دورية أكاديمية
Flexible modeling of ratio outcomes in clinical and epidemiological research.
| العنوان: | Flexible modeling of ratio outcomes in clinical and epidemiological research. |
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| المؤلفون: | Berger M; Department of Medical Biometry, Informatics and Epidemiology, University of Bonn/University Hospital Bonn, Bonn, Germany., Schmid M; Department of Medical Biometry, Informatics and Epidemiology, University of Bonn/University Hospital Bonn, Bonn, Germany. |
| المصدر: | Statistical methods in medical research [Stat Methods Med Res] 2020 Aug; Vol. 29 (8), pp. 2250-2268. Date of Electronic Publication: 2019 Dec 09. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: SAGE Publications Country of Publication: England NLM ID: 9212457 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1477-0334 (Electronic) Linking ISSN: 09622802 NLM ISO Abbreviation: Stat Methods Med Res Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: London : SAGE Publications Original Publication: Sevenoaks, Kent, UK : Edward Arnold, c1992- |
| مواضيع طبية MeSH: | Normal Distribution*, Epidemiologic Studies ; Risk Factors |
| مستخلص: | In medical studies one frequently encounters ratio outcomes. For modeling these right-skewed positive variables, two approaches are in common use. The first one assumes that the outcome follows a normal distribution after transformation (e.g. a log-normal distribution), and the second one assumes gamma distributed outcome values. Classical regression approaches relate the mean ratio to a set of explanatory variables and treat the other parameters of the underlying distribution as nuisance parameters. Here, more flexible extensions for modeling ratio outcomes are proposed that allow to relate all the distribution parameters to explanatory variables. The models are embedded into the framework of generalized additive models for location, scale and shape (GAMLSS), and can be fitted using a component-wise gradient boosting algorithm. The added value of the new modeling approach is demonstrated by the analysis of the LDL/HDL cholesterol ratio, which is a strong predictor of cardiovascular events, using data from the German Chronic Kidney Disease Study. Particularly, our results confirm various important findings on risk factors for cardiovascular events. |
| فهرسة مساهمة: | Keywords: Box–Cox transformation; GAMLSS; Ratio outcomes; generalized beta distribution of the second kind; gradient boosting; log-normal distribution |
| تواريخ الأحداث: | Date Created: 20191210 Date Completed: 20210728 Latest Revision: 20210728 |
| رمز التحديث: | 20231215 |
| DOI: | 10.1177/0962280219891195 |
| PMID: | 31813336 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1477-0334 |
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| DOI: | 10.1177/0962280219891195 |