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Evaluating the effect of optimized cutoff values in the assessment of prognostic factors

Lausen, B and Schumacher, M (1996) 'Evaluating the effect of optimized cutoff values in the assessment of prognostic factors.' Computational Statistics & Data Analysis, 21 (3). pp. 307-326. ISSN 0167-9473

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In clinical research the assessment of prognostic factors is often based on the division of the patients into two groups: a high risk and a low risk group. A common strategy is to select an optimal cutoff value in the prognostic factor which defines the two groups. The effect is measured as difference between the groups. We provide simple correction formulae for the correct P-value of the selected two-sample statistic. Moreover, we discuss consequences of that optimization on both the estimator of the cutoff point and the estimated effect. An approximate confidence region for both parameters is given. The small sample behaviour is analysed by means of a Monte-Carlo study. The optimization of the cutoff value results in an overestimation of the difference between the prognostic groups. Extensions of our discussion to censored data are given, too. Finally, we apply our approach to an example from oncology.

Item Type: Article
Uncontrolled Keywords: Assessment of prognostic factors; Censored data; Maximally selected test statistics; Optimization of cutoff values
Subjects: H Social Sciences > HA Statistics
Divisions: Faculty of Science and Health
Faculty of Science and Health > Mathematical Sciences, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 04 Jul 2012 12:16
Last Modified: 06 Jan 2022 13:24

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