getTmleDiagnostics() returns the empirical efficient influence curve (EIC)
convergence diagnostics stored on a fitted "ConcreteEst" object. Use
type = "components" to inspect the final component-wise stopping criteria,
type = "trace" to inspect the update history, or type = "norm" to inspect
the norm of the empirical mean EIC across update steps.
Usage
getTmleDiagnostics(ConcreteEst, type = c("components", "trace", "norm"))Arguments
- ConcreteEst
"ConcreteEst"object returned bydoConcrete().- type
character; one of
"components","trace", or"norm".
Examples
library(data.table)
library(concrete)
data <- as.data.table(survival::pbc)
data <- data[1:200, .SD, .SDcols = c("id", "time", "status", "trt", "age", "sex")]
data[, trt := sample(0:1, nrow(data), TRUE)]
#> id time status trt age sex
#> <int> <int> <int> <int> <num> <fctr>
#> 1: 1 400 2 1 58.76523 f
#> 2: 2 4500 0 1 56.44627 f
#> 3: 3 1012 2 1 70.07255 m
#> 4: 4 1925 2 1 54.74059 f
#> 5: 5 1504 1 1 38.10541 f
#> ---
#> 196: 196 2363 0 1 57.04038 f
#> 197: 197 2365 0 1 44.62697 f
#> 198: 198 2357 0 1 35.79740 f
#> 199: 199 1592 0 0 40.71732 f
#> 200: 200 2318 0 0 32.23272 f
concrete.args <- formatArguments(DataTable = data,
EventTime = "time",
EventType = "status",
Treatment = "trt",
ID = "id",
TargetTime = 2500,
TargetEvent = c(1, 2),
Intervention = makeITT(),
CVArg = list(V = 2),
MaxUpdateIter = 2,
Verbose = FALSE)
# \donttest{
concrete.est <- doConcrete(concrete.args)
#>
#> Estimating Treatment Propensity:
#>
#> Estimating Hazards:
#> Warning: Loglik converged before variable 1 ; coefficient may be infinite.
#> Warning: Loglik converged before variable 1,3 ; coefficient may be infinite.
#>
#> Starting TMLE Update:
#> Warning: TMLE has not converged by step 2 - Estimates may not have the desired asymptotic properties
getTmleDiagnostics(concrete.est, type = "components")
#> Intervention Time Event PnEIC RelativeCriteria AbsPnEIC
#> <char> <num> <num> <num> <num> <num>
#> 1: A=1 2500 1 -0.0007305945 0.003403878 0.0007305945
#> 2: A=1 2500 2 -0.0012659479 0.008296913 0.0012659479
#> 3: A=0 2500 1 0.0032918781 0.003184190 0.0032918781
#> 4: A=0 2500 2 0.0063725185 0.009231490 0.0063725185
#> AbsoluteCriteria StopCriteria RelativeRatio AbsoluteRatio ratio check
#> <num> <num> <num> <num> <num> <lgcl>
#> 1: 0 0.003403878 0.2146359 Inf 0.2146359 TRUE
#> 2: 0 0.008296913 0.1525806 Inf 0.1525806 TRUE
#> 3: 0 0.003184190 1.0338198 Inf 1.0338198 FALSE
#> 4: 0 0.009231490 0.6903023 Inf 0.6903023 TRUE
#> StopRule StopAbsTol Converged ConvergenceStep
#> <char> <num> <lgcl> <num>
#> 1: relative 0 FALSE 3
#> 2: relative 0 FALSE 3
#> 3: relative 0 FALSE 3
#> 4: relative 0 FALSE 3
# }