bootstrap_incidence: Calculates bootstrap variability estimates

In fellstat/TestingHistoryIncidence: Estimate Incidence from Testing History

Description

Calculates bootstrap variability estimates

Usage

bootstrap_incidence(incidence, nrep = 1000, rep_weights = NULL,
  type = c("BRR", "Fay", "JK1", "JKn", "bootstrap", "other"),
  combined_weights = TRUE, show_progress = TRUE, ...)

Arguments

incidence	a test_inc object returned by testing_incidence.
nrep	The number of bootstrap replications (ignored if rep_weights is not null.
rep_weights	A dataframe of replicate weights.
type	The type of resampling weights. See svrepdesign.
combined_weights	TRUE if the rep_weights already include the sampling weights. This is usually the case.
show_progress	If TRUE, prints bootstrap progress. This may also be a callback function taking one parameter equal to the index of the current replicate.
...	additional parameters to svrepdesign.

Examples

  data(tstdat)
  tstdat$age <- rep(15:64, 200)


  inc <- with(tstdat, testing_incidence(report_pos, hiv,
                                        ever_test, last_test,
                                        biomarker_art=biomarker_art, low_viral=low_viral))

  # Simple random sample bootstrap with 5 replicates.
  bootstrap_incidence(inc,nrep=5, show_progress=FALSE)

fellstat/TestingHistoryIncidence documentation built on May 7, 2019, 7:41 a.m.