Cross-validated stepwise regression for identification of novel non-nucleoside reverse transcriptase inhibitor resistance associated mutations

Table 4 3F model selection on genotype-phenotype data up to September 2006

^aThe number of 3F models generated was arbitrary but taken large enough such that at least one 3F model was found with a lower SBC or AIC than the reference on the genotype-phenotype data set up to July 2006.
^bFrom the remaining 3F models with lower SBC or AIC than the reference, the 3F model was then selected with the lowest average squared error (ase) on an unseen genotype-phenotype data set collected between July and September 2006 (test set) containing approximately 800 samples.
^cSBC of the selected 3F model < SBC reference on the test set (yes/no).
^dAIC of the selected 3F model < AIC reference on the test set (yes/no).
^eThe number of different random divisions used in the stepwise regression in the selected 3F model.
^fFor the nucleoside RT inhibitors the number of random divisions needed was less than 100, with exception of AZT and TDF.
^gFor the non-nucleoside RT inhibitors most random divisions were needed for ETR.
^hATV was the only drug for which more than 1000 different random divisions were needed.

ISSN: 1471-2105