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PubMed1997

Discrimination between rival dosing histories.

PURPOSE: In population pharmacokinetic studies, the dosing history is sometimes recorded in more than one way. The purpose of this study was to develop and evaluate a procedure for discriminating between rival dosing histories, i.e., for each individual in a data set, identify the dosing history that is the most plausible. METHODS: The procedure consists of four steps. In the first step we identify individuals whose dosing histories produce predictions that are consistent. In the second step these individuals are used to build a population pharmacokinetic model which is used, in step three, to select the dosing history for the individuals not identified in step one. In step four the population model is refined using the best available dosing histories for all individuals. The proposed procedure was evaluated using both simulations and a real data set, in which two dosing histories, based on patient diaries and electronic monitoring devices (MEMS) were available. RESULTS: In the real data set, estimated variabilities were almost always lower when the selected dosing histories were used compared to when no selection procedure was used. The diary dosing histories were selected more often than the MEMS dosing histories. In the simulations, the parameter estimates obtained using the selection procedure were closer to the true parameter values compared to when only one of the dosing histories was used. CONCLUSIONS: The proposed procedure appears to be robust and should be beneficial in at least two respects: improved parameter estimation of population pharmacokinetic and PK/PD models and objective information by which dosage recording methodologies can be compared and patient dose recording behavior can be assessed.

Algorithms↗

PubMed1984

Power spectral density analysis of lateral human standing sway.

A number of investigators have used power spectral density (PSD) analysis to try to identify and quantify various sensory systems which are involved in upright standing. Using PSD analysis, over a frequency range from 0.02-2.5 Hz, the present study examined two trials of lateral sway in each of 80 men. The results showed that little change occurred in PSD values between the first and second trials. Exponential curves were fit to the averaged trials data of each subject. The values of the parameter estimates obtained from the curve-fitting were regressed on the values of various direct, and derived anthropometric variables to try to explain the variance of the parameter estimates in terms of the anthropometrics. The subject's center of gravity location accounted for no more than 15.8% of the parameter variance, whereas the remaining anthropometrics explained even less. The overall averaged data suggest that three functions (related to visual, vestibular, and proprioceptive processes) may underlie the sway pattern over this frequency range. PSD curves of individuals with a history of high-level athletic activity clearly differed from those of sedentary subjects.

Journal Article↗

PubMed1986

The demand for health: some new empirical evidence.

This paper presents some new estimates of the 'pure investment' and 'pure consumption' models of the demand for health. In contrast to previous studies, the paper presents parameter estimates of both reduced-form and structural demand for health care equations. The latter--which are obtained by treating health capital as a latent variable in a recursive equation system--provide a safer way of checking the consistency of the model's predictions with the data. The present analysis of the pure consumption model differs from previous analyses in its recognition of the dependency of the shadow price of initial assets on the entire lifetime profiles of the model's exogenous variables. The paper also explores the implications in terms of reliability of parameter estimates of the failure on the part of previous studies to recognize this.

Costs and Cost Analysis↗

PubMed1998

Analysis of endogenous process behavior in activated sludge.

In this article, an autonomous four-compartment model that describes the endogenous respiration in an aerobic biodegradation process is proposed and analyzed theoretically. First, the multi-time scale of the system's behavior, to be taken into account in subsequent analyses, is emphasized. Then, an identifiability and observability study, given measurements of MLVSS (mixed liquor volatile suspended solids) and respiration rate, is performed for use under practical circumstances, such as in state and parameter estimation. It appears that the process is observable, but not fully identifiable. Hence, for the identification of some of the model parameters, additional measurements or experiments, also indicated here, have to be performed. Furthermore, it is shown that, under quasi-steady state conditions which, in general, appear shortly after initialization of an endogenous respiration experiment, the model can be reduced significantly. Finally, results of parameter estimation from available data are presented and discussed.

Aerobiosis↗

PubMed1994

Fitting epidemiologic follow-up studies with cumulative damage models.

The use of an extended version of the cumulative damage model to identify and quantify cancer risk arising from a specified exposure is outlined. For this, a strategy to fit the model to individual data coming from epidemiologic follow-up studies is described. Two statistical problems are addressed: first, the regularity of the model has to be ascertained to allow the application of maximum-likelihood and likelihood-ratio methods for parameter estimation and testing. Second, a statistical test has to be found that permits testing goodness of fit in the setting of parameter estimation with individual data. As an example, these methods are applied to the data of a cohort study on mortality among stainless steel welders in the Federal Republic of Germany. The results show that the model fits the data well and confirms a carcinogenic effect of stainless steel welding among welders. Some distinguishing characteristics of the model, especially its prediction of a potentially decreasing relative risk despite ongoing carcinogenic exposure, are discussed.

Carcinogens↗

PubMed2003

A tobit variance-component method for linkage analysis of censored trait data.

Variance-component (VC) methods are flexible and powerful procedures for the mapping of genes that influence quantitative traits. However, traditional VC methods make the critical assumption that the quantitative-trait data within a family either follow or can be transformed to follow a multivariate normal distribution. Violation of the multivariate normality assumption can occur if trait data are censored at some threshold value. Trait censoring can arise in a variety of ways, including assay limitation or confounding due to medication. Valid linkage analyses of censored data require the development of a modified VC method that directly models the censoring event. Here, we present such a model, which we call the "tobit VC method." Using simulation studies, we compare and contrast the performance of the traditional and tobit VC methods for linkage analysis of censored trait data. For the simulation settings that we considered, our results suggest that (1) analyses of censored data by using the traditional VC method lead to severe bias in parameter estimates and a modest increase in false-positive linkage findings, (2) analyses with the tobit VC method lead to unbiased parameter estimates and type I error rates that reflect nominal levels, and (3) the tobit VC method has a modest increase in linkage power as compared with the traditional VC method. We also apply the tobit VC method to censored data from the Finland-United States Investigation of Non-Insulin-Dependent Diabetes Mellitus Genetics study and provide two examples in which the tobit VC method yields noticeably different results as compared with the traditional method.

Analysis of Variance↗

PubMed1988

A comparison of the accuracy of a least squares regression, a Bayesian, Chiou's and the steady-state clearance method of individualising theophylline dosage.

We compared a least squares regression method, used prospectively to individualise the intravenous aminophylline and oral theophylline dosage of 48 patients, with 3 other pharmacokinetic methods - Chiou's, the steady-state clearance and the Bayesian - used retrospectively to analyse the same patient data. Methods were compared on the basis of the similarity of their parameter estimates and the accuracy with which serum concentrations during subsequent intravenous and oral therapy could be forecast, assuming each method's parameter estimates. The least squares and Bayesian programs were able to fit data from all but 4 and 2 patients, respectively. Mean absolute prediction errors were of the order of 20% for serum concentrations during intravenous therapy, and of the order of 40% for serum concentrations during oral therapy. The accuracy of the least squares, Bayesian and steady-state clearance methods were similar, but the accuracy of Chiou's method was comparable only when the 2 serum concentrations needed for the method were measured between 11 and 17 hours apart; an interval which corresponds to the 1.0 to 1.5 half-lives previously suggested as desirable for implementation of the Chiou method.

Adult↗

PubMed2006

An application of the GLUE methodology for estimating the parameters of the INCA-N model.

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist.

Agriculture↗

PubMed2000

Population pharmacokinetics of tacrolimus in Asian paediatric liver transplant patients.

AIMS: The purpose of this study was to describe the population pharmacokinetics of intravenous and oral tacrolimus (FK506) in 20 Asian paediatric patients, aged 1-14 years, following liver transplantation and to identify possible relationships between clinical covariates and population parameter estimates. METHODS: Details of drug dosage histories, sampling times and concentrations were collected retrospectively from routine therapeutic drug monitoring data accumulated for at least 4 days after surgery. Before analysis, patients were randomly allocated to either the population data set (n = 16) or a validation data set (n = 4). The population data set was comprised of 771 concentration measurements of patients admitted over the last 3 years. Population modelling using the nonlinear mixed-effects model (NONMEM) program was performed on the population data set, using a one-compartment model with first-order absorption and elimination. Population average parameter estimates of clearance (CL), volume of distribution (V) and oral bioavailability (F) were sought; a number of clinical and demographic variables were tested for their influence on these parameters. RESULTS: The final optimal population models related clearance to age, volume of distribution to body surface area and bioavailability to body weight and total bilirubin concentration. Predictive performance of this model evaluated using the validation data set, which comprised 86 concentrations, showed insignificant bias between observed and model-predicted blood tacrolimus concentrations. A final analysis performed in all 20 patients identified the following relationships: CL (l h-1) = 1.46 *[1 + 0. 339 * (AGE (years) -2.25)]; V (l) = 39.1 *[1 + 4.57 * (BSA (m2)-0. 49)]; F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] and F = 0.197 *[1 + 0.0887 * (WT (kg) -11.4)] * [1.61], if the total bilirubin > or = 200 micromol l-1. The interpatient variabilities (CV%) in CL, V and F were 33.5%, 33.0% and 24.1%, respectively. The intrapatient variability (s.d.) among observed and model-predicted blood concentrations was 5.79 ng ml-1. CONCLUSIONS: In this study, the estimates of the pharmacokinetic parameters of tacrolimus agreed with those obtained from conventional pharmacokinetic studies. It also identified significant relationships in Asian paediatric liver transplant patients between the pharmacokinetics of tacrolimus and developmental characteristics of the patients.

Asia↗

PubMed2000

Numerical methods for the evaluation of individual bioequivalence criteria.

The evaluation of individual bioequivalence (IBE) by bootstrap resampling using common statistical software, for example SAS, is extremely time consuming. In this article, an estimation procedure that can be implemented in a high level language with the same degree of accuracy as SAS is described. The necessary parameter estimating equations under both least square (LSE) and restricted maximum likelihood (REML) methods are given. The algorithms used to numerically compute these values are outlined and tested, in FORTRAN, on several simulated data sets and shown to reproduce SAS results with at least 10(-3) precision. More importantly, the REML bootstrap algorithm reduces the time taken in SAS by a factor of 20. Secondary results indicate that LSE and REML parameter estimates are similar for mild unbalancedness. PROC MIXED, with unstructured (UN) and compound symmetry heterogeneous (CSH) variance structures give the same results except when the subject-by-treatment interaction variance, sigma(2)(D), is 0 in which case CSH significantly overestimates sigma(2)(D) and underestimates the within-treatment variances. It is concluded that bootstrap evaluation of IBE is efficiently done using either the LSE or REML algorithm in FORTRAN.

Algorithms↗

PubMed1979

Practical application of generic growth theory and the significance of the growth curve parameters.

The generic growth curve is developed by plausibility arguments based on simple growth models. Parameters of the generic curve include the maximum size, maximum specific growth rate, and a dimensionless velocity constant which can be related to metabolic efficiency in the case of nutrient-limited growth. Parameter estimates are obtained from estimates of the size and time at the point of inflection, the size and time at any other arbitrarily selected point, and the maximum size. Parameter estimates thus obtained and used as initial estimates in nonlinear least squares analysis often give rapid convergence to a minimum error mean square. [For the growth of Escherichia coli K-12 in liquid medium, the generic curve could be simplified to a form containing only three parameters: the maximum specific growth rate, the maximum size, and the time required to reach maximum size. When the bacteria were inhibited by the addition of increasing amounts of the lactoperoxidase antimicrobial factor, there was no significant change in viable counts or maximum specific growth rate, but the time required to reach maximum growth increased linearly with increasing amounts of added antimicrobial factor.] Analysis of growth in terms of the generic growth curve can be a powerful technique for finding relationships which may not be apparent from qualitative consideration of the data.

Biometry↗

PubMedDate not supplied

Evaluation of the quality of clinical research studies of magnetic resonance angiography: 1991-1994.

To evaluate the quality of clinical research studies of magnetic resonance angiography (MRA), the authors reviewed studies of carotid, renal, and lower extremity MRA published in English during 1991-1994. The purpose, design, and implementation of the study, and the type of statistical information presented, were evaluated. The results were compared with those of previous studies that assessed the quality of MRI research. Fifty-nine studies of renal (n = 10), carotid (n = 29), and lower extremity (n = 20) MRA were identified; 30 met the inclusion criteria for the analysis. In these papers, presentation of a reference standard was routine, observer blinding was usual, information often was given about patient selection and exclusion, sample sizes were always given, and parameter estimates and statistical analyses were common. However, evidence of research planning was not routine, measurement of interobserver variability was occasional, variability of parameter estimates was usually not estimated, and validation of statistical assumptions was uncommon. On balance the authors conclude that the scientific quality of recent investigations of MRA is better than that of older studies of MRI.

Arteries↗

PubMed1977

Iodipamide kinetics: capacity-limited biliary excretion with simultaneous pseudo-first-order renal excretion.

Iodipamide was infused into three dogs with bile fistulas to achieve various steady-state blood levels. When using ultracentrifugation techniques, iodipamide was found to be highly bound to plasma protein. The total blood clearance was low relative to hepatic blood flow. For either the whole blood concentration or the unbound concentration of iodipamide, the biliary excretion was shown to be capacity limited with a transport maximum, Tm, of approximately 1.0mumole/kg/min. The steady-state renal excretion rate, plotted against the whole blood concentration of iodipamide, resulted in a concave ascending curve, which could lead to the false conclusion that iodipamide was undergoing active renal tubular reabsorption. However, when corrected for plasma protein binding, a linear relationship was obtained, suggesting that the renal excretion of iodipamide is a pseudo-first-order process. The Michaelis-Menten parameters for the extrarenal elimination, when calculated using the whole blood concentration of iodipamide, led to a similar discrepancy compared to the parameter estimates obtained from biliary excretion rate data. This discrepancy can be eliminated when one uses the unbound concentration of iodipamide in the parameter estimates.

Animals↗

PubMedDate not supplied

Depression-related hyperglycemia in type 1 diabetes: a mediational approach.

OBJECTIVE: Depression is linked with hyperglycemia and with an increased risk for diabetes complications, but the mechanisms underlying these relationships have not been established. In this study, we applied mediational analysis methods to determine whether the hyperglycemic effect of depression could be mediated by poor diabetes self-care. METHODS: Depression symptoms and diabetes self-care activity were assessed in a primary care sample of 188 patients with type 1 diabetes by using the Hopkins Symptom Checklist-90 (SCL-90) and the Summary of Diabetes Self-Care Activities (SDSCA). A composite score of self-care activity was formed from SDSCA ratings for diet amount, exercise, and glucose testing. Degree of hyperglycemia (level of glycosylated hemoglobin [HbA1c]), weight, insulin dose, and other clinical characteristics were obtained from electronic medical records. Ordinary least-squares regression was used to determine the effect of depression on HbA1c level controlling for weight and insulin dose. The SDSCA score was then added to the regression model to determine whether it attenuated the effect of depression symptoms on HbA1c level, thus providing suggestive evidence of mediation from these cross-sectional data. RESULTS: Depression symptoms, poor diabetes self-care, and hyperglycemia were correlated with one another in univariate analyses (p <.05). Depression symptoms were associated with higher HbA1c after controlling for weight and insulin dose (parameter estimate for depression 0.53, t = 3.6, p <.001). Inclusion of SDSCA in the model minimally attenuated the effect of depression symptoms (adjusted parameter estimate for depression 0.50, t = 3.3, p = .001). CONCLUSIONS: These findings do not support mediation of the depression-hyperglycemia relationship by diabetes self-care behavior. Other pathways, including psychophysiological mechanisms, should be investigated.

Adult↗

PubMed1975

Simultaneity bias in migration models: an empirical examination.

A number of migration studies have attempted to explain migration that occurred over a given time interval by means of variables defined for the end of the period and/or variables relating to changes that occurred over the period. Since migration may influence end-of-period levels of explanatory variables by influencing the behavior of these variables over the period of migration, simultaneous-equations bias may be inherent in the parameter estimates of the many single-equation, multiple-regression analyses. This study constitutes an empirical examination of qualitative differences in the parameter estimates of five different types of migration models estimated for two different time periods, 1960 and 1970.

Employment↗

PubMedDate not supplied

The site-scale saturated zone flow model for Yucca Mountain: calibration of different conceptual models and their impact on flow paths.

This paper presents several different conceptual models of the Large Hydraulic Gradient (LHG) region north of Yucca Mountain and describes the impact of those models on groundwater flow near the potential high-level repository site. The results are based on a numerical model of site-scale saturated zone beneath Yucca Mountain. This model is used for performance assessment predictions of radionuclide transport and to guide future data collection and modeling activities. The numerical model is calibrated by matching available water level measurements using parameter estimation techniques, along with more informal comparisons of the model to hydrologic and geochemical information. The model software (hydrologic simulation code FEHM and parameter estimation software PEST) and model setup allows for efficient calibration of multiple conceptual models. Until now, the Large Hydraulic Gradient has been simulated using a low-permeability, east-west oriented feature, even though direct evidence for this feature is lacking. In addition to this model, we investigate and calibrate three additional conceptual models of the Large Hydraulic Gradient, all of which are based on a presumed zone of hydrothermal chemical alteration north of Yucca Mountain. After examining the heads and permeabilities obtained from the calibrated models, we present particle pathways from the potential repository that record differences in the predicted groundwater flow regime. The results show that Large Hydraulic Gradient can be represented with the alternate conceptual models that include the hydrothermally altered zone. The predicted pathways are mildly sensitive to the choice of the conceptual model and more sensitive to the quality of calibration in the vicinity on the repository. These differences are most likely due to different degrees of fit of model to data, and do not represent important differences in hydrologic conditions for the different conceptual models.

Calibration↗

PubMed1997

Modeling of trough plasma bismuth concentrations.

Disposition pharmacokinetics of bismuth following oral dosing of ranitidine bismuth citrate are complicated and variable. An analysis of data from healthy volunteers suggests a model with three disposition compartments and first-order absorption. Patient data are pooled from 10 separate studies and consist of 1140 trough concentrations measured in 802 patients following dosing of 2 to 12 weeks duration. There are therefore insufficient data to obtain reliable parameter estimates for the full model and we use instead a much reduced model and an informative prior based on the volunteer data. Individual parameter estimates from this model can then be used to establish covariate relationships. Trough concentrations were influenced by the coadministration of clarithromycin and by creatinine clearance. A simulation study was carried out to check the validity of the estimates obtained from the reduced model. We carry out analysis via Bayesian sampling-based techniques. Throughout, we use predictive distributions for both diagnostic and inference purposes. In particular, we determine predicted distributions for the Cmax, Cmin and AUC characteristics of new individuals.

Bayes Theorem↗

PubMed2004

Investigation of possible neural architectures underlying information-geometric measures.

A novel analytical method based on information geometry was recently proposed, and this method may provide useful insights into the statistical interactions within neural groups. The link between informationgeometric measures and the structure of neural interactions has not yet been elucidated, however, because of the ill-posed nature of the problem. Here, possible neural architectures underlying information-geometric measures are investigated using an isolated pair and an isolated triplet of model neurons. By assuming the existence of equilibrium states, we derive analytically the relationship between the information-geometric parameters and these simple neural architectures. For symmetric networks, the first- and second-order information-geometric parameters represent, respectively, the external input and the underlying connections between the neurons provided that the number of neurons used in the parameter estimation in the log-linear model and the number of neurons in the network are the same. For asymmetric networks, however, these parameters are dependent on both the intrinsic connections and the external inputs to each neuron. In addition, we derive the relation between the information-geometric parameter corresponding to the two-neuron interaction and a conventional cross-correlation measure. We also show that the information-geometric parameters vary depending on the number of neurons assumed for parameter estimation in the log-linear model. This finding suggests a need to examine the information-geometric method carefully. A possible criterion for choosing an appropriate orthogonal coordinate is also discussed. This article points out the importance of a model-based approach and sheds light on the possible neural structure underlying the application of information geometry to neural network analysis.

Action Potentials↗