Optimal Sampling Strategies for Statistical Models with Discrete Dependent Variables

1980 ◽  
Vol 14 (4) ◽  
pp. 324-345 ◽  
Author(s):  
Carlos F. Daganzo
Keyword(s):  
Statistical Models ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Dependent Variables ◽  
Discrete Dependent Variables

scholarly journals Optimal Sampling Strategies for Detecting Zoonotic Disease Epidemics

2014 ◽  
Vol 10 (6) ◽  
pp. e1003668 ◽  
Author(s):  
Jake M. Ferguson ◽  
Jessica B. Langebrake ◽  
Vincent L. Cannataro ◽  
Andres J. Garcia ◽  
Elizabeth A. Hamman ◽  
...  
Keyword(s):  
Zoonotic Disease ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Disease Epidemics

scholarly journals Pharmacokinetic Modeling and Optimal Sampling Strategies for Therapeutic Drug Monitoring of Rifampin in Patients with Tuberculosis

2015 ◽  
Vol 59 (8) ◽  
pp. 4907-4913 ◽  
Author(s):  
Marieke G. G. Sturkenboom ◽  
Leonie W. Mulder ◽  
Arthur de Jager ◽  
Richard van Altena ◽  
Rob E. Aarnoutse ◽  
...  
Keyword(s):  
Population Pharmacokinetic Model ◽  
Pharmacokinetic Model ◽  
Mean Squared Error ◽  
Geometric Mean ◽  
Plasma Concentrations ◽  
Therapeutic Drug ◽  
Population Pharmacokinetic ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Wide Range

ABSTRACTRifampin, together with isoniazid, has been the backbone of the current first-line treatment of tuberculosis (TB). The ratio of the area under the concentration-time curve from 0 to 24 h (AUC0–24) to the MIC is the best predictive pharmacokinetic-pharmacodynamic parameter for determinations of efficacy. The objective of this study was to develop an optimal sampling procedure based on population pharmacokinetics to predict AUC0–24values. Patients received rifampin orally once daily as part of their anti-TB treatment. A one-compartmental pharmacokinetic population model with first-order absorption and lag time was developed using observed rifampin plasma concentrations from 55 patients. The population pharmacokinetic model was developed using an iterative two-stage Bayesian procedure and was cross-validated. Optimal sampling strategies were calculated using Monte Carlo simulation (n= 1,000). The geometric mean AUC0–24value was 41.5 (range, 13.5 to 117) mg · h/liter. The median time to maximum concentration of drug in serum (Tmax) was 2.2 h, ranging from 0.4 to 5.7 h. This wide range indicates that obtaining a concentration level at 2 h (C2) would not capture the peak concentration in a large proportion of the population. Optimal sampling using concentrations at 1, 3, and 8 h postdosing was considered clinically suitable with anr2value of 0.96, a root mean squared error value of 13.2%, and a prediction bias value of −0.4%. This study showed that the rifampin AUC0–24in TB patients can be predicted with acceptable accuracy and precision using the developed population pharmacokinetic model with optimal sampling at time points 1, 3, and 8 h.

scholarly journals Optimal Sampling Strategies in Quicksort and Quickselect

2001 ◽  
Vol 31 (3) ◽  
pp. 683-705 ◽  
Author(s):  
Conrado Martínez ◽  
Salvador Roura
Keyword(s):  
Optimal Sampling ◽  
Sampling Strategies

Determining optimal sampling strategies for monitoring mercury and reproductive success in common loons in the Adirondacks of New York

Ecotoxicology ◽  
2019 ◽  
Vol 29 (10) ◽  
pp. 1786-1793 ◽  
Author(s):  
Yang Yang ◽  
Ruth D. Yanai ◽  
Nina Schoch ◽  
Valerie L. Buxton ◽  
Kara E. Gonzales ◽  
...  
Keyword(s):  
New York ◽  
Reproductive Success ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Common Loons
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