Robustification of Linear Regression and Its Application in Genome-Wide Association Studies.

ABSTRACT: Regression analysis is one of the most popular statistical techniques that attempt to explore the relationships between a response (dependent) variable and one or more explanatory (independent) variables. To test the overall significance of regression, F-statistic is used if the parameters are estimated by the least-squares estimators (LSEs), while if the parameters are estimated by the maximum likelihood estimators (MLEs), the likelihood ratio test (LRT) statistic is used. However, both procedures produce misleading results and often fail to provide good fits to the reasonable space of the dataset in the presence of outlying observations. Moreover, outliers occur very frequently in any real datasets as well as in the molecular OMICS datasets. Hence, an effort is made in this study to robu

SUBMITTER: Alamin M 

PROVIDER: S-EPMC7295010 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature