scoresurv: Calculate the log CATE score given the baseline covariates...

In precmed: Precision Medicine

Calculate the log CATE score given the baseline covariates and follow-up time for specified scoring method methods for survival outcomes

Description

Based on intxsurv results of the CATE coefficients estimated with random forest, boosting, naive Poisson, two regression, contrast regression

Usage

scoresurv(
  fit,
  x.cate,
  tau0,
  score.method = c("randomForest", "boosting", "poisson", "twoReg", "contrastReg")
)

Arguments

fit	List of objects generated from intxsurv: outputs of random forest, boosting, naive Poisson, two regression, contrast regression
x.cate	Matrix of p.cate baseline covariates specified in the outcome model; dimension n by p.cate.
tau0	The truncation time for defining restricted mean time lost.
score.method	A vector of one or multiple methods to estimate the CATE score. Allowed values are: 'randomForest', 'boosting', 'poisson', 'twoReg', 'contrastReg'. Default specifies all 5 methods.

Value

score.randomForest: Estimated log CATE score for all n observations with the random forest method; vector of size n score.boosting: Estimated log CATE score for all n observations with the boosting method; vector of size n score.poisson: Estimated log CATE score for all n observations with the naive Poisson method; vector of size n score.twoReg: Estimated log CATE score for all n observations with the two regression method; vector of size n score.contrastReg: Estimated log CATE score for all n observations with the contrast regression method; vector of size n score = NA if the corresponding method is not called

precmed documentation built on Oct. 6, 2024, 1:07 a.m.