Article ; Online: High-dimensional prediction of binary outcomes in the presence of between-study heterogeneity.
Statistical methods in medical research
2018 Volume 28, Issue 9, Page(s) 2848–2867
Abstract: Many prediction methods have been proposed in the literature, but most of them ignore heterogeneity between populations. Either only data from a single study or population is available for model building and evaluation, or when data from multiple studies ...
Abstract | Many prediction methods have been proposed in the literature, but most of them ignore heterogeneity between populations. Either only data from a single study or population is available for model building and evaluation, or when data from multiple studies make up the training dataset, studies are pooled before model building. As a result, prediction models might perform less than expected when applied to new subjects from new study populations. We propose a linear method for building prediction models with high-dimensional data from multiple studies. Our method explicitly addresses between-population variability and tends to select predictors that are predictive in most of the study populations. We employ empirical Bayes estimators and hence avoid selection bias during the variable selection process. Simulation results demonstrate that the new method works better than other linear prediction methods that ignore the between-study variability. Our method is developed for classification into two groups. |
---|---|
MeSH term(s) | Bayes Theorem ; Computer Simulation ; Graft Rejection/genetics ; Humans ; Kidney Transplantation ; Linear Models ; Predictive Value of Tests ; Risk Factors |
Language | English |
Publishing date | 2018-07-27 |
Publishing country | England |
Document type | Journal Article ; Research Support, Non-U.S. Gov't |
ZDB-ID | 1136948-6 |
ISSN | 1477-0334 ; 0962-2802 |
ISSN (online) | 1477-0334 |
ISSN | 0962-2802 |
DOI | 10.1177/0962280218787544 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
More links
Kategorien
In stock of ZB MED Cologne/Königswinter
Zs.A 3564: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG) |
Order via subito
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.