WebWe will perform a competing risk analysis on data from 177 patients who received a stem cell transplant for acute leukemia. The event of interest in relapse, but other competing causes (e.g. transplant-related death) need to be taken into account. We also want to take into account the effect of several covariates such as Sex, Disease ... WebMiettinen and Hanley (2009) explained how case-base sampling can be used to estimate smooth-in-time parametric hazard functions. The idea is to sample person-moments, …
Introduction to casebase sampling
WebDescription. Visualize estimated hazard curves as a function of time with confidence intervals. This function takes as input, the result from the fitSmoothHazard () function. … WebMar 14, 2024 · casebase. casebase is an R package for fitting flexible and fully parametric hazard regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression. Our formulation allows for arbitrary functional forms of time and its interactions with other predictors for time-dependent hazards and … chinese medicine for stress and anxiety
GitHub - sahirbhatnagar/casebase
WebNov 9, 2024 · Using the output of the function fitSmoothHazard, we can compute absolute risks by integrating the fitted hazard function over a time period and then converting this … WebThe casebase package uses the following hierarchy of classes for the output of fitSmoothHazard: casebase: singleEventCB: - glm - gam - cv.glmnet CompRisk: - vglm. The class singleEventCB is an S3 class, and we also keep track of the classes appearing below. The class CompRisk is an S4 class that inherits from vglm. Credit WebNov 16, 2024 · absoluteRisk: Compute absolute risks using the fitted hazard function. bmtcrr: Data on transplant patients brcancer: German Breast Cancer Study Group 2 checkArgsEventIndicator: Check that Event is in Correct Format CompRisk-class: An S4 class to store the output of fitSmoothHazard confint.absRiskCB: Compute confidence … grand peterhof palace