Transformation based on likelihood ratio

Adimari D To D Chiogna M. Letter to the editor: non-monotone transformation of biomarkers. Stat Methods Med Res in press.

Yang J Kuan P Li J. Non-monotone transformation of biomarkers to improve diagnostic and screening accuracy in a DNA methylation study with trichotomous phenotypes. Stat Methods Med Res in press.

Pepe MS. The statistical evaluation of medical tests for classification and prediction. Cambridge: Cambridge Press, 2003.

Newton M Kendziorski C Richmond C , et al. On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data. J Comput Biol 2001; 8: 37–52.

Church BV Williams HT Mar JC. Investigating skewness to understand gene expression heterogeneity in large patient cohorts. BMC Bioinformatics 2019; 20: 668.

Kalbfleish JD Prentice RL. The statistical analysis of failure time data. New York: John Wiley & Sons, Inc., 1980.

Li J Ma S. Survival analysis in medicine and genetics. Boca Raton: CRC Press, 2013.

Orlenko A Moore J Orzechowski P , et al. Considerations for automated machine learning in clinical metabolic profiling: altered homocysteine plasma concentration associated with metformin exposure. Pac Symp Biocomput 2018; 23: 460–471.

Wang T Li B Nelson CE , et al. Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data. BMC Bioinformatics 2019; 20: 40.

Jin H Lu Y. A procedure for determining whether a simple combination of diagnostic tests may be noninferior to the theoretical optimum combination. Med Decis Making 2008; 28: 909–916.

Lu Q Obuchowski N Won S , et al. Using the optimal robust receiver operating characteristic (ROC) curve for predictive genetic tests. Biometrics 2010; 66: 586–593.