### check what happened to the patients who have a record of analysis initiation within SHARP but are pre-RRT both at screening and FFU
rm(list = ls())
# identify the patients
library(readstata13)
dfIncome <- read.dta13("L:\\SHARP analyses\\Income work\\dfIncome.dta")
alpha <- subset(dfIncome, initiate_dialysis == 1 & initiate_RRT == 0 & CKD_stage_screen != "RRT")
ids <- as.numeric(as.character(alpha$USUBJID))
alpha
subset(alpha, select = c("USUBJID", "reached_eGFR10", "reached_eGFR5"))
install.packages("mime")
install.packages("jsonlint")
install.packages("jsonlite")
?cat
obj <- 1
change_obj <- function(obj){
obj <- 2
}
change_obj(obj)
obj <- 1
change_obj <- function(obj){
obj <- 2
}
change_obj(obj)
change_obj(obj)
obj <- 1
change_obj <- function(obj){
obj <- 2
return(obj)
}
change_obj(obj)
obj
install.packages("shiny")
runExample("01_hello")
library(shiny)
runExample("01_hello")
shiny::runApp('Shiny Model/Shiny tutorials/App-1')
shiny::runApp('Shiny Model/Shiny tutorials/App-1')
shiny::runApp('Shiny Model/Shiny tutorials/App-1')
load("L:/SHARP analyses/Decision analytic model/Uncertainty analysis/PSA/output/lifetime_CE/none_UK/dfOutput, compl = 0, sim 2.Rdata")
View(dfOutput)
View(dfOutput)
shiny::runApp('Shiny Model/Previous work/2015 post-Oliver updates')
alpha <- get(load("L:\\SHARP analyses\\Decision analytic model\\Uncertainty analysis\\PSA\\output\\Model manuscript\\main_UK\\dfOutput, compliance = 0 sim 1.Rdata"))
head(alpha)
shiny::runApp('Shiny Model/code')
shiny::runApp('Shiny Model/code')
shiny::runApp('Shiny Model/code')
shiny::runApp('Shiny Model/code')
shiny::runApp('Shiny Model/code')
shiny::runApp('Shiny Model/code')
shiny::runApp('Shiny Model/code')
shiny::runApp('Shiny Model/code')
