WebJun 6, 2016 · ‘could not find function’ Error This error arises when an R package is not loaded properly or due to misspelling of the functions. As you can see in the screenshot below, when we run the code, we get a could not find function “ymd” error in the console. This is because we have not loaded the package “lubridate” to which the ymd function … WebOct 16, 2024 · #main program library (shiny) library (rms) library (ggplot2) shinyApp ( ui = fluidPage ( titlePanel ("RCS plot"), sidebarLayout ( sidebarPanel ( fileInput ("file", "Choose CSV File", multiple = TRUE, accept = c ("text/csv")) ), mainPanel ( plotOutput ("Plot_RCS") ) ) ), server = shinyServer (function (input,output,session) { base<-reactive ( { …
survival analysis - Calibrate with cph function (with external ...
Webtfun <- function (tform) coxph (tform, data=lung) fit <- tfun (Surv (time, status) ~ age) predict (fit) In such a case add the model=TRUE option to the coxph call to obviate the need for … WebJul 27, 2024 · R "Could not find function <-<-" but I did not use that function What I entered in the console (alp, DF1, DF2 are defined): What I got: The answer I am looking for is 2.22, which I get when the Lower Tail is d ... marta testing hours
cph : Cox Proportional Hazards Model and Extensions
WebAug 14, 2015 · I am doing a time dependent Cox model using cph function in rms package. I use Predict and plot.Predict to plot the hazard ratio on y axis and a continuous covariate (e.g. LDL cholesterol) on X axis for 3 levels of a treatment. I get 3 curves for 3 treatment across the range of my continous covariate LDL. I use the R code below: Web2 days ago · Both the CPH with treatment (CPH-T) and RSF with treatment (RSF-T) models better discriminated between lower-risk and higher-risk candidates compared with the 6-status system (CPH-T: cH = 0.76 [95% CI: 0.72-0.79]; P < 0.001; RSF-T: cH = 0.74 [95% CI: 0.70-0.78]; P = 0.011) ( Table 2 ). WebSep 5, 2024 · Iterating over multiple elements in R is bad for performance. Moreover, foreach is only combining results 100 by 100, which also slows computations. If there are too many elements to loop over, the best is to split the computation in ncores blocks and to perform some optimized sequential work on each block. In package {bigstatsr}, I use the … marta train from atlanta airport