SimNPH (version 0.5.5)

wrap_all_in_trycatch: Wrappers around Analyse Functions

Description

Wrappers around Analyse Functions

Usage

wrap_all_in_trycatch(
  list_of_functions,
  error = function(e) {
     warning(e$message)
     NA
 }
)
wrap_all_in_preserve_seed(list_of_functions)

Value

a list of functions

Arguments

list_of_functions

the list of functions to be wrapped

error

the error function in the tryCatch call

Functions

• wrap_all_in_trycatch(): Wrap all functions in a list in tryCatch calls

• wrap_all_in_preserve_seed(): wrap all functions in withr::with_preserve_seed

Details

SimDesign redraws data if one analysis function fails. This is not only highly inefficient for large studies, but failure of a method is informative and might be of interest. Moreover redrawing of data might introduce bias if the failure of the method is not independent of the parameter value, which would be a strong assumption.

To avoid redrawing data, we can catch all errors the analysis methods could throw and return NA instead.

This is handled well by the summarise functions generated with create_summarise_function other summarise functions might throw errors when trying to rbind a data.frame to a scalar NA value. In this case add another error argument. For example \(e){NULL} could work in some cases, in other cases you'll have to give a function that returns a data.frame with the same columns as the analyse functions and only NA values.

Analysis functions might use random numbers. If simulations should be replicated this can interfere with the RNG state of other analysis functions. To avoid this you can wrap all analysis function in a withr::with_preserve_seed call, so that the RNG state is reset after each analysis function is called. This way adding, removing or changing one analysis function has no effect on the other analysis functions, even if the analysis functions use random numbers.

Examples

funs1 <- list(\(){stop("test")}, \(){1})
funs2 <- wrap_all_in_trycatch(funs1)
try(lapply(funs1, \(f){f()}))
try(lapply(funs2, \(f){f()}))

funs1 <- list(\(){rnorm(1)})
funs2 <- list(\(){runif(1)}, \(){rnorm(1)})
funs3 <- funs2 |> wrap_all_in_preserve_seed()
set.seed(1)
lapply(funs1, \(f){f()})
set.seed(1)
lapply(funs2, \(f){f()})
set.seed(1)
lapply(funs3, \(f){f()})