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Multilocus association testing with penalized regression
2011
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
doi:10.1002/gepi.20625
pmid:21922539
pmcid:PMC3350336
fatcat:k4v7sknp2naajhf4itkgtcdlgm