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At least 19 recordsLinked to original sources

PubMed1991

A simulation model of AIDS in San Francisco: I. Model formulation and parameter estimation.

A model is formulated for the spread of the human immunodeficiency virus (HIV) and the subsequent development of acquired immunodeficiency syndrome (AIDS) in the population of homosexual men in San Francisco. The dynamic simulation model includes sexually very active and active subpopulations, migration, and a staged progression of HIV-infected persons to AIDS and death. Numerous data sources are used to estimate parameter values in the model. In a companion paper, simulations using the model and parameter estimates are found that are consistent with HIV and AIDS incidence data.

Acquired Immunodeficiency Syndrome↗

PubMed1992

Methods of segregation analysis for animal breeding data: parameter estimates.

Three approximations to the combined model likelihood (including variation due to both polygenes and a major gene) used in segregation analysis were compared in their ability to estimate the parameters describing the model. Paternal half-sib data simulated under four different combined models were used. In general, when a combined model provides the best explanation of the data the parameter estimates from all three approximations investigated are, on average, in good agreement with the values simulated. The use of Hermite integration to replace the integration in the combined model likelihood provided the parameter estimates closest to those stimulated. The other two approximations, based on extensions of linear mixed-model theory, gave estimates further from the expected values, however, these latter two methods can estimate transmitting abilities for the sires directly from the analyses. The three approximations are similar in their ability to genotype sires at the major locus. On average, with the models studied here, about 65 per cent of sires can be successfully genotyped.

Alleles↗

PubMed1991

Identification of insulin receptor systems: assessing the impact of model selection and measurement error on precision of parameter estimates using Monte Carlo study.

An extensive Monte Carlo study has been carried out in order to study the effect of measurement error on the precision of parameter estimates of an insulin binding system. Hypothetical radioimmunoassay experiments were generated for insulin binding to erythrocytes. The design of experiments followed strictly the protocol of real experiments. Randomly generated error was added to the synthetic data. The standard technique, a weighted non-linear regression analysis, was employed to re-estimate parameters of a model of two receptor sites and a model of negative co-operativity. As the original parameter values were known, the differences between original and estimated values was studied for (a) measurement error in the range from 0-17%, (b) random initial estimates and (c) error-free non-specific binding. In addition, analytical estimates of parameter precision were compared with the true between-experiment variation of parameter estimates. At the measurement error of 12%, a one site model is recommended to estimate the high affinity population of the two sites model. Plausible results can be expected in 90% of experiments, the between-experiment variation being approximately 30%. The model of two receptor sites gives approximately two thirds of plausible results. The high affinity population can be estimated with the between-experiment variation of 40%, the low affinity population is virtually unidentifiable with the between-experiment variation of approximately 100% and parameter estimates biased to higher values. Only half of the results obtained from the model of negative co-operativity are plausible, the variation in parameter estimates ranges from 90-150% and estimates are biased to higher values. At the level of 12% measurement error, random initial estimates do not significantly affect the estimation process, provided initial estimates are selected from a feasible range. At the same measurement error, the error-free non-specific binding does not improve the results, indicating that the mean of six replicates may be taken as a reliable estimate of non-specific binding. The analytical estimates of the coefficient of variation systematically underestimates the true between-experiments coefficient of variation, the difference has been found to be about 50%.

Erythrocytes↗

PubMed1992

Bayesian parameter estimation and population pharmacokinetics.

The widespread application of Bayesian parameter estimation in the area of therapeutic drug monitoring (TDM) has prompted the need for well conducted population studies to obtain relevant prior pharmacokinetic parameter estimates. In many cases the population has consisted of a relatively small number of subjects. This may be unavoidable for drugs used in cancer chemotherapy or in small, specific populations of patients. In contrast, information about drugs which are used extensively, such as the aminoglycosides, can be obtained by population studies which involve a large number of individuals. Indeed, this technique has proved particularly useful for determining parameter estimates which can be employed in neonatal TDM. Bayesian parameter estimation has been most frequently used for drugs with narrow therapeutic ranges such as the aminoglycosides, cyclosporin, digoxin, anticonvulsants (especially phenytoin), lithium and theophylline. However, the technique has now been extended to cytotoxic drugs, Factor VIII and warfarin. Bayesian methods have also been used to limit the number of samples required in more conventional pharmacokinetic studies with new drugs. Further advances in the use of these methods are likely to include measures of drug response and toxicity requiring population studies which also include relevant pharmacodynamic information.

Bayes Theorem↗

PubMed1979

Kinetic parameter estimation by numerical algorithms and multiple linear regression: application to pharmacokinetics.

Two numerical examples are presented to illustrate the application of the proposed method of parameter estimation in pharmacokinetics. Results for a system exemplifying first-order kinetics indicate that parameters estimated by the proposed procedure compare favorably with those estimated by a nonlinear regression method. In a simulated example characterized by Michaelis-Menten elimination kinetics, the accuracy of the estimated parameters was comparable to that expected, verifying the validity of the method. The importance of the numerical approximation algorithms was demonstrated also.

Kinetics↗

PubMed1991

Population parameter estimates for performance and reproductive traits in Polish Large White nucleus herds.

Performance test records from on-farm tests of young Polish Large White boars and reproductive records of Polish Large White sows from 94 nucleus farms during 1978 to 1987 were used to estimate population parameters for the measured traits. The number of boar performance records after editing was 114,347 from 3,932 sires, 21,543 dams, 44,493 litters and 1,075 herd-year-seasons. Reproductive performance records of sows involved 41,080 litters from 2,348 sires, 18,683 dams and 1,520 herd-year-seasons. Both data sets were analyzed by using restricted maximum-likelihood programs. The model used for the performance records included fixed herd-year-seasons, random sires, dams and error effects, and covariances for the year of birth of sire and year of birth of dam. The model used for the reproduction data set was the same as the performance data with parity as an additional fixed effect. Estimated heritabilities were .27, .29, .26, .07, .06, .06 for average daily gain standardized to 180 d (ADG), backfat thickness standardized to 110 kg BW (BF), days to 110 kg (DAYS), litter size at birth born alive (NBA), litter size at 21 d (N21) and litter weight at 21 d (W21), respectively. Estimated common environmental effects for the same traits were .09, .10, .09, .06, .07 and .08, respectively. Genetic correlations were .25 (ADG and BF), -.99 (ADG and DAYS), -.21 (BF and DAYS), .91 (NBA and N21), .68 (NBA and W21) and .80 (N21 and W21). The respective phenotypic correlations were .23, -.99, -.20, .88, .75, .86. These population parameters for Polish Large White pigs are similar to those for breeds in other countries.

Animals↗

PubMed1991

Serial lung model for simulation and parameter estimation in body plethysmography.

A serial lung model with a compressible segment has been implemented to simulate different types of lung and airway disorders such as asthma, emphysema, fibrosis and upper airway obstruction. The model described can be used during normal breathing, and moreover the compliant segment is structured according to more recent physiological data. A parameter estimation technique was applied and its reliability and uniqueness were tested by means of sine wave input signals. The characteristics of the alveolar pressure/flow patterns simulated with the model agree to a great extent with those found in the literature. In the case of absence of noise the parameter estimation routine produced unique solutions for different simulated pathologic classes. The sensitivity of the different parameters depended on the values belonging to each class of pathology. Some more simplified models are presented and their advantages over the complex model in special types of pathology are demonstrated. Noise added to the simulated flow appeared to have no influence on the estimated parameters, in contradiction to the effects with noise added to the pressure signal. In that case effective resistance was accurately estimated. Where parameters had no influence, as for instance upper airway resistance in emphysema or peripheral airway resistance in upper airway obstruction, the measurement accuracy was less. In all other cases, a satisfactory accuracy could be obtained.

Humans↗

PubMed1991

The effects of measurement errors in the plasma radioactivity curve on parameter estimation in positron emission tomography.

The effects of three error sources in plasma curve measurements on parameter estimation in kinetic analysis of positron emission tomography (PET) fluorodeoxyglucose (FDG) data are investigated by computer simulation. The three error sources are: (1) measurement noise in the radioactivity concentrations of plasma samples; (2) linear interpolation between adjacent plasma sampling points of the plasma time activity curve; and (3) incorrect weights used for the least-squares regression. All three error sources are found to increase the variability of the parameter estimates, with the first one a primary error source in normal PET FDG studies. The performance of five estimation methods which account for the error sources are evaluated. When the noise variances of the plasma and the tissue measurements are not known, an iterative weighting procedure is shown to give accurate and reliable estimates.

Computer Simulation↗

PubMed1992

Effects of violating local independence on IRT parameter estimation for the Binomial Trials Model.

The appropriateness of the Binomial Trials Model for test data that consist of multiple attempts of the same item needs to be determined because the presence of learning or fatigue effects may violate the model's assumption of local independence. The purpose of this study was to determine what effect the severity of the violation of local independence (VLI), coupled with different sample size (SS), test length (TL), and test difficulty (TD) had on the estimation of the model difficulty parameter, b, using computer simulation techniques. Each of the following conditions was replicated 100 times under a completely crossed design: SS (100, 200, 500, 2,000); TL (5, 10, 20, 25 attempts); TD (-1.2, 0.0, 1.2); and VLI (from no violation to complete violation). Examinee ability or latent trait was pseudorandomly drawn from a standard normal distribution, and the b-parameter was estimated using a maximum likelihood procedure on generated test scores. Regardless of SS, TL, and TD, the b-parameter tended to be overestimated for situations in which the VLI condition simulated fatigue and underestimated when the VLI condition simulated late-test learning or practice effect. The findings suggest that violations of local independence, at least as simulated in this study, could seriously bias the difficulty parameter estimates if all examinees tested exhibited the dependency.

Bias↗

PubMed1991

Genetic and environmental growth trait parameter estimates for Brahman and Brahman-derivative cattle.

Beefmaster, Brahman, Brangus, and Santa Gertrudis field data records were used to determine genetic and environmental parameter estimates using a multiple-trait, pseudo-expectation approach. Adjusted birth weight, 205-d weight, and postweaning gain records were analyzed for each breed. Also, Brangus weaning sheath and navel scores were both analyzed using a single-trait, pseudo-expectation method to determine genetic parameter estimates. Additive birth weight heritability (h2A) estimates ranged from .22 to .37 and maternal birth weight heritability (h2M) estimates ranged from .12 to .55. Estimates for 205-d weight h2A for the four breeds varied from .21 to .25, and 205-d weight h2M estimates ranged from .15 to .21. Postweaning gain h2A estimates ranged from .16 to .56. The genetic correlation between direct and maternal portions of birth weight was negative for all breeds. This was also true for the genetic correlation between direct and maternal portions of 205-d weight, except in Brahman cattle, for which it was .15. The genetic correlation between additive portions of birth weight and 205-d weight was large and positive in all breeds. A moderately positive correlation between 205-d weight and postweaning gain was found for all breeds except Santa Gertrudis, whereas the environmental correlation between these two traits was a small to moderately negative estimate in all breeds. Brangus weaning sheath and navel score heritabilities indicated that genetic change for the size and shape of the sheath and navel area is possible.

Analysis of Variance↗

PubMed1991

Identification of compartmental models for perturbed cell populations using state-space parameter estimation techniques.

Multiple compartment models for describing synchronous cell kinetics in which cell populations are characterized by DNA content are reviewed. These models are useful for understanding and predicting a cell population's dynamic response to perturbations induced by drugs or radiation. A practical approach is proposed for determining the parameters of these models from empirical cell-cycle data. Specifically, a state-space parameter estimation algorithm based on the maximum likelihood method--developed and coded primarily for engineering applications and commercially available for personal computers and minicomputers--can be applied to DNA specific cell-cycle measurements from synchronized cell populations to produce model parameter estimates. This is demonstrated using published data from a cell-cycle experiment. The results show that the procedure works well, and that with careful experimental planning even better results should be possible. Since the compartmental model is often used to represent biological systems, this approach is widely applicable.

Algorithms↗

PubMed1979

Selection of optimal model for the DNA histogram by analysis of error of estimated parameters.

The ability of four different mathematical models of the DNA histogram to give accurate estimates for the fractions of cells in G1, S, and G2 + M has been investigated. The models studied differ in the form and number of parameters of the function used to represent cells in S-phase. Results obtained from simulated DNA histograms suggest that the standard deviations of the model parameters increase exponentially with the width of the G1 and G2 + M peaks of the histogram. Error analysis is presented as a method to select a model of optimal complexity in relation to the resolution provided by the data in a given set of DNA histograms. Introduction of additional parameters improves the agreement between model and data but may result in a less well-posed model. A model with an optimal number of parameters can therefore be found that will yield parameter estimates with the smallest possible standard deviations.

Cell Cycle↗

PubMed1979

A program package for simulation and parameter estimation in pharmacokinetic systems.

A set of programs is presented which has been developed for parameter estimation and simulation of models arising from pharmacokinetic applications. The programs can accommodate linear and nonlinear models with multiple inputs and multiple outputs. When the model is defined by differential equations, non-uniform repetitive dosage regimens can be handled. The model may also be entered in integrated form when single dose studies or uniform multiple dose studies are being considered. The programs employ a variable-step, variable-order integration routine to solve the model differential equations, and the Nelder-Mead simplex procedure to determine the parameter values which minimize a weighted least squares criterion. The programs have been written for an interactive time-sharing environment with the experimental data and model equations stored in files for future use.

Computers↗

PubMed1992

Analysis of variance of parameter estimates: F tests and t tests.

The problem of comparing and pooling experimentally independent estimates of a parameter such as a Michaelis constant (K) has been treated as a simple analysis of variance of "within" and "between" set deviations from the fitted variable (v). As applied to assessing the reproducibility of multiple estimates of the same K, this is identical to the procedure of Duggleby (Anal. Biochem. 189, 84-87, 1990). However, the theory developed here shows that applying Duggleby's procedure to the comparison of two experiments (each consisting of multiple data sets) depends critically on the assumption of equal errors within and between the individual sets, i.e., Fvb vw = s2wv/s2bv is close to 1. Application of the method when this is not the case will underestimate the common error (s2rv), overestimate its associated degrees of freedom (vr = vb+vw), and may suggest apparently significant differences where there are none. The theory also shows that this situation is an instance of the Fisher-Behrens problem and shows how Welch's solution can be applied. This gives the between set error s2bv as the corrected estimate of the common error and the corrected degrees of freedom as a simple function of vb, vw, and Fvb vw. When the nine prephenate dehydratase data sets which originally showed three apparently significant differences were reanalyzed in this way, all the variations in K were found to be within the range of the experimental error.

Analysis of Variance↗

PubMed1978

ESTRIP, a BASIC computer program for obtaining initial polyexponential parameter estimates.

A new BASIC exponential stripping program, ESTRIP, allows the relatively rapid calculation of initial polyexponential parameter estimates, as does the previously published FORTRAN IV program, CSTRIP. The potential advantages of the new program are that it can be run on microcomputers and minicomputers with BASIC capability and a relatively small core and that it can be easily modified by the user.

Computers↗

PubMed1977

Kinetic parameter estimation by numerical algorithms and multiple linear regression: theoretical.

A new method is presented for the determination of kinetic parameters based on a functional relationship among experimental data derived from the postulated model. The data, even though containing errors, are manifestations of this relationship, which should be satisfied by parameters fitted to the system. The procedure involves the use of numerical integration and/or differentiation of the data, followed by multiple linear regression. It does not require initial estimates or repetitive iteration for linear systems and can be applied to nonlinear models. The accuracy of estimated parameter depends on the goodness of the particular numerical approximation method used.

Computers↗

PubMedDate not supplied

Nonlinear gradient isotherm parameter estimation for proteins with consideration of salt competition and multiple forms.

Salt gradients in ion-exchange chromatography are routinely used to speed separation of proteins and to concentrate products, but systematic optimization of these gradients requires protein equilibrium data as a function of salt concentration. An understanding of conformational changes, aggregation, and salt effects, which include both competition and affinity modulation, is important for equilibrium isotherm parameter estimation. In this study, gradient elution of bovine serum albumin (BSA) in anion exchange was well predicted by a salt-modulated nonlinear isotherm which considers salt competition. The isotherm was able to predict BSA gradient elution from batch equilibrium data. The same isotherm was also able to predict elution for various gradient slopes when fitted to an intermediate slope gradient experiment. If multiple forms due to aggregation or denaturation exist, isotherm parameters are readily averaged in batch experiments because of the long equilibration times. Similarly, gradient experiments yield averaged parameters because the salt gradient tends to merge the closely eluting forms. However, in isocractic elution, if the reaction rate is not rapid enough to give a merged peak, the estimated isotherm parameters are only fair predictors of gradient behavior and vice versa. Slower flow rates in isocratic elution can help reduce the discrepancy by allowing forms to merge through interconversion. As an alternative to determining averaged parameters, consideration of two binding forms, using VERSE-LC, an advanced rate model, gave good agreement with experimental data over the entire range of salt gradient durations.

Animals↗

PubMed1992

Transport parameter estimation from lymph measurements and the Patlak equation.

Two methods of estimating protein transport parameters for plasma-to-lymph transport data are presented. Both use IBM-compatible computers to obtain least-squares parameters for the solvent drag reflection coefficient and the permeability-surface area product using the Patlak equation. A matrix search approach is described, and the speed and convenience of this are compared with a commercially available gradient method. The results from both of these methods were different from those of a method reported by Reed, Townsley, and Taylor [Am. J. Physiol. 257 (Heart Circ. Physiol. 26): H1037-H1041, 1989]. It is shown that the Reed et al. method contains a systematic error. It is also shown that diffusion always plays an important role for transmembrane transport at the exit end of a membrane channel under all conditions of lymph flow rate and that the statement that diffusion becomes zero at high lymph flow rate depends on a mathematical definition of diffusion.

Animals↗