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PubMed2003

On the performance of random-coefficient pattern-mixture models for non-ignorable drop-out.

Random-coefficient pattern-mixture models (RCPMMs) have been proposed for longitudinal data when drop-out is thought to be non-ignorable. An RCPMM is a random-effects model with summaries of drop-out time included among the regressors. The basis of every RCPMM is extrapolation. We review RCPMMs, describe various extrapolation strategies, and show how analyses may be simplified through multiple imputation. Using simulated and real data, we show that alternative RCPMMs that fit equally well may lead to very different estimates for parameters of interest. We also show that minor model misspecification can introduce biases that are quite large relative to standard errors, even in fairly small samples. For many scientific applications, where the form of the population model and nature of the drop-out are unknown, interval estimates from any single RCPMM may suffer from undercoverage because uncertainty about model specification is not taken into account.

Antipsychotic Agents↗
PubMed2005

Modeling the dynamic changes in concentrations of gamma-hexachlorocyclohexane (gamma-HCH) in Tianjin region from 1953 to 2020.

A level IV fugacity model was used to simulate the dynamic changes of gamma-hexachlorocyclohexane (gamma-HCH) concentrations in environmental media in Tianjin, China. A similar model (level III) was previously used and validated under steady state conditions; this paper explores its dynamic behavior. Application of the level IV fugacity model has been validated using independently observed gamma-HCH concentrations in various media during the early 1980s and during 2001. Sensitivity analysis was conducted using coefficient-of-variation normalized sensitivity coefficients. The model was also subject to uncertainty analysis using Monte Carlo simulation. It was found that concentrations of gamma-HCH reached within 95% of their steady-state levels in all media after less than 15 years. Around one order-of-magnitude decreases in gamma-HCH concentrations in various media occurred between 1993 and 2001. We project that gamma-HCH concentrations will decrease another 1.7-1.9 orders of magnitude to reach 1.1 (0.9-1.2) x 10(-14), 2.7 (2.5-3.0) x 10(-10), 1.2 (1.1-1.3) x 10(-7), and 6.1 (5.4-6.8) x 10(-8) mol/m(3), in air, water, soil, and sediment, respectively, by 2020. The sensitivities and true uncertainty of the model are discussed.

Air Pollutants↗
PubMedDate not supplied

Probabilistic analysis of decision trees using symbolic algebra.

Uncertainty in medical decision making techniques occurs in the specification of both decision tree probabilities and utilities. Using a computer-based algebraic approach, methods for modeling this uncertainty have been formulated. This analytic procedure allows an exact calculation of the statistical variance at the final decision node using automated symbolic manipulation. Confidence and conditional confidence levels for the preferred decision are derived from gaussian theory, and the mutual information index that identifies probabilistically important tree variables is provided. The computer-based algebraic method is illustrated for a problem previously analyzed by Monte Carlo simulation. This methodology provides the decision analyst with a procedure to evaluate the outcome of specification uncertainty, in many decision problems, without resorting to Monte Carlo analysis.

Adult↗
PubMed1998

Ligaments and articular contact guide passive knee flexion.

The aim of this study was to test the hypothesis that the coupled features of passive knee flexion are guided by articular contact and by the isometric fascicles of the ACL, PCL and MCL. A three-dimensional mathematical model of the knee was developed, in which the articular surfaces in the lateral and medial compartments and the isometric fascicles in the ACL, PCL and MCL were represented as five constraints in a one degree-of-freedom parallel spatial mechanism. Mechanism analysis techniques were used to predict the path of motion of the tibia relative to the femur. Using a set of anatomical parameters obtained from a cadaver specimen, the model predicts coupled internal rotation and ab/adduction with flexion. These predictions correspond well to measurements of the cadaver specimen's motion. The model also predicts posterior translation of contact on the tibia with flexion. Although this is a well-known feature of passive knee flexion, the model predicts more translation than has been reported from experiments in the literature. Modelling of uncertainty in the anatomical parameters demonstrated that the discrepancy between theoretical predictions and experimental measurement can be attributed to parameter sensitivity of the model. This study shows that the ligaments and articular surfaces work together to guide passive knee motion. A principal implication of the work is that both articular surface geometry and ligament geometry must be preserved or replicated by surgical reconstruction and replacement procedures to ensure normal knee kinematics and by extension, mechanics.

Anterior Cruciate Ligament↗
PubMed2001

Resource cost analysis of cervical spine trauma radiography.

PURPOSE: To determine the resource costs of the technical component of cervical spine radiography in patients with trauma and the factors that drive resource costs, to provide a model for resource cost estimation, and to compare resource costs with other methods of cost estimation. MATERIALS AND METHODS: Direct measurement was made of technologist labor and supply costs of a cohort of 409 consecutive patients with trauma who underwent cervical spine radiography. Probability of cervical spine injury was determined by reviewing emergency department medical records. An animated simulation model was used to combine cost and injury probability estimates to determine resource costs. Sensitivity analysis explored factors that determined costs and estimated uncertainty in model estimations. Comparison was made with other cost estimates. RESULTS: The average technical resource cost for cervical spine radiography was $49.60. Both direct labor ($19.60 vs $13.33; P <.005) and film ($8.39 vs $6.76; P <.005) costs were greater in patients with high probability of injury than in those with low probability of injury. Overall costs in patients with high probability of injury exceeded those in patients with low probability of injury by 33%. Resource costs exceeded Medicare resource-based relative value unit reimbursements for all patients with trauma. CONCLUSION: Resource costs of the technical components of cervical spine radiography varied with patient probability of injury and were higher than Medicare reimbursements.

Adolescent↗
PubMed1995

Decision-theoretic refinement planning: a new method for clinical decision analysis.

Clinical decision analysis seeks to identify the optimal management strategy by modelling the uncertainty and risks entailed in the diagnosis, natural history, and treatment of a particular problem or disorder. Decision trees are the most frequently used model in clinical decision analysis, but can be tedious to construct, cumbersome to use, and computationally prohibitive, especially with large, complex decision problems. We present a new method for clinical decision analysis that combines the techniques of decision theory and artificial intelligence. Our model uses a modular representation of knowledge that simplifies model building and enables more fully automated decision making. Moreover, the model exploits problem structures to yield better computational efficiency. As an example we apply our techniques to the problem of management of acute deep venous thrombosis.

Artificial Intelligence↗
PubMed2006

Modeling denitrification in terrestrial and aquatic ecosystems at regional scales.

Quantifying where, when, and how much denitrification occurs on the basis of measurements alone remains particularly vexing at virtually all spatial scales. As a result, models have become essential tools for integrating current understanding of the processes that control denitrification with measurements of rate-controlling properties so that the permanent losses of N within landscapes can be quantified at watershed and regional scales. In this paper, we describe commonly used approaches for modeling denitrification and N cycling processes in terrestrial and aquatic ecosystems based on selected examples from the literature. We highlight future needs for developing complementary measurements and models of denitrification. Most of the approaches described here do not explicitly simulate microbial dynamics, but make predictions by representing the environmental conditions where denitrification is expected to occur, based on conceptualizations of the N cycle and empirical data from field and laboratory investigations of the dominant process controls. Models of denitrification in terrestrial ecosystems include generally similar rate-controlling variables, but vary in their complexity of the descriptions of natural and human-related properties of the landscape, reflecting a range of scientific and management perspectives. Models of denitrification in aquatic ecosystems range in complexity from highly detailed mechanistic simulations of the N cycle to simpler source-transport models of aggregate N removal processes estimated with empirical functions, though all estimate aquatic N removal using first-order reaction rate or mass-transfer rate expressions. Both the terrestrial and aquatic modeling approaches considered here generally indicate that denitrification is an important and highly substantial component of the N cycle over large spatial scales. However, the uncertainties of model predictions are large. Future progress will be linked to advances in field measurements, spatial databases, and model structures.

Agriculture↗
PubMed2005

Modelling and experimental studies on the transfer of radionuclides to fruit.

Although fruit is an important component of the diet, the extent to which it contributes to radiological exposure remains unclear, partially as a consequence of uncertainties in models and data used to assess transfer of radionuclides in the food chain. A Fruits Working Group operated as part of the IAEA BIOMASS (BIOsphere Modelling and ASSessment) programme from 1997 to 2000, with the aim of improving the robustness of the models that are used for radiological assessment. The Group completed a number of modelling and experimental activities including: (i) a review of experimental, field and modelling information on the transfer of radionuclides to fruit; (ii) discussion of recently completed or ongoing experimental studies; (iii) development of a database on the transfer of radionuclides to fruit; (iv) development of a conceptual model for fruit and (v) two model intercomparison studies and a model validation study. The Group achieved significant advances in understanding the processes involved in transfer of radionuclides to fruit. The work demonstrated that further experimental and modelling studies are required to ensure that the current generation of models can be applied to a wide range of scenarios.

Fruit↗
PubMed2006

Fate of chemical warfare agents and toxic industrial chemicals in landfills.

One component of preparedness for a chemical attack is planning for the disposal of contaminated debris. To assess the feasibility of contaminated debris disposal in municipal solid waste (MSW) landfills, the fate of selected chemical warfare agents (CWAs) and toxic industrial chemicals (TICs) in MSW landfills was predicted with a mathematical model. Five blister agents [sulfur mustard (HD), nitrogen mustard (HN-2), lewisite (L), ethyldichloroarsine (ED), and phosgene oxime (CX)], eight nerve agents [tabun (GA), sarin (GB), soman (GD), GE, GF, VX, VG, and VM], one riot-control agent [CS], and two TICs [furan and carbon disulfide] were studied. The effects of both infiltration (climate) and contaminant biodegradability on fate predictions were assessed. Model results showed that hydrolysis and gas-phase advection were the principal fate pathways for CWAs and TICs, respectively. Apart from CX and the TICs, none of the investigated compounds was predicted to persist in a landfill for more than 5 years. Climate had little impact on CWA/TIC fate, and biodegradability was only important for compounds with long hydrolysis half-lives. Monte Carlo simulations were performed to assess the influence of uncertainty in model input parameters on CWA/TIC fate predictions. Correlation analyses showed that uncertainty in hydrolysis rate constants was the primary contributor to variance of CWA fate predictions, while uncertainty in the Henry's Law constant and landfill gas-production rate accounted for most of the variance of TIC fate predictions. CWA hydrolysates were more persistent than the parent CWAs, but limited information is available on abiotic or biotic transformation rates for these chemicals.

Biodegradation, Environmental↗
PubMed2003

Econometric estimation of country-specific hospital costs.

Information on the unit cost of inpatient and outpatient care is an essential element for costing, budgeting and economic-evaluation exercises. Many countries lack reliable estimates, however. WHO has recently undertaken an extensive effort to collect and collate data on the unit cost of hospitals and health centres from as many countries as possible; so far, data have been assembled from 49 countries, for various years during the period 1973-2000. The database covers a total of 2173 country-years of observations. Large gaps remain, however, particularly for developing countries. Although the long-term solution is that all countries perform their own costing studies, the question arises whether it is possible to predict unit costs for different countries in a standardized way for short-term use. The purpose of the work described in this paper, a modelling exercise, was to use the data collected across countries to predict unit costs in countries for which data are not yet available, with the appropriate uncertainty intervals.The model presented here forms part of a series of models used to estimate unit costs for the WHO-CHOICE project. The methods and the results of the model, however, may be used to predict a number of different types of country-specific unit costs, depending on the purpose of the exercise. They may be used, for instance, to estimate the costs per bed-day at different capacity levels; the "hotel" component of cost per bed-day; or unit costs net of particular components such as drugs.In addition to reporting estimates for selected countries, the paper shows that unit costs of hospitals vary within countries, sometimes by an order of magnitude. Basing cost-effectiveness studies or budgeting exercises on the results of a study of a single facility, or even a small group of facilities, is likely to be misleading.

Journal Article↗
PubMed1990

Sensitivity analysis applied to Coburn-Forster-Kane models of carboxyhemoglobin formation.

When mathematical model predictions disagree with the behavior of the physiological system modeled, blame is generally placed on the inadequacy of the model. It was shown using the Coburn-Forster-Kane (CFK) models of carboxyhemoglobin (COHb) formation as illustrations, that a sensitivity analysis of the model can provide estimates of the effects of data variability and inaccuracy on model predictions. Sensitivity functions were derived for each variable in the model, and families of them were plotted as functions of time with work level as a parameter. The sensitivity plots identify the variables which can contribute the most to disparities between model and system behavior and illustrate how the relative importance of the error in each variable changes with both time and work level. For example, with exposure to a constant concentration of carbon monoxide (CO) at a constant level of exercise, errors in blood volume determination, initial [COHb], and total hemoglobin concentration do not affect the calculated equilibrium value of blood [COHb]; neither inspired concentration of carbon monoxide nor endogenous production rate affect the rate at which equilibrium is achieved; and all other variables affect both the equilibrium value of blood [COHb] and the rate at which it is achieved. The sensitivity analysis provides a link between model output variability and input or data variability which can be used to assess the value of efforts to reduce data error and to estimate the overall uncertainty of model predictions.

Carbon Monoxide↗
PubMed2006

Air quality modeling in the South Coast Air Basin of California: what do the numbers really mean?

This study evaluates air quality model sensitivity to input and to model components. Simulations are performed using the California Institute of Technology (CIT) airshed model. Results show the impacts on ozone (O3) concentration in the South Coast Air Basin (SCAB) of California because of changes in: (1) input data, including meteorological conditions (temperature, UV radiation, mixing height, and wind speed), boundary conditions, and initial conditions (ICs); and (2) model components, including advection solver and chemical mechanism. O3 concentrations are strongly affected by meteorological conditions and, in particular, by temperature. ICs also affect O3 concentrations, especially in the first 2 days of simulation. On the other hand, boundary conditions do not significantly affect the absolute peak O3 concentration, although they do affect concentrations near the inflow boundaries. Moreover, predicted O3 concentrations are impacted considerably by the chemical mechanism. In addition, dispersion of pollutants is affected by the advection routine used to calculate its transport. Comparison among CIT, California Photochemical Grid Model (CALGRID), and Urban Airshed Model air quality models suggests that differences in O3 predictions are mainly caused by the different chemical mechanisms used. Additionally, advection solvers contribute to the differences observed among model predictions. Uncertainty in predicted peak O3 concentration suggests that air quality evaluation should not be based solely on this single value but also on trends predicted by air quality models using a number of chemical mechanisms and with an advection solver that is mass conservative.

Air Pollution↗
PubMed2000

Adaptive Optics Imaging of the CLASS Gravitational Lens System B1359+154 with the Canada-France-Hawaii Telescope.

We present adaptive optics imaging of the CLASS gravitational lens system B1359+154 obtained with the Canada-France-Hawaii Telescope (CFHT) in the infrared K band. The observations show at least three brightness peaks within the ring of lensed images, which we identify as emission from multiple lensing galaxies. The results confirm the suspected compound nature of the lens, as deduced from preliminary mass modeling. The detection of several additional nearby galaxies suggests that B1359+154 is lensed by the compact core of a small galaxy group. We attempted to produce an updated lens model based on the CFHT observations and new 5 GHz radio data obtained with the MERLIN array, but there are too few constraints to construct a realistic model at this time. The uncertainties inherent with modeling compound lenses make B1359+154 a challenging target for Hubble constant determination through the measurement of differential time delays. However, time delays will offer additional constraints to help pin down the mass model. This lens system therefore presents a unique opportunity to directly measure the mass distribution of a galaxy group at intermediate redshift.

Journal Article↗
PubMed2004

Estimating contaminant dose for intermittent dermal contact: model development, testing, and application.

Assessments of aggregate exposure to pesticides and other surface contamination in residential environments are often driven by assumptions about dermal contacts. Accurately predicting cumulative doses from realistic skin contact scenarios requires characterization of exposure scenarios, skin surface loading and unloading rates, and contaminant movement through the epidermis. In this article we (1) develop and test a finite-difference model of contaminant transport through the epidermis; (2) develop archetypal exposure scenarios based on behavioral data to estimate characteristic loading and unloading rates; and (3) quantify 24-hour accumulation below the epidermis by applying a Monte Carlo simulation of these archetypal exposure scenarios. The numerical model, called Transient Transport through the epiDERMis (TTDERM), allows us to account for variable exposure times and time between exposures, temporal and spatial variations in skin and compound properties, and uncertainty in model parameters. Using TTDERM we investigate the use of a macro-activity parameter (cumulative contact time) for predicting daily (24-hour) integrated uptake of pesticides during complex exposure scenarios. For characteristic child behaviors and hand loading and unloading rates, we find that a power law represents the relationship between cumulative contact time and cumulative mass transport through the skin. With almost no loss of reliability, this simple relationship can be used in place of the more complex micro-activity simulations that require activity data on one- to five-minute intervals. The methods developed in this study can be used to guide dermal exposure model refinements and exposure measurement study design.

Child↗
PubMed2006

Comparing experimental designs for benchmark dose calculations for continuous endpoints.

The BMD (benchmark dose) method that is used in risk assessment of chemical compounds was introduced by Crump (1984) and is based on dose-response modeling. To take uncertainty in the data and model fitting into account, the lower confidence bound of the BMD estimate (BMDL) is suggested to be used as a point of departure in health risk assessments. In this article, we study how to design optimum experiments for applying the BMD method for continuous data. We exemplify our approach by considering the class of Hill models. The main aim is to study whether an increased number of dose groups and at the same time a decreased number of animals in each dose group improves conditions for estimating the benchmark dose. Since Hill models are nonlinear, the optimum design depends on the values of the unknown parameters. That is why we consider Bayesian designs and assume that the parameter vector has a prior distribution. A natural design criterion is to minimize the expected variance of the BMD estimator. We present an example where we calculate the value of the design criterion for several designs and try to find out how the number of dose groups, the number of animals in the dose groups, and the choice of doses affects this value for different Hill curves. It follows from our calculations that to avoid the risk of unfavorable dose placements, it is good to use designs with more than four dose groups. We can also conclude that any additional information about the expected dose-response curve, e.g., information obtained from studies made in the past, should be taken into account when planning a study because it can improve the design.

Animals↗
PubMed2001

Cost analysis of a hospital-at-home initiative using discrete event simulation.

OBJECTIVES: To examine whether, from a National Health Service (NHS) and local authority social services' viewpoint, a hospital-at-home service was cost saving compared with conventional inpatient care. METHODS: The subjects of this part-retrospective and part-prospective cost analysis were 51 elderly medical and orthopaedic surgical patients assessed at Hillingdon Hospital, West London, as being suitable for hospital-at-home care. Thirty patients received hospital-at-home care, provided for up to 14 days, while 21 patients remained in hospital and received standard inpatient care. All direct costs to the NHS hospital, community health services' provider and social services' department during the initial episode of care and the three months after discharge were collected for each group of patients. Costs and clinical event data were entered in a discrete event simulation model which generated baseline results. Uncertainty surrounding the model's parameters was explored using sensitivity analysis. RESULTS: The baseline simulation performed with 1000 patients in each group showed the mean cost per patient for hospital-at-home care and three-month follow-up to be around three-fifths the mean cost per patient of inpatient care and follow-up. Most of the excess cost in the inpatient group was attributable to the initial period of hospitalisation. Under all assumptions used in the sensitivity analysis, the hospital-at-home service was less costly. CONCLUSIONS: For elderly patients assessed as needing no more than 14 days of hospital care, hospital-at-home care is cost saving to health and social care agencies when compared with conventional inpatient care.

Aged↗
PubMed1995

Regulatory ozone modeling: status, directions, and research needs.

The Clean Air Act Amendments (CAAA) of 1990 have established selected comprehensive, three-dimensional, Photochemical Air Quality Simulation Models (PAQSMs) as the required regulatory tools for analyzing the urban and regional problem of high ambient ozone levels across the United States. These models are currently applied to study and establish strategies for meeting the National Ambient Air Quality Standard (NAAQS) for ozone in nonattainment areas; State Implementation Plans (SIPs) resulting from these efforts must be submitted to the U.S. Environmental Protection Agency (U.S. EPA) in November 1994. The following presentation provides an overview and discussion of the regulatory ozone modeling process and its implications. First, the PAQSM-based ozone attainment demonstration process is summarized in the framework of the 1994 SIPs. Then, following a brief overview of the representation of physical and chemical processes in PAQSMs, the essential attributes of standard modeling systems currently in regulatory use are presented in a nonmathematical, self-contained format, intended to provide a basic understanding of both model capabilities and limitations. The types of air quality, emission, and meteorological data needed for applying and evaluating PAQSMs are discussed, as well as the sources, availability, and limitations of existing databases. The issue of evaluating a model's performance in order to accept it as a tool for policy making is discussed, and various methodologies for implementing this objective are summarized. Selected interim results from diagnostic analyses, which are performed as a component of the regulatory ozone modeling process for the Philadelphia-New Jersey region, are also presented to provide some specific examples related to the general issues discussed in this work. Finally, research needs related to a) the evaluation and refinement of regulatory ozone modeling, b) the characterization of uncertainty in photochemical modeling, and c) the improvement of the model-based ozone-attainment demonstration process are presented to identify future directions in this area.

Air Pollution↗