## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval = FALSE ) ## ----setup-------------------------------------------------------------------- # library(SEQTaRget) ## ----------------------------------------------------------------------------- # options <- SEQopts(# tells SEQuential to create Kaplan-Meier curves # km.curves = TRUE, # # tells SEQuential to bootstrap # bootstrap = TRUE, # # tells SEQuential to run bootstraps 5 times # bootstrap.nboot = 5) # # # use example data # data <- SEQdata # model <- SEQuential(data, id.col = "ID", # time.col = "time", # eligible.col = "eligible", # treatment.col = "tx_init", # outcome.col = "outcome", # time_varying.cols = c("N", "L", "P"), # fixed.cols = "sex", # method = "dose-response", # options = options) # # km_curve(model, plot.type = "risk") # retrieve risk plot # risk_data(model) # risk_comparison(model) ## ----------------------------------------------------------------------------- # options <- SEQopts(km.curves = TRUE, # bootstrap = TRUE, # bootstrap.nboot = 5, # # tells SEQuential to expect LTFU as the censoring column # cense = "LTFU", # # tells SEQuential to treat this column as the # # censoring eligibility column # cense.eligible = "eligible_cense") # # # use example data for LTFU # data <- SEQdata.LTFU # model <- SEQuential(data, id.col = "ID", # time.col = "time", # eligible.col = "eligible", # treatment.col = "tx_init", # outcome.col = "outcome", # time_varying.cols = c("N", "L", "P"), # fixed.cols = "sex", # method = "dose-response", # options = options) # # km_curve(model, plot.type = "risk") # risk_data(model) # risk_comparison(model) ## ----------------------------------------------------------------------------- # options <- SEQopts(km.curves = TRUE, # bootstrap = TRUE, # bootstrap.nboot = 5, # # Using LTFU as our competing event # compevent = "LTFU") # # data <- SEQdata.LTFU # model <- SEQuential(data, id.col = "ID", # time.col = "time", # eligible.col = "eligible", # treatment.col = "tx_init", # outcome.col = "outcome", # time_varying.cols = c("N", "L", "P"), # fixed.cols = "sex", # method = "dose-response", # options = options) # # km_curve(model, plot.type = "risk") # risk_data(model) # risk_comparison(model) ## ----------------------------------------------------------------------------- # options <- SEQopts(# km.curves must be set to FALSE to turn on hazard # # ratio creation # km.curves = FALSE, # # set hazard to TRUE for hazard ratio creation # hazard = TRUE, # bootstrap = TRUE, # bootstrap.nboot = 5, # compevent = "LTFU") # # data <- SEQdata.LTFU # model <- SEQuential(data, id.col = "ID", # time.col = "time", # eligible.col = "eligible", # treatment.col = "tx_init", # outcome.col = "outcome", # time_varying.cols = c("N", "L", "P"), # fixed.cols = "sex", # method = "dose-response", # options = options) # # # retrieve hazard ratios # hazard_ratio(model) ## ----------------------------------------------------------------------------- # options <- SEQopts(km.curves = TRUE, # bootstrap = TRUE, # bootstrap.nboot = 5, # compevent = "LTFU", # # define the subgroup # subgroup = "sex") # # data <- SEQdata.LTFU # model <- SEQuential(data, id.col = "ID", # time.col = "time", # eligible.col = "eligible", # treatment.col = "tx_init", # outcome.col = "outcome", # time_varying.cols = c("N", "L", "P"), # fixed.cols = "sex", # method = "dose-response", # options = options) # # km_curve(model, plot.type = "risk") # risk_data(model) # risk_comparison(model)