https://scholars.lib.ntu.edu.tw/handle/123456789/521725
標題: | A permutation method to assess heterogeneity in external validation for risk prediction models | 作者: | Wang L.-Y. WEN-CHUNG LEE |
公開日期: | 2015 | 出版社: | Public Library of Science | 卷: | 10 | 期: | 1 | 來源出版物: | PLoS ONE | 摘要: | The value of a developed prediction model depends on its performance outside the development sample. The key is therefore to externally validate the model on a different but related independent data. In this study, we propose a permutation method to assess heterogeneity in external validation for risk prediction models. The permutation p value measures the extent of homology between development and validation datasets. If p < 0.05, the model may not be directly transported to the external validation population without further revision or updating. Monte-Carlo simulations are conducted to evaluate the statistical properties of the proposed method, and two microarray breast cancer datasets are analyzed for demonstration. The permutation method is easy to implement and is recommended for routine use in external validation for risk prediction models. ? 2015 Wang Lee. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921793715&doi=10.1371%2fjournal.pone.0116957&partnerID=40&md5=25a04614ce32a355fffb5eb19698e62c https://scholars.lib.ntu.edu.tw/handle/123456789/521725 |
ISSN: | 1932-6203 | DOI: | 10.1371/journal.pone.0116957 | SDG/關鍵字: | area under the curve; Article; breast cancer; controlled study; female; gene expression; human; major clinical study; microarray analysis; Monte Carlo method; permutation method; prediction; reproducibility; support vector machine; Breast Neoplasms; DNA microarray; gene expression profiling; genetics; risk; statistical model; Breast Neoplasms; Female; Gene Expression Profiling; Humans; Models, Statistical; Monte Carlo Method; Oligonucleotide Array Sequence Analysis; Reproducibility of Results; Risk |
顯示於: | 流行病學與預防醫學研究所 |
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