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Multilocus association testing with penalized regression
| Content Provider | Scilit |
|---|---|
| Author | Basu, Saonli Pan, Wei Shen, Xiaotong Oetting, William S. |
| Copyright Year | 2011 |
| Description | Journal: Genetic epidemiology In multilocus association analysis, since some markers may not be associated with a trait, it seems attractive to use penalized regression with the capability of automatic variable selection. On the other hand, in spite of a rapidly growing body of literature on penalized regression, most focus on variable selection and outcome prediction, for which penalized methods are generally more effective than their nonpenalized counterparts. However, for statistical inference, i.e. hypothesis testing and interval estimation, it is less clear how penalized methods would perform, or even how to best apply them, largely due to lack of studies on this topic. In our motivating data for a cohort of kidney transplant recipients, it is of primary interest to assess whether a group of genetic variants are associated with a binary clinical outcome, acute rejection at 6 months. In this article, we study some technical issues and alternative implementations of hypothesis testing in Lasso penalized logistic regression, and compare their performance with each other and with several existing global tests, some of which are specifically designed as variance component tests for high-dimensional data. The most interesting, and perhaps surprising, conclusion of this study is that, for low to moderately high-dimensional data, statistical tests based on Lasso penalized regression are not necessarily more powerful than some existing global tests. In addition, in penalized regression, rather than building a test based on a single selected "best" model, combining multiple tests, each of which is built on a candidate model, might be more promising. |
| Related Links | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3350336/pdf |
| Ending Page | 765 |
| Page Count | 11 |
| Starting Page | 755 |
| ISSN | 07410395 |
| e-ISSN | 10982272 |
| DOI | 10.1002/gepi.20625 |
| Journal | Genetic epidemiology |
| Issue Number | 8 |
| Volume Number | 35 |
| Language | English |
| Publisher | Wiley-Blackwell |
| Publisher Date | 2011-09-15 |
| Access Restriction | Open |
| Subject Keyword | Journal: Genetic epidemiology Statistics and Probability Logistic Kernel Machine Regression Logistic Regression Random-effects Model Score Test Sum of Squared Score (ssu) Test |
| Content Type | Text |
| Resource Type | Article |
| Subject | Epidemiology Genetics (clinical) |
