<b>mexhaz</b>: An <i>R</i> Package for Fitting Flexible Hazard-Based Regression Models for Overall and Excess Mortality with a Random Effect

We present mexhaz, an R package for fitting flexible hazard-based regression models with the possibility to add time-dependent effects of covariates and account a twolevel hierarchical structure in data through inclusion normally distributed random intercept (i.e., log-normally shared frailty). Moreover, mexhazbased can be fitted within excess hazard setting by allowing specification expected model. These are common use context analysis population-based cancer registry data. Follow-up time entered right-censored or counting process input style, latter delayed entries. The logarithm baseline flexibly modeled B-splines restricted cubic splines time. Parameters estimation is based on likelihood maximization: deriving contribution each observation cluster-specific conditional likelihood, Gauss-Legendre quadrature used calculate cumulative hazard; marginal likelihoods then obtained integrating over distribution, using adaptive Gauss-Hermite quadrature. Functions compute plot predicted (excess) (net) survival (possibly predictions case effect models) provided. illustrate different options mexhaz compare results those other available packages.