
pmid: 2277875
AbstractWe present a critical review of aspects of clinical decision analysis which uses an application to screening for familial intracranial aneurysms. The analysis is reported together with methods for assessing decision trees. These methods appear to be powerful checks on the usually rather intuitive way in which decision trees are built. The problem of assessing the uncertainty in the results of a decision analysis is discussed in detail. In practice, sensitivity analysis covers nearly every calculation apart from the standard evaluation of the decision tree. Different forms of sensitivity analysis are distinguished and given appropriate names: influence analysis, threshold analysis, full Bayesian analysis, Bayesian influence analysis, attribute analysis, generalization analysis and scenario analysis. The biostatistical community may well contribute to the much needed methodological improvement in decision analysis and its different forms of sensitivity analysis, especially if prepared to look beyond the standard statistical techniques.
Adult, Family Health, Decision Trees, Humans, Mass Screening, Bayes Theorem, Female, Intracranial Aneurysm, Decision Support Techniques
Adult, Family Health, Decision Trees, Humans, Mass Screening, Bayes Theorem, Female, Intracranial Aneurysm, Decision Support Techniques
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 40 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
