PMC:4572492 / 5743-6394 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/4572492","sourcedb":"PMC","sourceid":"4572492","source_url":"https://www.ncbi.nlm.nih.gov/pmc/4572492","text":"Cao et al.17 considered a joint test of mean and variance differences by using a full likelihood approach based on linear regression models. The likelihood ratio test (LRT) statistic follows an asymptotic chi-square distribution under the null hypothesis. The LRT approach can increase power but is more sensitive to model assumptions such as normality. Therefore, Cao et al.17 proposed a parametric bootstrap method to calculate “honest” p values at the cost of computational efficiency. For both the LRT and distribution methods, implementation difficulties arise for multivariate (e.g., gene-based, gene-set, and pathway) analyses (see Appendix A).","tracks":[{"project":"2_test","denotations":[{"id":"26140448-24482837-2053686","span":{"begin":10,"end":12},"obj":"24482837"},{"id":"26140448-24482837-2053687","span":{"begin":375,"end":377},"obj":"24482837"}],"attributes":[{"subj":"26140448-24482837-2053686","pred":"source","obj":"2_test"},{"subj":"26140448-24482837-2053687","pred":"source","obj":"2_test"}]}],"config":{"attribute types":[{"pred":"source","value type":"selection","values":[{"id":"2_test","color":"#ec9393","default":true}]}]}}