Directions for improvement of substitute heart valves: National Heart, Lung, and Blood Institute's Working Group report on heart valves.
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Biomedical subjects
Publications and source records attributed to W Q Meeker.
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A computer pattern recognition system, RAPID, has been used to study the spontaneous motor activity of Sprague-Dawley rats. This system produces a large number of measures of the activity of control and experimental groups in any given study. The large number of measures involved presents a problem when one attempts to decide whether the behavioral activity of the exposed group differs from that of the control group. Extensive Monte Carlo studies have been performed in an attempt to develop and validate a simple statistic to be used in such decisions.
In this paper we show how to evaluate the effect that perturbations to the model, data, or case weights have on maximum likelihood estimates from censored survival data. The ideas and methods also apply to other nonlinear estimation problems. We review the ideas behind using log-likelihood displacement and local influence methods. We describe new interpretations for some local influence statistics and show how these statistics extend and complement traditional case deletion influence statistics for linear least squares. These statistics identify individual and combinations of cases that have important influence on estimates of parameters and functions of these parameters. We illustrate the methods by reanalyzing the Stanford Heart Transplant data with a parametric regression model.