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Status: Bibliographieeintrag

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Verfasst von:Jenkner, Carolin [VerfasserIn]   i
 Lorenz, Eva [VerfasserIn]   i
 Becher, Heiko [VerfasserIn]   i
 Sauerbrei, Wilhelm F. [VerfasserIn]   i
Titel:Modeling continuous covariates with a “spike” at zero
Titelzusatz:Bivariate approaches
Verf.angabe:Carolin Jenkner, Eva Lorenz, Heiko Becher, Willi Sauerbrei
E-Jahr:2016
Jahr:[2016]
Umfang:14 S.
Illustrationen:Diagramme
Fussnoten:Gesehen am 06.05.2020
Titel Quelle:Enthalten in: Biometrical journal
Ort Quelle:Berlin : Wiley-VCH, 1959
Jahr Quelle:2016
Band/Heft Quelle:58(2016), 4, Seite 783-796
ISSN Quelle:1521-4036
Abstract:In epidemiology and clinical research, predictors often take value zero for a large amount of observations while the distribution of the remaining observations is continuous. These predictors are called variables with a spike at zero. Examples include smoking or alcohol consumption. Recently, an extension of the fractional polynomial (FP) procedure, a technique for modeling nonlinear relationships, was proposed to deal with such situations. To indicate whether or not a value is zero, a binary variable is added to the model. In a two stage procedure, called FP-spike, the necessity of the binary variable and/or the continuous FP function for the positive part are assessed for a suitable fit. In univariate analyses, the FP-spike procedure usually leads to functional relationships that are easy to interpret. This paper introduces four approaches for dealing with two variables with a spike at zero (SAZ). The methods depend on the bivariate distribution of zero and nonzero values. Bi-Sep is the simplest of the four bivariate approaches. It uses the univariate FP-spike procedure separately for the two SAZ variables. In Bi-D3, Bi-D1, and Bi-Sub, proportions of zeros in both variables are considered simultaneously in the binary indicators. Therefore, these strategies can account for correlated variables. The methods can be used for arbitrary distributions of the covariates. For illustration and comparison of results, data from a case-control study on laryngeal cancer, with smoking and alcohol intake as two SAZ variables, is considered. In addition, a possible extension to three or more SAZ variables is outlined. A combination of log-linear models for the analysis of the correlation in combination with the bivariate approaches is proposed.
DOI:doi:10.1002/bimj.201400112
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: https://doi.org/10.1002/bimj.201400112
 Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/bimj.201400112
 DOI: https://doi.org/10.1002/bimj.201400112
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Correlated predictors
 Fractional polynomials
 Regression modeling
 Spike at zero
K10plus-PPN:1697274536
Verknüpfungen:→ Zeitschrift

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