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Inhaltsverzeichnis - Mathematisches Institut der Universität zu Köln

Inhaltsverzeichnis - Mathematisches Institut der Universität zu Köln

Inhaltsverzeichnis - Mathematisches Institut der Universität zu Köln

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DMV Tagung 2011 - <strong>Köln</strong>, 19. - 22. September<br />

Lutz Mattner, Frauke Mattner<br />

<strong>Universität</strong> Trier, Kliniken <strong>der</strong> Stadt <strong>Köln</strong><br />

On the statistical comparison of diagnostic tests using joint test results<br />

We consi<strong>der</strong> the common problem of estimating or comparing sensitivities or specificities of (dichotomous)<br />

diagnostic tests, with the available data consisting of joint test results from the whole population, without<br />

true state determinations. Assuming the plausible latent class model of Gart and Buck (1966), it is well<br />

known that interesting inferences are possible only un<strong>der</strong> not always plausible additional assumptions,<br />

most notoriously the one of conditional independence of results of different tests given the true state,<br />

as discussed and criticized in, for example, the book of Pepe (2003). We suggest to impose additional<br />

assumptions only if they are plausible in a given application, even if this leads to nonidentifiability of the<br />

parameters of interest and hence to, say, only upper confidence bounds instead of two-sided confidence<br />

intervals.<br />

A detailed example in the talk will be the case of two diagnostic tests with the second at least as<br />

specific as the first. An application where this specificity assumption seems plausible is the comparison<br />

of two competing tests for diagnosing toxigenic Clostridium difficile from stool samples, applying an<br />

enzyme-immuno-assay either directly or after culturing (possibly nontoxigenic) Clostridium difficile. We<br />

<strong>der</strong>ive confidence bounds good enough to refute the direct test.<br />

The talk will be aimed at mathematicians without prior knowledge of diagnostic tests.<br />

Dietmar Pfeifer<br />

Karl von Ossietzky <strong>Universität</strong> Oldenburg<br />

Bernstein-Copulas: wie man den ’Fluch <strong>der</strong> Dimension’ umgeht<br />

Der Modellierung und Simulation von stochastischen Abhängigkeiten versicherungstechnischer Risiken<br />

kommt insbeson<strong>der</strong>e im Licht von Solvency II eine wachsende Bedeutung <strong>zu</strong>. Für die Konzeption<br />

und Implementierung interner Risikomodelle ist sie praktisch unverzichtbar. In dem Vortrag wird eine<br />

Möglichkeit auf <strong>der</strong> Basis von Bernstein- und an<strong>der</strong>en konstruktiven Copula-Ansätzen vorgestellt, die<br />

insbeson<strong>der</strong>e das Problem des ’Fluchs <strong>der</strong> Dimension’ umgehen. In dem Vortrag wird auch ein konkretes<br />

Anwendungsbeispiel vorgestellt.<br />

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