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At least 19 recordsLinked to original sources
PubMed1984

The design of the Epidemiologic Catchment Area surveys. The control and measurement of error.

Several methods are used to minimize and measure error in the NIMH Epidemiologic Catchment Area program. Sampling methods involve the inclusion of group quarters such as prisons, nursing homes, and mental hospitals in the sample frame and the use of probability sampling throughout. Interviewing, methods include use of identical diagnostic interview protocols, centralized training of interview supervisors, standard instructions to interviewers, and reinterview of a subsample by clinicians. In the area of completion, the methods include a 75% to 80% respondent completion rate, a 95% or greater completion rate for individual questions, use of informant interviews where necessary, and statistical adjustments to correct for low completion rates in some subgroups. Analytic methods include use of a computerized diagnostic algorithm, common estimation formulas on identically formatted data files, and estimation of exact variances that take account of the multistage sample design.

Catchment Area, Health↗
PubMed1975

Construction of an interpretive pattern directory for the API 10 S kit and analysis of its diagnostic accuracy.

A directory of test patterns and their interpretations has been prepared for identification of Enterobacteriaceae by using the 11-test API 10 S kit. The diagnostic accuracy of the directory and kit were evaluated by using records of test results for 37,476 isolates studied with the 21-test API 20 Enteric kit. Analysis indicates that 96.9% of the isolates would have been correctly identified at the genus level and 95.9% at the species level by using only the subset of tests included in the API 10 S.

Bacteriological Techniques↗
PubMed2004

Optimization of a vector quantization codebook for objective evaluation of surgical skill.

Surgical robotic systems and virtual reality simulators have introduced an unprecedented precision of measurement for both tool-tissue and tool-surgeon interaction; thus holding promise for more objective analyses of surgical skill. Integrative or averaged metrics such as path length, time-to-task, success/failure percentages, etc., have often been employed towards this end but these fail to address the processes associated with a surgical task as a dynamic phenomena. Stochastic tools such as Markov modeling using a 'white-box' approach have proven amenable to this type of analysis. While such an approach reveals the internal structure of the of the surgical task as a process, it requires a task decomposition based on expert knowledge, which may result in a relatively large/complex model. In this work, a 'black box' approach is developed with generalized cross-procedural applications., the model is characterized by a compact topology, abstract state definitions, and optimized codebook size. Data sets of isolated tasks were extracted from the Blue DRAGON database consisting of 30 surgical subjects stratified into six training levels. Vector quantization (VQ) was employed on the entire database, thus synthesizing a lexicon of discrete, task-independent surgical tool/tissue interactions. VQ has successfully established a dictionary of 63 surgical code words and displayed non-temporal skill discrimination. VQ allows for a more cross-procedural analysis without relying on a thorough study of the procedure, links the results of the black-box approach to observable phenomena, and reduces the computational cost of the analysis by discretizing a complex, continuous data space.

Algorithms↗