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Separate Models (separate + models)
Selected AbstractsSCHIP's Impact on Dependent Coverage in the Small-Group Health Insurance MarketHEALTH SERVICES RESEARCH, Issue 1 2010Eric E. Seiber Objective. To estimate the impact of State Children's Health Insurance Program (SCHIP) expansions on public and private coverage of dependents at small firms compared with large firms. Data Sources. 1996,2007 Annual Demographic Survey of the Current Population Survey (CPS). Study Design. This study estimates a two-stage least squares (2SLS) model for four insurance outcomes that instruments for SCHIP and Medicaid eligibility. Separate models are estimated for small group markets (firms with fewer than 25 employees), small businesses (firms under 500 employees), and large firms (firms 500 employees and above). Data Collection/Extraction Methods. We extracted data from the 1996,2007 CPS for children in households with at least one worker. Principal Findings. The SCHIP expansions decreased the percentage of uninsured dependents in the small group market by 7.6 percentage points with negligible crowd-out in the small group and no significant effect on private coverage across the 11-year-period. Conclusions. The SCHIP expansions have increased coverage for households in the small group market with no significant crowd-out of private coverage. In contrast, the estimates for large firms are consistent with the substantial crowd-out observed in the literature. [source] The Challenge of Predicting Demand for Emergency Department ServicesACADEMIC EMERGENCY MEDICINE, Issue 4 2008Melissa L. McCarthy MS Abstract Objectives:, The objective was to develop methodology for predicting demand for emergency department (ED) services by characterizing ED arrivals. Methods:, One year of ED arrival data from an academic ED were merged with local climate data. ED arrival patterns were described; Poisson regression was selected to represent the count of hourly ED arrivals as a function of temporal, climatic, and patient factors. The authors evaluated the appropriateness of prediction models by whether the data met key Poisson assumptions, including variance proportional to the mean, positive skewness, and absence of autocorrelation among hours. Model accuracy was assessed by comparing predicted and observed histograms of arrival counts and by how frequently the observed hourly count fell within the 50 and 90% prediction intervals. Results:, Hourly ED arrivals were obtained for 8,760 study hours. Separate models were fit for high- versus low-acuity patients because of significant arrival pattern differences. The variance was approximately equal to the mean in the high- and low-acuity models. There was no residual autocorrelation (r = 0) present after controlling for temporal, climatic, and patient factors that influenced the arrival rate. The observed hourly count fell within the 50 and 90% prediction intervals 50 and 90% of the time, respectively. The observed histogram of arrival counts was nearly identical to the histogram predicted by a Poisson process. Conclusions:, At this facility, demand for ED services was well approximated by a Poisson regression model. The expected arrival rate is characterized by a small number of factors and does not depend on recent numbers of arrivals. [source] Simulation of two-phase flow with sub-scale droplet and bubble effectsCOMPUTER GRAPHICS FORUM, Issue 2 2009Viorel Mihalef Abstract We present a new Eulerian-Lagrangian method for physics-based simulation of fluid flow, which includes automatic generation of sub-scale spray and bubbles. The Marker Level Set method is used to provide a simple geometric criterion for free marker generation. A filtering method, inspired from Weber number thresholding, further controls the free marker generation (in a physics-based manner). Two separate models are used, one for sub-scale droplets, the other for sub-scale bubbles. Droplets are evolved in a Newtonian manner, using a density-extension drag force field, while bubbles are evolved using a model based on Stokes' Law. We show that our model for sub-scale droplet and bubble dynamics is simple to couple with a full (macro-scale) Navier-Stokes two-phase flow model and is quite powerful in its applications. Our animations include coarse grained multiphase features interacting with fine scale multiphase features. [source] Cannabis and crime: findings from a longitudinal studyADDICTION, Issue 1 2010Willy Pedersen ABSTRACT Aim To examine the association between cannabis use during adolescence and young adulthood, and subsequent criminal charges. Methods Data were obtained from the Young in Norway Longitudinal Study. A population-based sample (n = 1353) was followed from 13 to 27 years of age. Data were gathered on cannabis use, alcohol consumption and alcohol problems, and use of other illegal substances such as amphetamines, cocaine and opiates. In addition, extensive information on socio-demographic, family and personal factors was collected. This data set was linked to individual-level information from official Norwegian crime statistics. Findings We found robust associations between cannabis use and later registered criminal charges, both in adolescence and in young adulthood. These associations were adjusted for a range of confounding factors, such as family socio-economic background, parental support and monitoring, educational achievement and career, previous criminal charges, conduct problems and history of cohabitation and marriage. In separate models, we controlled for alcohol measures and for use of other illegal substances. After adjustment, we still found strong associations between cannabis use and later criminal charges. However, when eliminating all types of drug-specific charges from our models, we no longer observed any significant association with cannabis use. Conclusions The study suggests that cannabis use in adolescence and early adulthood may be associated with subsequent involvement in criminal activity. However, the bulk of this involvement seems to be related to various types of drug-specific crime. Thus, the association seems to rest on the fact that use, possession and distribution of drugs such as cannabis is illegal. The study strengthens concerns about the laws relating to the use, possession and distribution of cannabis. [source] Impact of Alternative Interventions on Changes in Generic Dispensing RatesHEALTH SERVICES RESEARCH, Issue 5 2006A. James O'Malley Objectives. To evaluate the effectiveness of four alternative interventions (member mailings, advertising campaigns, free generic drug samples to physicians, and physician financial incentives) used by a major health insurer to encourage its members to switch to generic drugs. Methods. Using claim-level data from Blue Cross Blue Shield of Michigan, we evaluated the success of four interventions implemented during 2000,2003 designed to increase the use of generic drugs among its members. Around 13 million claims involving seven important classes of drugs were used to assess the effectiveness of the interventions. For each intervention a control group was developed that most closely resembled the corresponding intervention group. Logistic regression models with interaction effects between the treatment group (intervention versus control) and the status of the intervention (active versus not active) were used to evaluate if the interventions had an effect on the generic dispensing rate (GDR). Because the mail order pharmacy was considered more aggressive at converting prescriptions to generics, separate generic purchasing models were fitted to retail and mail order claims. In secondary analyses separate models were also fitted to claims involving a new condition and claims refilled for preexisting conditions. Results. The interventions did not appear to increase the market penetration of generic drugs for either retail or mail order claims, or for claims involving new or preexisting conditions. In addition, we found that the ratio of copayments for brand name to generic drugs had a large positive effect on the GDR. Conclusions. The interventions did not appear to directly influence the GDR. Financial incentives expressed to consumers through benefit designs have a large influence on their switching to generic drugs and on the less-costly mail-order mode of purchase. [source] Statistical downscaling relationships for precipitation in the Netherlands and North GermanyINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2002Björn-R. Abstract The statistical linkage of daily precipitation to the National Centers for Environment Prediction (NCEP) reanalysis data is described for De Bilt and Maastricht (Netherlands), and for Hamburg, Hanover and Berlin (Germany), using daily data for the period 1968,97. Two separate models were used to describe the daily precipitation at a particular site: an additive logistic model for rainfall occurrence and a generalized additive model for wet-day rainfall. Several dynamical variables and atmospheric moisture were included as predictor variables. The relative humidity at 700 hPa was considered as the moisture variable for rainfall occurrence modelling. For rainfall amount modelling, two options were compared: (i) the use of the specific humidity at 700 hPa, and (ii) the use of both the relative humidity at 700 hPa and precipitable water. An application is given with data from a time-dependent greenhouse gas forcing experiment using the coupled ECHAM4/OPYC3 atmosphere,ocean general circulation model for the periods 1968,97 and 2070,99. The fitted statistical relationships were used to estimate the changes in the mean number of wet days and the mean rainfall amounts for the winter and summer halves of the year at De Bilt, Hanover and Berlin. A decrease in the mean number of wet days was found. Despite this decrease, an increase in the mean seasonal rainfall amounts is predicted if specific humidity is used in the model for wet-day rainfall. This is caused by the larger atmospheric water content in the future climate. The effect of the increased atmospheric moisture is smaller if the alternative wet-day rainfall amount model with precipitable water and relative humidity is applied. Except for an anomalous change in mean winter rainfall at Hanover, the estimated changes from the latter model correspond quite well with those from the ECHAM4/OPYC3 model. Despite the flexibility of generalized additive models, the rainfall amount model systematically overpredicts the mean rainfall amounts in situations where extreme rainfall could be expected. Interaction between predictor effects has to be incorporated to reduce this bias. Copyright © 2002 Royal Meteorological Society [source] Landmines and Local Community AdaptationJOURNAL OF CONTINGENCIES AND CRISIS MANAGEMENT, Issue 2 2002Aldo A. Benini Despite international mobilization for greater humanitarian mine action and despite considerable clearance achievements, the majority of mine-affected communities have not yet been involved in formal clearance activities. They adapt to the contamination largely by local means. The differing degree to which local adaptation is successful is now better understood as a result of the Global Landmine Survey, a multi-country survey project launched in the wake of the 1997 Ottawa treaty to ban anti-personnel mines. Socio-economic impact surveys have since been completed in several countries. In addition to landmines, the Global Landmine Survey records impacts also from unexploded ordnance (UXO). The ability to avoid mine incidents is used to measure adaptation success. We use a variant of Poisson regression models in order to identify community and contamination correlates of the number of recent landmine victims. We estimate separate models using data from the Yemen, Chad and Thailand surveys. We interpret them in a common framework that includes variables from three domains: Pressure on resources, intensity of past conflict and communities' institutional endowments. Statistically significant associations occur in all three domains and in all the three countries studied. Physical correlates are the most strongly associated, pointing to a lasting deadly legacy of violent conflict, but also significant learning effects over time are present. Despite different measurements of institutional endowments, in each country one factor signifying greater local development is correlated with reductions in victims, whereas factors commonly associated with the presence of government officials do not contribute to local capacity to diminish the landmine problem. Strong spatial effects are manifest in clusters of communities with recent victims. Two policy consequences emerge. Firstly, given humanitarian funding limits, trade-offs between clearing contaminated land and creating alternative employment away from that land need to be studied more deeply; the Global Landmine Survey will need to reach out to other bodies of knowledge in development. Secondly, communities with similar contamination types and levels often form local clusters that are smaller than the administrative districts of the government and encourage tailored planning approaches for mine action. These call for novel coalitions that bring advocacy and grassroots NGOs together with local governments, agricultural and forestry departments and professional mine clearance and awareness education agencies. [source] AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 6 2004Ashu Jain ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set. [source] A model to predict survival at one month, one year, and five years after liver transplantation based on pretransplant clinical characteristicsLIVER TRANSPLANTATION, Issue 5 2003Paul J. Thuluvath MD Reliable models that could predict outcome of liver transplantation (LT) may guide physicians to advise their patients of immediate and late survival chances and may help them to optimize organ use. The objective of this study was to develop user-friendly models to predict short and long-term mortality after LT in adults based on pre-LT recipient characteristics. The United Network for Organ Sharing (UNOS) transplant registry (n = 38,876) from 1987 to 2001 was used to develop and validate the model. Two thirds of patients were randomized to develop the model (the modeling group), and the remaining third was randomized to cross-validate (the cross-validation group) it. Three separate models, using multivariate logistic regression analysis, were created and validated to predict survival at 1 month, 1 year, and 5 years. Using the total severity scores of patients in the modeling group, a predictive model then was created, and the predicted probability of death as a function of total score then was compared in the cross-validation group. The independent variables that were found to be very significant for 1 month and 1 year survival were age, body mass index (BMI), UNOS status 1, etiology, serum bilirubin (for 1 month and 1 year only), creatinine, and race (only for 5 years). The actual deaths in the cross-validation group followed very closely the predicted survival graph. The chi-squared goodness-of-fit test confirmed that the model could predict mortality reliably at 1 month, 1 year, and 5 years. We have developed and validated user-friendly models that could reliably predict short-term and long-term survival after LT. [source] A model to design recreational boat mooring fieldsNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 2 2009Ronald E. Giachetti Abstract This article develops a mathematical model and heuristic algorithm to design recreational boating mooring fields. The boating industry is important to the Florida economy, and boat storage is becoming a concern among those in the industry. The mooring field design problem is formulated to maximize the total number of boat feet moored in the mooring field. In the model, we allow two adjacent moorings to overlap, which introduces a risk that under certain conditions the boats on these moorings could contact each other. We identify the conditions when contact is possible and quantify the probability of contact. The mooring field design problem is formulated as a nonlinear mixed-integer programming problem. To solve the problem, we decompose it into two separate models, a mooring radii assignment model and a mooring layout model, which are solved sequentially. The first is solved via exhaustive enumeration and the second via a depth-first search algorithm. Two actual mooring fields are evaluated, and in both cases our model leads to better layouts than ones experts developed manually. The mooring field design model rationalizes the mooring field design and shows that in one case by increasing the risk from 0 to 1%, the mooring efficiency increases from 74.8% to 96.2%. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009 [source] Prepayment Behavior of Dutch Mortgagors: An Empirical AnalysisREAL ESTATE ECONOMICS, Issue 2 2003Erwin Charlier The suboptimal exercise of the prepayment option in a mortgage is relevant for mortgage pricing and the management of a mortgage portfolio. Construction of an accurate prepayment model requires quantification of driving factors such as seasoning, seasonality, refinance incentive and burnout. We focus on Dutch mortgages but also discuss the Dutch market in a European setting. Within the euro-denominated MBS market, the Dutch market is often referred to as the benchmark market. In our application we include typical Dutch market and contract characteristics such as the annual penalty-free prepayment of 10 to 20% of the original loan amount. We use loan-level historical data on mortgages originated between January 1989 and June 1999 to estimate separate models for two popular redemption types: savings mortgages and interest-only mortgages. In both models we allow for suboptimal prepayment behavior. The results clearly indicate that prepayment rates depend on interest rates and the age of the mortgage contract. Moreover, we find that burnout is an important element in describing the prepayment behavior of Dutch mortgagors. [source] Kinetic Reaction Models for the Selective Reduction of NO by Methane over Multifunctional Zeolite-based Redox CatalystsCHEMICAL ENGINEERING & TECHNOLOGY (CET), Issue 12 2004T. Sowade Abstract Kinetic measurements of the selective catalytic reduction (SCR) of NO by methane were performed over CeO2/H-ZSM-5, In-ZSM-5, and CeO2/In-ZSM-5 catalysts. The parameter space covered NO, CH4, and O2 concentrations varying from 250 to 1000 ppm, from 500 to 2000 ppm, and from 0.5 to 10,vol.-%, respectively, space velocities between 5000 and 90000 h,1 and temperatures between 573 and 873 K depending on the catalyst activities. With CeO2/In-ZSM-5 an additional series of measurements was performed with moistened feed gas (0.5,10,vol.-% H2O). On the basis of a pseudo-homogeneous, one-dimensional fixed-bed reactor model, the data were fitted to a kinetic model that includes power rate laws for the reduction of NO and for the unselective total oxidation of methane. From analyses of isothermal data sets, almost all reaction orders were found to vary significantly with changing temperature, which indicates that the simple kinetic model cannot reflect the complex reaction mechanism correctly. Nevertheless, the data measured with In-ZSM-5 could be modeled with good accuracy over a wide range of reaction temperatures (150 K) while the accuracy was less satisfactory with the remaining data sets, in particular for data with the moist feed over CeO2/In-ZSM-5. With the latter catalyst it was not possible to represent the data measured in dry and in moist feed in a single model even upon confinement to fixed reaction temperatures. A comparison of the separate models established showed strong changes in the reaction orders in the presence of water, which occur apparently already at a very low water content (,,0.5,vol.-%). The kinetic parameters found are in agreement with earlier conclusions about the reaction mechanisms. With In-ZSM-5, both reaction orders and the activation energy show a rate-limiting influence of NO oxidation on the NO reduction path which is removed by the presence of the CeO2 promoter. A difference in the reaction mechanism over CeO2/In-ZSM-5 and CeO2/H-ZSM-5 is reflected in different kinetic parameters. The differences of the kinetic parameters between dry-feed and moist-feed models for CeO2/In-ZSM-5 reflect adsorption competition between the reactants and water. [source] | |||||||||||||