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At least 595 records · Page 33Linked to original sources
PubMed1996

Quantitative investigation of population persistence and recurrent outbreaks of bovine respiratory syncytial virus on dairy farms.

OBJECTIVE: To determine if transmission of virus among seropositive cattle is a plausible mechanism for the permanent presence of bovine respiratory syncytial virus (BRSV) in dairy herds, and how likely, with the scenario for persistence, there will be only 1 clinical outbreak of BRSV per year. DESIGN: Build a stochastic model, parameter estimation from serologic data on BRSV, and interpret the estimated parameter values from the model analysis. SAMPLE POPULATION: Monthly data on the prevalence of antibodies directed against BRSV in sera from all cattle in 6 dairy herds. PROCEDURE: Parameter estimation applying general linear models, model analysis using calculation of the reproduction ratio for simplified models, and Monte-Carlo simulation for the whole model. RESULTS: Persistence of BRSV by transmission among seropositive cattle given estimated parameter values would be accompanied by frequent extinctions (once every 10 to 50 years) and long infectious periods in seropositive cattle (100 days). Moreover, in the model, a single clinical outbreak among seronegative cattle only occurred with external forcing. CONCLUSIONS: From these data, transmission among seropositive cattle is not a plausible mechanism for persistence of BRSV in dairy herds.

Animals↗
PubMed2004

The effect of sample size for estimating Rasch/IRT parameters with dichotomous items.

Thirteen samples were randomly drawn from the normative database for the latest edition of Knox's Cube Test-Revised (KCT-R). Parameter estimates for the Rasch model and two and three parameter logistic models were derived and compared. Sample size influenced these estimates as might be expected. Rasch parameter estimates consistently showed the smallest values by sample size using a goodness of fit index.

Data Interpretation, Statistical↗
PubMed1997

Intracranial pressure dynamics in patients with acute brain damage.

The time pattern of intracranial pressure (ICP) during pressure-volume index (PVI) tests was analyzed in 20 patients with severe acute brain damage by means of a simple mathematical model. In most cases, a satisfactory fitting between model response and patient data was achieved by adjusting only four parameters: the cerebrospinal fluid (CSF) outflow resistance, the intracranial elastance coefficient, and the gain and time constant of cerebral autoregulation. The correlation between the parameter estimates was also analyzed to elucidate the main mechanisms responsible for ICP changes in each patient. Starting from information on the estimated parameter values and their correlation, the patients were classified into two main classes: those with weak autoregulation (8 of 20 patients) and those with strong autoregulation (12 of 20 patients). In the first group of patients, ICP mainly reflects CSF circulation and passive cerebral blood volume changes. In the second group, ICP exhibits paradoxical responses attributable to active changes in cerebral blood volume. Moreover, in two patients of the second group, the time constant of autoregulation is significantly increased (>40 s). The correlation between the parameter estimates was significantly different in the two groups of patients, suggesting the existence of different mechanisms responsible for ICP changes. Moreover, analysis of the correlation between the parameter estimates might give information on the directions of parameter changes that have a greater impact on ICP.

Acute Disease↗
PubMed2000

Usefulness of single nucleotide polymorphism data for estimating population parameters.

Single nucleotide polymorphism (SNP) data can be used for parameter estimation via maximum likelihood methods as long as the way in which the SNPs were determined is known, so that an appropriate likelihood formula can be constructed. We present such likelihoods for several sampling methods. As a test of these approaches, we consider use of SNPs to estimate the parameter Theta = 4N(e)micro (the scaled product of effective population size and per-site mutation rate), which is related to the branch lengths of the reconstructed genealogy. With infinite amounts of data, ML models using SNP data are expected to produce consistent estimates of Theta. With finite amounts of data the estimates are accurate when Theta is high, but tend to be biased upward when Theta is low. If recombination is present and not allowed for in the analysis, the results are additionally biased upward, but this effect can be removed by incorporating recombination into the analysis. SNPs defined as sites that are polymorphic in the actual sample under consideration (sample SNPs) are somewhat more accurate for estimation of Theta than SNPs defined by their polymorphism in a panel chosen from the same population (panel SNPs). Misrepresenting panel SNPs as sample SNPs leads to large errors in the maximum likelihood estimate of Theta. Researchers collecting SNPs should collect and preserve information about the method of ascertainment so that the data can be accurately analyzed.

Computer Simulation↗
PubMed1983

Optimal frequency locations for estimating model parameters in studies on respiratory control.

Sinusoidal work rate inputs yield a dynamic ventilatory response which can be fitted to a mathematical model. The model structure leads to inferences about the underlying physiology of the respiratory control mechanism. A particular problem of interest in model parameter estimation concerns the location of the test frequencies. The effects of estimating the parameters of a relatively complex model developed by Fujihara et al. using arbitrary frequency locations from a study by Casaburi et al. versus using the frequencies derived from an optimization method presented in a recent paper by Engeman et al. were examined. The Fujihara model is indicated to be much more likely to be justified when optimal sinusoids are used to generate the data than when Casaburi's arbitrary frequencies are used. The implications are that more descriptive models of respiratory control may be developed with the aid of optimal frequency design for the input sinusoids.

Humans↗
PubMed2000

Ascertainment adjustment: where does it take us?

It is commonly assumed that the parameter estimates of a statistical genetics model that has been adjusted for ascertainment will estimate parameters in the general population from which the ascertained subpopulation was originally drawn. We show that this is true only in certain restricted circumstances. More generally, ascertainment-adjusted parameter estimates reflect parameters in the ascertained subpopulation. In many situations, this shift in perspective is immaterial: the parameters of interest are the same in the ascertained sample and in the population from which it was drawn, and it is therefore irrelevant to which population inferences are presumed to apply. In other circumstances, however, this is not so. This has important implications, particularly for studies investigating the etiology of complex diseases.

Computer Simulation↗