R/eventglm-package.R

In sachsmc/eventglm: Regression Models for Event History Outcomes

#' Regression Models for Event History Outcomes
#'
#' A user friendly, easy to understand way of doing event history regression
#' for marginal estimands of interest, including the cumulative incidence and the
#' restricted mean survival, using the pseudo observation framework for estimation.
#' The interface uses the well known formulation of a generalized linear model and allows
#' for features including plotting of residuals, the use of sampling weights, and corrected
#' variance estimation.
#'
#' @docType package
#' @name eventglm
#' @references Sachs MC, Gabriel EE (2022). "Event History Regression with Pseudo-Observations: Computational Approaches and an Implementation in R." Journal of Statistical Software, 102(9), 1-34. <doi:10.18637/jss.v102.i09>
#' @useDynLib eventglm, .registration=TRUE
#' @importFrom stats coef model.frame model.matrix model.response .getXlevels model.offset model.weights naprint pnorm predict quasi residuals residuals.glm terms update as.formula update.formula reformulate vcov qnorm setNames coefficients
NULL

#' @importFrom survival Surv
#' @export
survival::Surv