surface heat flux because heavy rainfall occurs over convective areas embedded in broad non-convective or clear areas, whereas diurnal signals over whole model areas yield high spatial correlation of surface heat flux. As a result, mixed-layer salinities contribute more to the density differences than do mixed-layer temperatures.

Simulating land-use changes by incorporating spatial autocorrelation and self-organization in CLUE-S modeling: a case study in Zengcheng District, Guangzhou, China

NASA Astrophysics Data System (ADS)

Mei, Zhixiong; Wu, Hao; Li, Shiyun

2018-06-01

The Conversion of Land Use and its Effects at Small regional extent (CLUE-S), which is a widely used model for land-use simulation, utilizes logistic regression to estimate the relationships between land use and its drivers, and thus, predict land-use change probabilities. However, logistic regression disregards possible spatial autocorrelation and self-organization in land-use data. Autologistic regression can depict spatial autocorrelation but cannot address self-organization, while logistic regression by considering only self-organization (NElogistic regression) fails to capture spatial autocorrelation. Therefore, this study developed a regression (NE-autologistic regression) method, which incorporated both spatial autocorrelation and self-organization, to improve CLUE-S. The Zengcheng District of Guangzhou, China was selected as the study area. The land-use data of 2001, 2005, and 2009, as well as 10 typical driving factors, were used to validate the proposed regression method and the improved CLUE-S model. Then, three future land-use scenarios in 2020: the natural growth scenario, ecological protection scenario, and economic development scenario, were simulated using the improved model. Validation results showed that NE-autologistic regression performed better than logistic regression, autologistic regression, and NE-logistic regression in predicting land-use change probabilities. The spatial allocation accuracy and kappa values of NE-autologistic-CLUE-S were higher than those of logistic-CLUE-S, autologistic-CLUE-S, and NE-logistic-CLUE-S for the simulations of two periods, 2001-2009 and 2005-2009, which proved that the improved CLUE-S model achieved the best simulation and was thereby effective to a certain extent. The scenario simulation results indicated that under all three scenarios, traffic land and residential/industrial land would increase, whereas arable land and unused land would decrease during 2009-2020. Apparent differences also existed in the simulated change sizes and locations of each land-use type under different scenarios. The results not only demonstrate the validity of the improved model but also provide a valuable reference for relevant policy-makers.

Prediction of stock markets by the evolutionary mix-game model

NASA Astrophysics Data System (ADS)

Chen, Fang; Gou, Chengling; Guo, Xiaoqian; Gao, Jieping

2008-06-01

This paper presents the efforts of using the evolutionary mix-game model, which is a modified form of the agent-based mix-game model, to predict financial time series. Here, we have carried out three methods to improve the original mix-game model by adding the abilities of strategy evolution to agents, and then applying the new model referred to as the evolutionary mix-game model to forecast the Shanghai Stock Exchange Composite Index. The results show that these modifications can improve the accuracy of prediction greatly when proper parameters are chosen.

SpaceNet: Modeling and Simulating Space Logistics

NASA Technical Reports Server (NTRS)

Lee, Gene; Jordan, Elizabeth; Shishko, Robert; de Weck, Olivier; Armar, Nii; Siddiqi, Afreen

2008-01-01

This paper summarizes the current state of the art in interplanetary supply chain modeling and discusses SpaceNet as one particular method and tool to address space logistics modeling and simulation challenges. Fundamental upgrades to the interplanetary supply chain framework such as process groups, nested elements, and cargo sharing, enabled SpaceNet to model an integrated set of missions as a campaign. The capabilities and uses of SpaceNet are demonstrated by a step-by-step modeling and simulation of a lunar campaign.

On the effects of nonlinear boundary conditions in diffusive logistic equations on bounded domains

NASA Astrophysics Data System (ADS)

Cantrell, Robert Stephen; Cosner, Chris

We study a diffusive logistic equation with nonlinear boundary conditions. The equation arises as a model for a population that grows logistically inside a patch and crosses the patch boundary at a rate that depends on the population density. Specifically, the rate at which the population crosses the boundary is assumed to decrease as the density of the population increases. The model is motivated by empirical work on the Glanville fritillary butterfly. We derive local and global bifurcation results which show that the model can have multiple equilibria and in some parameter ranges can support Allee effects. The analysis leads to eigenvalue problems with nonstandard boundary conditions.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not possible. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2009-01-01

Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

Model comparison for Escherichia coli growth in pouched food.

PubMed

Fujikawa, Hiroshi; Yano, Kazuyoshi; Morozumi, Satoshi

2006-06-01

We recently studied the growth characteristics of Escherichia coli cells in pouched mashed potatoes (Fujikawa et al., J. Food Hyg. Soc. Japan, 47, 95-98 (2006)). Using those experimental data, in the present study, we compared a logistic model newly developed by us with the modified Gompertz and the Baranyi models, which are used as growth models worldwide. Bacterial growth curves at constant temperatures in the range of 12 to 34 degrees C were successfully described with the new logistic model, as well as with the other models. The Baranyi gave the least error in cell number and our model gave the least error in the rate constant and the lag period. For dynamic temperature, our model successfully predicted the bacterial growth, whereas the Baranyi model considerably overestimated it. Also, there was a discrepancy between the growth curves described with the differential equations of the Baranyi model and those obtained with DMfit, a software program for Baranyi model fitting. These results indicate that the new logistic model can be used to predict bacterial growth in pouched food.

History of falls, gait, balance, and fall risks in older cancer survivors living in the community.

PubMed

Huang, Min H; Shilling, Tracy; Miller, Kara A; Smith, Kristin; LaVictoire, Kayle

2015-01-01

Older cancer survivors may be predisposed to falls because cancer-related sequelae affect virtually all body systems. The use of a history of falls, gait speed, and balance tests to assess fall risks remains to be investigated in this population. This study examined the relationship of previous falls, gait, and balance with falls in community-dwelling older cancer survivors. At the baseline, demographics, health information, and the history of falls in the past year were obtained through interviewing. Participants performed tests including gait speed, Balance Evaluation Systems Test, and short-version of Activities-specific Balance Confidence scale. Falls were tracked by mailing of monthly reports for 6 months. A "faller" was a person with ≥1 fall during follow-up. Univariate analyses, including independent sample t-tests and Fisher's exact tests, compared baseline demographics, gait speed, and balance between fallers and non-fallers. For univariate analyses, Bonferroni correction was applied for multiple comparisons. Baseline variables with P<0.15 were included in a forward logistic regression model to identify factors predictive of falls with age as covariate. Sensitivity and specificity of each predictor of falls in the model were calculated. Significance level for the regression analysis was P<0.05. During follow-up, 59% of participants had one or more falls. Baseline demographics, health information, history of falls, gaits speed, and balance tests did not differ significantly between fallers and non-fallers. Forward logistic regression revealed that a history of falls was a significant predictor of falls in the final model (odds ratio =6.81; 95% confidence interval =1.594-29.074) (P<0.05). Sensitivity and specificity for correctly identifying a faller using the positive history of falls were 74% and 69%, respectively. Current findings suggested that for community-dwelling older cancer survivors with mixed diagnoses, asking about the history of falls may help detect individuals at risk of falling.

History of falls, gait, balance, and fall risks in older cancer survivors living in the community

PubMed Central

Huang, Min H; Shilling, Tracy; Miller, Kara A; Smith, Kristin; LaVictoire, Kayle

2015-01-01

Older cancer survivors may be predisposed to falls because cancer-related sequelae affect virtually all body systems. The use of a history of falls, gait speed, and balance tests to assess fall risks remains to be investigated in this population. This study examined the relationship of previous falls, gait, and balance with falls in community-dwelling older cancer survivors. At the baseline, demographics, health information, and the history of falls in the past year were obtained through interviewing. Participants performed tests including gait speed, Balance Evaluation Systems Test, and short-version of Activities-specific Balance Confidence scale. Falls were tracked by mailing of monthly reports for 6 months. A “faller” was a person with ≥1 fall during follow-up. Univariate analyses, including independent sample t-tests and Fisher’s exact tests, compared baseline demographics, gait speed, and balance between fallers and non-fallers. For univariate analyses, Bonferroni correction was applied for multiple comparisons. Baseline variables with P<0.15 were included in a forward logistic regression model to identify factors predictive of falls with age as covariate. Sensitivity and specificity of each predictor of falls in the model were calculated. Significance level for the regression analysis was P<0.05. During follow-up, 59% of participants had one or more falls. Baseline demographics, health information, history of falls, gaits speed, and balance tests did not differ significantly between fallers and non-fallers. Forward logistic regression revealed that a history of falls was a significant predictor of falls in the final model (odds ratio =6.81; 95% confidence interval =1.594–29.074) (P<0.05). Sensitivity and specificity for correctly identifying a faller using the positive history of falls were 74% and 69%, respectively. Current findings suggested that for community-dwelling older cancer survivors with mixed diagnoses, asking about the history of falls may help detect individuals at risk of falling. PMID:26425079

EXpectation Propagation LOgistic REgRession (EXPLORER): Distributed Privacy-Preserving Online Model Learning

PubMed Central

Wang, Shuang; Jiang, Xiaoqian; Wu, Yuan; Cui, Lijuan; Cheng, Samuel; Ohno-Machado, Lucila

2013-01-01

We developed an EXpectation Propagation LOgistic REgRession (EXPLORER) model for distributed privacy-preserving online learning. The proposed framework provides a high level guarantee for protecting sensitive information, since the information exchanged between the server and the client is the encrypted posterior distribution of coefficients. Through experimental results, EXPLORER shows the same performance (e.g., discrimination, calibration, feature selection etc.) as the traditional frequentist Logistic Regression model, but provides more flexibility in model updating. That is, EXPLORER can be updated one point at a time rather than having to retrain the entire data set when new observations are recorded. The proposed EXPLORER supports asynchronized communication, which relieves the participants from coordinating with one another, and prevents service breakdown from the absence of participants or interrupted communications. PMID:23562651

Emerging Heterogeneities in Italian Customs and Comparison with Nearby Countries

PubMed Central

Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Javarone, Marco Alberto; Pizzoferrato, Andrea; Tantari, Daniele

2015-01-01

In this work we apply techniques and modus operandi typical of Statistical Mechanics to a large dataset about key social quantifiers and compare the resulting behaviors of five European nations, namely France, Germany, Italy, Spain and Switzerland. The social quantifiers considered are i. the evolution of the number of autochthonous marriages (i.e., between two natives) within a given territorial district and ii. the evolution of the number of mixed marriages (i.e., between a native and an immigrant) within a given territorial district. Our investigations are twofold. From a theoretical perspective, we develop novel techniques, complementary to classical methods (e.g., historical series and logistic regression), in order to detect possible collective features underlying the empirical behaviors; from an experimental perspective, we evidence a clear outline for the evolution of the social quantifiers considered. The comparison between experimental results and theoretical predictions is excellent and allows speculating that France, Italy and Spain display a certain degree of internal heterogeneity, that is not found in Germany and Switzerland; such heterogeneity, quite mild in France and in Spain, is not negligible in Italy and highlights quantitative differences in the habits of Northern and Southern regions. These findings may suggest the persistence of two culturally distinct communities, long-term lasting heritages of different and well-established customs. Also, we find qualitative differences between the evolution of autochthonous and of mixed marriages: for the former imitation in decisional mechanisms seems to play a key role (and this results in a square root relation between the number of autochthonous marriages versus the percentage of possible couples inside that country), while for the latter the emerging behavior can be recovered (in most cases) with elementary models with no interactions, suggesting weak imitation patterns between natives and migrants (and this translates in a linear growth for the number of mixed marriages versus the percentage of possible mixed couples in the country). However, the case of mixed marriages displays a more complex phenomenology, where further details (e.g., the provenance and the status of migrants, linguistic barriers, etc.) should also be accounted for. PMID:26713615

Emerging Heterogeneities in Italian Customs and Comparison with Nearby Countries.

PubMed

Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Javarone, Marco Alberto; Pizzoferrato, Andrea; Tantari, Daniele

2015-01-01

In this work we apply techniques and modus operandi typical of Statistical Mechanics to a large dataset about key social quantifiers and compare the resulting behaviors of five European nations, namely France, Germany, Italy, Spain and Switzerland. The social quantifiers considered are i. the evolution of the number of autochthonous marriages (i.e., between two natives) within a given territorial district and ii. the evolution of the number of mixed marriages (i.e., between a native and an immigrant) within a given territorial district. Our investigations are twofold. From a theoretical perspective, we develop novel techniques, complementary to classical methods (e.g., historical series and logistic regression), in order to detect possible collective features underlying the empirical behaviors; from an experimental perspective, we evidence a clear outline for the evolution of the social quantifiers considered. The comparison between experimental results and theoretical predictions is excellent and allows speculating that France, Italy and Spain display a certain degree of internal heterogeneity, that is not found in Germany and Switzerland; such heterogeneity, quite mild in France and in Spain, is not negligible in Italy and highlights quantitative differences in the habits of Northern and Southern regions. These findings may suggest the persistence of two culturally distinct communities, long-term lasting heritages of different and well-established customs. Also, we find qualitative differences between the evolution of autochthonous and of mixed marriages: for the former imitation in decisional mechanisms seems to play a key role (and this results in a square root relation between the number of autochthonous marriages versus the percentage of possible couples inside that country), while for the latter the emerging behavior can be recovered (in most cases) with elementary models with no interactions, suggesting weak imitation patterns between natives and migrants (and this translates in a linear growth for the number of mixed marriages versus the percentage of possible mixed couples in the country). However, the case of mixed marriages displays a more complex phenomenology, where further details (e.g., the provenance and the status of migrants, linguistic barriers, etc.) should also be accounted for.

Dental health between self-perception, clinical evaluation and body image dissatisfaction - a cross-sectional study in mixed dentition pre-pubertal children.

PubMed

Banu, Ancuta; Șerban, Costela; Pricop, Marius; Urechescu, Horatiu; Vlaicu, Brigitha

2018-05-03

Self-perception of oral health status is a multidimensional construct that includes psychological, psychosocial and functional aspects of oral health. Contemporary concepts suggest that the evaluation of health needs should focus on clinical standards and socio-dental indicators that measure the impact of health/disease on the individual quality of life. Oral health cannot be dissociated from general health. This study evaluates a possible association between oral health status, body size, self-perception of oral health, self-perception of body size and dissatisfaction with body image in prepubertal children with mixed dentition, targeting the completion of children's health status assessment which will further allow the identification of individuals at risk and could be further used as an evaluation of the need for specific interventions. The present study is cross-sectional in design and uses data from 710 pre-pubertal children with mixed dentition. The outcome variables comprised one item self-perception of oral health: dmft/DMFT Index and Dental Aesthetic Index, body size, self-assessed body size and desired body size. Multiple logistic regression analyses were performed. The level of significance was set at 5%. More than a half (53.1%) of the participants with mixed dentition reported that their oral health was excellent or very good. In the unadjusted model, untreated decayed teeth, dmft score and body dissatisfaction levels had a significant contribution to poor self-perception of oral health, but after adjustment for gender, BMI status, dmft score, DMFT score and DAI score, only untreated decayed teeth OR = 1.293, 95%CI (1.120-1.492) and higher body dissatisfaction levels had a significant contribution. It was concluded that the need for dental treatment influenced self-perception of oral health in prepubertal children with mixed dentition, especially with relation to untreated decayed teeth. Since only body dissatisfaction levels, but not BMI, were related to poor self-perception of oral health, which involves a psychological component, further studies should evaluate the risk factors of body dissatisfaction, in order to plan health care directed to this age group, and with the purpose to positive parenting strategies.

Case Study on Optimal Routing in Logistics Network by Priority-based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiaoguang; Lin, Lin; Gen, Mitsuo; Shiota, Mitsushige

Recently, research on logistics caught more and more attention. One of the important issues on logistics system is to find optimal delivery routes with the least cost for products delivery. Numerous models have been developed for that reason. However, due to the diversity and complexity of practical problem, the existing models are usually not very satisfying to find the solution efficiently and convinently. In this paper, we treat a real-world logistics case with a company named ABC Co. ltd., in Kitakyusyu Japan. Firstly, based on the natures of this conveyance routing problem, as an extension of transportation problem (TP) and fixed charge transportation problem (fcTP) we formulate the problem as a minimum cost flow (MCF) model. Due to the complexity of fcTP, we proposed a priority-based genetic algorithm (pGA) approach to find the most acceptable solution to this problem. In this pGA approach, a two-stage path decoding method is adopted to develop delivery paths from a chromosome. We also apply the pGA approach to this problem, and compare our results with the current logistics network situation, and calculate the improvement of logistics cost to help the management to make decisions. Finally, in order to check the effectiveness of the proposed method, the results acquired are compared with those come from the two methods/ software, such as LINDO and CPLEX.

Comparison of Logistic Regression and Artificial Neural Network in Low Back Pain Prediction: Second National Health Survey

PubMed Central

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

Background: The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Methods: Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. Results: The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Conclusions: Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant. PMID:23113198

Comparison of logistic regression and artificial neural network in low back pain prediction: second national health survey.

PubMed

Parsaeian, M; Mohammad, K; Mahmoudi, M; Zeraati, H

2012-01-01

The purpose of this investigation was to compare empirically predictive ability of an artificial neural network with a logistic regression in prediction of low back pain. Data from the second national health survey were considered in this investigation. This data includes the information of low back pain and its associated risk factors among Iranian people aged 15 years and older. Artificial neural network and logistic regression models were developed using a set of 17294 data and they were validated in a test set of 17295 data. Hosmer and Lemeshow recommendation for model selection was used in fitting the logistic regression. A three-layer perceptron with 9 inputs, 3 hidden and 1 output neurons was employed. The efficiency of two models was compared by receiver operating characteristic analysis, root mean square and -2 Loglikelihood criteria. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the logistic regression was 0.752 (0.004), 0.3832 and 14769.2, respectively. The area under the ROC curve (SE), root mean square and -2Loglikelihood of the artificial neural network was 0.754 (0.004), 0.3770 and 14757.6, respectively. Based on these three criteria, artificial neural network would give better performance than logistic regression. Although, the difference is statistically significant, it does not seem to be clinically significant.

Effect of folic acid on appetite in children: ordinal logistic and fuzzy logistic regressions.

PubMed

Namdari, Mahshid; Abadi, Alireza; Taheri, S Mahmoud; Rezaei, Mansour; Kalantari, Naser; Omidvar, Nasrin

2014-03-01

Reduced appetite and low food intake are often a concern in preschool children, since it can lead to malnutrition, a leading cause of impaired growth and mortality in childhood. It is occasionally considered that folic acid has a positive effect on appetite enhancement and consequently growth in children. The aim of this study was to assess the effect of folic acid on the appetite of preschool children 3 to 6 y old. The study sample included 127 children ages 3 to 6 who were randomly selected from 20 preschools in the city of Tehran in 2011. Since appetite was measured by linguistic terms, a fuzzy logistic regression was applied for modeling. The obtained results were compared with a statistical ordinal logistic model. After controlling for the potential confounders, in a statistical ordinal logistic model, serum folate showed a significantly positive effect on appetite. A small but positive effect of folate was detected by fuzzy logistic regression. Based on fuzzy regression, the risk for poor appetite in preschool children was related to the employment status of their mothers. In this study, a positive association was detected between the levels of serum folate and improved appetite. For further investigation, a randomized controlled, double-blind clinical trial could be helpful to address causality. Copyright © 2014 Elsevier Inc. All rights reserved.

Interplanetary Supply Chain Risk Management

NASA Technical Reports Server (NTRS)

Galluzzi, Michael C.

2018-01-01

Emphasis on KSC ground processing operations, reduced spares up-mass lift requirements and campaign-level flexible path perspective for space systems support as Regolith-based ISM is achieved by; Network modeling for sequencing space logistics and in-space logistics nodal positioning to include feedstock. Economic modeling to assess ISM 3D printing adaption and supply chain risk.

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…

Flower Power: Sunflowers as a Model for Logistic Growth

ERIC Educational Resources Information Center

Fernandez, Eileen; Geist, Kristi A.

2011-01-01

Logistic growth displays an interesting pattern: It starts fast, exhibiting the rapid growth characteristic of exponential models. As time passes, it slows in response to constraints such as limited resources or reallocation of energy. The growth continues to slow until it reaches a limit, called capacity. When the growth describes a population,…

Scheduling Algorithm for Mission Planning and Logistics Evaluation (SAMPLE). Volume 2: Mission payloads subsystem description

NASA Technical Reports Server (NTRS)

Dupnick, E.; Wiggins, D.

1980-01-01

The scheduling algorithm for mission planning and logistics evaluation (SAMPLE) is presented. Two major subsystems are included: The mission payloads program; and the set covering program. Formats and parameter definitions for the payload data set (payload model), feasible combination file, and traffic model are documented.

Automatic Generation of Customized, Model Based Information Systems for Operations Management.

DTIC Science & Technology

The paper discusses the need for developing a customized, model based system to support management decision making in the field of operations ... management . It provides a critique of the current approaches available, formulates a framework to classify logistics decisions, and suggests an approach for the automatic development of logistics systems. (Author)

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…

Semiparametric Item Response Functions in the Context of Guessing

ERIC Educational Resources Information Center

Falk, Carl F.; Cai, Li

2016-01-01

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood-based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

The Performance of the Linear Logistic Test Model When the Q-Matrix Is Misspecified: A Simulation Study

ERIC Educational Resources Information Center

MacDonald, George T.

2014-01-01

A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…

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.

Advanced colorectal neoplasia risk stratification by penalized logistic regression.

PubMed

Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

2016-08-01

Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming

PubMed Central

Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

2015-01-01

In order to recycle and dispose of all people’s expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies. PMID:26184252

An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming.

PubMed

Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

2015-07-09

In order to recycle and dispose of all people's expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies.

Country logistics performance and disaster impact.

PubMed

Vaillancourt, Alain; Haavisto, Ira

2016-04-01

The aim of this paper is to deepen the understanding of the relationship between country logistics performance and disaster impact. The relationship is analysed through correlation analysis and regression models for 117 countries for the years 2007 to 2012 with disaster impact variables from the International Disaster Database (EM-DAT) and logistics performance indicators from the World Bank. The results show a significant relationship between country logistics performance and disaster impact overall and for five out of six specific logistic performance indicators. These specific indicators were further used to explore the relationship between country logistic performance and disaster impact for three specific disaster types (epidemic, flood and storm). The findings enhance the understanding of the role of logistics in a humanitarian context with empirical evidence of the importance of country logistics performance in disaster response operations. © 2016 The Author(s). Disasters © Overseas Development Institute, 2016.

Analysis of Logistics in Support of a Human Lunar Outpost

NASA Technical Reports Server (NTRS)

Cirillo, William; Earle, Kevin; Goodliff, Kandyce; Reeves, j. D.; Andrashko, Mark; Merrill, R. Gabe; Stromgren, Chel

2008-01-01

Strategic level analysis of the integrated behavior of lunar transportation system and lunar surface system architecture options is performed to inform NASA Constellation Program senior management on the benefit, viability, affordability, and robustness of system design choices. This paper presents an overview of the approach used to perform the campaign (strategic) analysis, with an emphasis on the logistics modeling and the impacts of logistics resupply on campaign behavior. An overview of deterministic and probabilistic analysis approaches is provided, with a discussion of the importance of each approach to understanding the integrated system behavior. The logistics required to support lunar surface habitation are analyzed from both 'macro-logistics' and 'micro-logistics' perspectives, where macro-logistics focuses on the delivery of goods to a destination and micro-logistics focuses on local handling of re-supply goods at a destination. An example campaign is provided to tie the theories of campaign analysis to results generation capabilities.