893 resultados para data analysis: algorithms and implementation
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This is a photocopy reproduction.
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"September 1985."
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Mode of access: Internet.
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National Highway Traffic Safety Administration, Office of Vehicle Safety Research, Washington, D.C.
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National Highway Traffic Safety Administration, Washington, D.C.
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Mode of access: Internet.
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"HRDI-13/11-05(1M)E"--P. [4] of cover.
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Mode of access: Internet.
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"UILU-ENG 80 1741"--Cover.
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Mode of access: Internet.
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This paper reviews the key features of an environment to support domain users in spatial information system (SIS) development. It presents a full design and prototype implementation of a repository system for the storage and management of metadata, focusing on a subset of spatial data integrity constraint classes. The system is designed to support spatial system development and customization by users within the domain that the system will operate.
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n early 2001 there was a dramatic decline in the availability of heroin in New South Wales (NSW), Australia, where previously heroin had been readily available at a low price and high purity.1 The decline was confirmed by Australia's strategic early warning system, which revealed a reduction in heroin supply across Australia and a considerable increase in price,2 particularly from January to April 2001. This "heroin shortage" provided a natural experiment in which to examine the effect of substantial changes in price and availability on injecting drug use and its associated harms in Australia's largest heroin market,2 a setting in which harm reduction strategies were widely used. Publicly funded needle and syringe programmes were introduced to Australia in 1987, and methadone maintenance programmes, which were established in the 1970s, were significantly expanded in 1985 and again in 1999.
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The aim of this report is to describe the use of WinBUGS for two datasets that arise from typical population pharmacokinetic studies. The first dataset relates to gentamicin concentration-time data that arose as part of routine clinical care of 55 neonates. The second dataset incorporated data from 96 patients receiving enoxaparin. Both datasets were originally analyzed by using NONMEM. In the first instance, although NONMEM provided reasonable estimates of the fixed effects parameters it was unable to provide satisfactory estimates of the between-subject variance. In the second instance, the use of NONMEM resulted in the development of a successful model, albeit with limited available information on the between-subject variability of the pharmacokinetic parameters. WinBUGS was used to develop a model for both of these datasets. Model comparison for the enoxaparin dataset was performed by using the posterior distribution of the log-likelihood and a posterior predictive check. The use of WinBUGS supported the same structural models tried in NONMEM. For the gentamicin dataset a one-compartment model with intravenous infusion was developed, and the population parameters including the full between-subject variance-covariance matrix were available. Analysis of the enoxaparin dataset supported a two compartment model as superior to the one-compartment model, based on the posterior predictive check. Again, the full between-subject variance-covariance matrix parameters were available. Fully Bayesian approaches using MCMC methods, via WinBUGS, can offer added value for analysis of population pharmacokinetic data.