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Results for “sensitivity analysis”

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At least 19 recordsLinked to original sources
PubMed1983

Using microcomputers to teach sensitivity analysis to medical students.

Teaching sensitivity analysis can be hampered by the large computational burden required by successive recalculation of outcomes. We designed a package of programs for an Apple II Plus microcomputer that allows rapid recalculation of two "model" decision problems currently available in the literature (hernia surgery and pharyngitis). The package presents the baseline values of the models and the expected utilities for each decision. The user can alter one or more key model values and recalculate the utilities easily and repeatedly. The threshold points for a number of variables are automatically computed. The package is interactive and prompts the user for all required input. No knowledge of computer programming is required to use the package. Students who were familiar with the basic elements of decision analysis were introduced to the modeled problems by didactic tutorials and independent reading. They were then given a set of sensitivity analyses to perform using the computerized models as a tool. Students were able to complete the sensitivity analysis assignments without difficulty and discussion of model assumptions was stimulated. The package enhances the teaching of sensitivity analysis by reducing its computational burden and promoting understanding of its nature and value.

Computer-Assisted Instruction↗
PubMed1990

Sensitivity analysis of human oculomotor muscle model.

Sensitivity analysis is a procedure for examining the importance of model parameters with respect to the input or output of the model. Presented is a sensitivity analysis of a recently updated fourth order linear homeomorphic oculomotor model. Each muscle is modeled as a viscoelastic parallel combination connected to an active state tension generator, viscosity element and length tension element parallel combination. The eyeball is modeled as a sphere with a moment of inertia which is connected to two voight elements in series. The sensitivity analysis revealed the parameters of the model obtained from mathematical analysis are acceptable to be used as nominal parameters. Consequently, the analytical parameters can vary considerably while allowing the model to perform as empirical data predicts.

Elasticity↗
PubMedDate not supplied

The use of efficiency linear programs for sensitivity analysis in medical decision making.

Sensitivity analysis in most medical problems is a complex process involving repeated calculations that can be computationally cumbersome, and its results are only approximate. The authors present a linear program-based approach that reveals the optimum strategies in a decision problem when event probabilities are not known exactly but their value ranges are available. Its application in a clinical decision-making situation is demonstrated. The approach promises to provide a flexible, precise, and computationally efficient technique for sensitivity analysis in medical decision making.

Aged↗
PubMed1991

Sensitivity analysis for matched case-control studies.

A sensitivity analysis in an observational study indicates the degree to which conclusions would be altered by hidden biases of various magnitudes. A method of sensitivity analysis previously proposed for cohort studies is extended for use in matched case-control studies with multiple controls, where slightly different derivations and calculations are required. Also discussed is a sensitivity analysis for case-control studies that have two distinct types of controls, say hospital and neighborhood controls, where the two types may be affected by different biases. For illustration, the method is applied to five case-control studies, including a study of herniated lumbar disc in which there are three types of cases, and a study of breast cancer with two types of controls.

Biometry↗
PubMedDate not supplied

N-way sensitivity analysis: a verification and stability-assessment technique for completely subjective decision analysis trees.

The purpose of this paper is to describe the development of N-way sensitivity analysis, a modified version of traditional sensitivity analysis that was created for the purpose of verifying the stability of decisions made by a completely subjective decision-analytic tree. The technique was developed during research that addressed whether nurses make clinical decisions that coincide with those recommended by a decision-analytic model. Since all parameters of the model were derived from subjective assessment, traditional one-way or two-way sensitivity analysis was deemed inappropriate. Consequently, N-way sensitivity analysis was developed and used for the verification of the decision model's results.

Analysis of Variance↗
PubMed1986

Probabilistic sensitivity analysis methods for general decision models.

Probabilistic sensitivity analysis has previously been described for the special case of dichotomous decision trees. We now generalize these techniques for a wider range of decision problems. These methods of sensitivity analysis allow the analyst to evaluate the impact of the multivariate uncertainty in the data used in the decision model and to gain insight into the probabilistic contribution of each of the variables to the decision outcome. The techniques are illustrated using Monte Carlo simulation on a trichotomous decision tree. Application of these powerful tools permits the decision analyst to investigate the structure and limitations of more complex decision problems with inherent uncertainties in the data upon which the decisions are based. Probabilistic sensitivity measures can provide guidance into the allocation of resources to resolve uncertainty about critical components of medical decisions.

Decision Theory↗
PubMed1982

Sensitivity analysis of a model for the environmental movement of radionuclides.

Results are presented from a sensitivity analysis study of a model developed to represent the environmental movement of radionuclides. This model is designated the Environmental Transport Model. The study has three purposes: (1) to develop sensitivity analysis techniques applicable to the Environmental Transport Model, (2) to provide insight and experience with respect to the performance of a sensitivity analysis of this model and (3) to develop understanding of the overall operation of the model and the variables which influence this operation. Two variations of a hypothetical river receiving a radionuclide discharge containing 99Tc, 245Cm, 241Pu, 234U, 230Th and 226Ra are defined. Independent variables of the following types are introduced: variables which define physical properties of the river system (e.g. soil depth, river discharge and sediment resuspension) and variables which summarize radionuclide, the following dependent variables are investigated: (1) radionuclide concentration in soil, (2) dissolved radionuclide concentration in surface-water and (3) total radionuclide concentration in surface-water. The investigation employs sensitivity analysis techniques based on Latin hypercube sampling, rank transformations and stepwise regression. Among the important variables indicated in the analysis are distribution coefficients, river discharge and suspended sediment concentration.

Fresh Water↗
PubMed1982

Sensitivity analysis of biological models.

An inhomogenous linear model of the lung mechanics system was selected for the demonstration of one of the methods of sensitivity analysis. Given the values of state variables, the sensitivity of the model makes possible a safe adjustment of coefficients, without leading to large errors of solution with even a small deviation in adjustment. Any mathematical model only represents a picture of basic and substantial dynamic properties and relations of a real object. By means of sensitivity analysis it is possible to obtain a faithful description of the real object's behavior by computing the simplest model solution, with knowing at the same time, by sensitivity analysis, the range of errors introduced by simplifications and approximations.

Computers↗
PubMed1989

Sensitivity analysis for GMDH correction modeling of MKG signals.

The purpose of this paper is to propose application of sensitivity analysis to the GMDH modeling for the correction of distorted kinesiographic signals recorded for inter-lattice points in space, and to evaluate its correction accuracy to estimate coordinates of an inter-lattice point, i.e., an observation, distorted coordinates of a nominal lattice point which is most adjacent to a given inter-lattice point is searched. Variations, i. e., differences, between distorted coordinates of the observations and their concomitant nominals are calculated. Instead of substituting kinesiographic measurements of the nominal and its neighbouring eight lattice points, the sum of the observation and its corresponding variation is substituted into the GMDH model which has been employed for the correction of distorted measurements of the aforementioned lattice point. A stereotaxic device is developed to stimulate mandibular jaw movement and determine position of a magnet transducer of a mandibular kinesiograph (MKG). Nominals of 3-D coordinates of the inter-lattice points are determined by the stimulator together with simultaneous recording of distorted output signals from the MKG which correspond to the nominals. Distorted signals are corrected on the basis of the sensitivity-oriented correction modeling. A mean estimation error of 0.16 mm (s. d., 0.19 mm) is determined for 24 inter-lattice coordinates. Thus, the application of sensitivity analysis to the GMDH modeling is confirmed to be effective.

Humans↗
PubMed1984

Design sensitivity analysis: a new method for implant design and a comparison with parametric finite element analysis.

A unified theory of structural design sensitivity is proposed to be used in conjunction with the parametric design variation method traditionally used in finite element analyses applied to biomechanics problems. Bone cement strain energy density dependence on cement and stem modulii of elasticity as analyzed with the theory of structural design sensitivity analysis is compared parametrically varied finite element results. Two-dimensional, eight-noded isoparametric and interface finite elements with optimal stresses at Gauss points are employed. Design sensitivity for strain energy density compares well with perturbation of design and reanalysis by finite element techniques.

Hip Prosthesis↗
PubMed1995

A comparison of sensitivity analysis techniques.

Modeling the movement and consequence of radioactive pollutants is critical for environmental protection and control of nuclear facilities. Sensitivity analysis is an integral part of model development and involves analytical examination of input parameters to aid in model validation and provide guidance for future research. Sensitivities of 21 input parameters have been analyzed for a specific-activity tritium dose model using fourteen methods of parameter sensitivity analysis. This report demonstrates, for each sensitivity method, the required calculational effort, the sensitivity ranking of parameters, and the relative method performance. The sensitivity measures include the following: partial derivatives, variation of inputs by 1 standard deviation (SD) and by 20%, a sensitivity index, an importance index, a relative deviation of the output distribution, a relative deviation ratio, partial rank correlation coefficients, standardized regression coefficients, rank regression coefficients, the Smirnov test, the Cramer-von Mises test, the Mann-Whitney test, and the squared-ranks test.

Diet↗
PubMed1981

Sensitivity analysis and optimization for a head movement model.

A sixth order nonlinear model for horizontal head rotations in humans is analyzed using an extended parameter sensitivity analysis and a global optimization algorithm. The sensitivity analysis is used in both the direct sense, as a model fitting tool, and in the indirect sense, as a guide to experimental design. Resolution is defined in terms of the sensitivity table, and is used to interpret the sensitivity results. Using sensitivity analyses, the head and eye movement systems are compared and contrasted. Controller signal parameters are the most influential. Their variations and effects on head movement trajectories and accelerations are investigated, and the conclusions are compared with clinical neurological findings. The global optimization algorithm, in addition to automating the fitting of various types of data, is combined with time optimality theory to give theoretical time-optimal inputs to the model.

Computers↗
PubMed1985

Probabilistic sensitivity analysis using Monte Carlo simulation. A practical approach.

The data for medical decision analyses are often unreliable. Traditional sensitivity analysis--varying one or more probability or utility estimates from baseline values to see if the optimal strategy changes--is cumbersome if more than two values are allowed to vary concurrently. This paper describes a practical method for probabilistic sensitivity analysis, in which uncertainties in all values are considered simultaneously. The uncertainty in each probability and utility is assumed to possess a probability distribution. For ease of application we have used a parametric model that permits each distribution to be specified by two values: the baseline estimate and a bound (upper or lower) of the 95 percent confidence interval. Following multiple simulations of the decision tree in which each probability and utility is randomly assigned a value within its distribution, the following results are recorded: (a) the mean and standard deviation of the expected utility of each strategy; (b) the frequency with which each strategy is optimal; (c) the frequency with which each strategy "buys" or "costs" a specified amount of utility relative to the remaining strategies. As illustrated by an application to a previously published decision analysis, this technique is easy to use and can be a valuable addition to the armamentarium of the decision analyst.

Decision Making↗
PubMed1986

Sensitivity analysis of the influence of source-term and environmental parameters on the radiological risk of coal-fired plants.

A sensitivity analysis was undertaken to determine the influence of different source-term and environmental parameters on the radiological risks from a coal-fired plant (CFP). It was found that the release rate of radionuclides and the effective release height most significantly influence radiological risk. Site characteristics, such as rain scavenging coefficients and food acquirement habits, have a lesser influence, and some parameters, such as time delay before ingestion of contaminated food, have practically no influence on the radiological impact of a CFP. The contribution to radiation risks of different exposure modes (i.e. inhalation, ingestion and contact with ground surface) were also analyzed, as well as of specific radionuclides and human body organs. Results of the sensitivity analysis were interpreted in terms of the characteristics of the fuel, facilities and site of a CFP. It is concluded that by proper choice of coal, furnace, ash filtration and stack height, as well as by proper siting, the radiological impact of a CFP can be drastically reduced.

Coal↗
PubMed1994

Stochastic simulation and sensitivity analysis: estimating future demand for health resources in China.

A simulation model has been built to estimate the demand for hospital beds and doctors in China between 1990 and 2010. The model was used to compare deterministic sensitivity analysis and stochastic simulation in assessing inherent uncertainty in health projections. The stochastic simulation method uses information more efficiently, and produces a more reasonable average estimate and a more meaningful range of projections than deterministic sensitivity analysis. However, it may be preferable to combine the use of both approaches because they have different, complementary, advantages and disadvantages. The usefulness of 3 value estimates of input variables and the benefits of the triangular distribution for stochastic simulation should be emphasized in health projections.

China↗
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↗
PubMed1990

Sensitivity analysis of respiratory parameter uncertainties: impact of criterion function form and constraints.

A sensitivity analysis based on weighted least-squares regression is presented to evaluate alternative methods for fitting lumped-parameter models to respiratory impedance data. The goal is to maintain parameter accuracy simultaneously with practical experiment design. The analysis focuses on predicting parameter uncertainties using a linearized approximation for joint confidence regions. Applications are with four-element parallel and viscoelastic models for 0.125- to 4-Hz data and a six-element model with separate tissue and airway properties for input and transfer impedance data from 2-64 Hz. The criterion function form was evaluated by comparing parameter uncertainties when data are fit as magnitude and phase, dynamic resistance and compliance, or real and imaginary parts of input impedance. The proper choice of weighting can make all three criterion variables comparable. For the six-element model, parameter uncertainties were predicted when both input impedance and transfer impedance are acquired and fit simultaneously. A fit to both data sets from 4 to 64 Hz could reduce parameter estimate uncertainties considerably from those achievable by fitting either alone. For the four-element models, use of an independent, but noisy, measure of static compliance was assessed as a constraint on model parameters. This may allow acceptable parameter uncertainties for a minimum frequency of 0.275-0.375 Hz rather than 0.125 Hz. This reduces data acquisition requirements from a 16- to a 5.33- to 8-s breath holding period. These results are approximations, and the impact of using the linearized approximation for the confidence regions is discussed.

Airway Resistance↗
PubMed1976

Parametric sensitivity analysis of a homeomorphic model for saccadic and vergence eye movements.

A non-linear sixth order homeomorphic model, fitted with parameters based on eye movements and physiological data, was tuned so that it provided good simulations for the shapes of the magnitude, velocity and acceleration trajectories. Excellent quantitative agreement was obtained in terms of the Main Sequence diagrams for human eye movements. Parametric sensitivity analysis was done for a saccade of ten degree amplitude, a physiologically normal magnitude at which experimental data is both abundant and relatively noise free. Among the many useful results of this sensitivity analysis are that pulse width (PW) and pulse height (PH) were confirmed as the two controlling parameters for the human eye movement model. Output behavior was relatively insensitive to variations of the passive elements of the plant. This analysis also pointed out that more physiological data are needed to understand the role of the non-linear force-velocity relationship of the extraocular muscles.

Computers↗