The algorithm implemented in this package was designed to quickly estimates the distribution of the log-rank especially for heavy unbalanced groups. VALORATE estimates the null distribution and the p-value of the log-rank test based on a recent formulation. For a given number of alterations that define the size of survival groups, the estimation involves a weighted sum of distributions that are conditional on a co-occurrence term where mutations and events are both present. The estimation of conditional distributions is quite fast allowing the analysis of large datasets in few minutes <http://bioinformatica.mty.itesm.mx/valorate>.
|Author||Victor Trevino [aut, cre]|
|Date of publication||2016-10-09 23:23:03|
|Maintainer||Victor Trevino <firstname.lastname@example.org>|
|License||GPL (>= 2)|
New_Valorate: CREATE A VALORATE OBJECT
prepare.n1: ESTIMATES THE LOG-RANK DISTRIBUTION AND STORE IT WITHIN A...
valorate-internal: Internal VALORATE Functions
valorate.plot.empirical: PLOT THE SAMPLED (EMPIRICAL) LOG-RANK DISTRIBUTION
valorate.plot.kaplan: PLOT KAPLAN-MEIER CURVES
valorate.plot.sampling.densities: PLOT CO-OCCURRENCE DENSITIES FORMING A LOG-RANK DISTRIBUTION
valorate.plot.subpop: PLOT ALL ESTIMATED LOG-RANK DISTRIBUTIONS
valorate.p.value: ESTIMATES THE P-VALUE OF THE LOG-RANK TEST
valorate.risk: ESTIMATES RISK
valorate.survdiff: ESTIMATES THE P-VALUE AND STATISTICS OF THE LOG-RANK TEST