BBS_mortality: Estimate Probability of Mortality Among Key Population...
In sgutreuter/SGmisc: Miscellaneous R Convenience Functions

BBS_mortality

R Documentation

Estimate Probability of Mortality Among Key Population Members

Description

BBS_mortality computes estimates of the probability of death over some time interval (determined by the survey questions) among members of key populations using information about contacts collected as part of Bio-Behavioral Surveillance Surveys. Estimation includes bootstrap confidence intervals.

Usage

BBS_mortality(
  .data,
  n_know = NULL,
  n_lost = NULL,
  n_died = NULL,
  degree = NULL,
  recall_max = 100,
  R = 2000L,
  conf = 0.95,
  ci_type = c("bca", "perc", "basic")
)

Arguments

`.data`	a dataframe containing the four variables.
`n_know`	a character string naming the variable containing the number of contacts known by the subject and who know the subject within the past time interval.
`n_lost`	a character string naming the variable containing the subset of `n_know` for whom the subject lost contact during the past time interval.
`n_died`	a character string naming the variable containing the subset of `n_know` who were known by the subject to have died, by any cause, during the past time interval.
`degree`	a character string naming the variable containing the network degree of the subject.
`recall_max`	the maximum contact count that is deemed plausible. Default: 100.
`R`	an integer-valued count of the number of bootstrap replicates desired for estimation of confidence limits. Default: 2000.
`conf`	the desired confidence level. Default: 0.95.
`ci_type`	a character string naming the type of bootstrap confidence interval desired; one of `⁠'bca'⁠` (default), `⁠'perc'⁠` or `⁠'basic'⁠`. See `boot.ci`.

Details

BBS_mortality eliminates records for which n_know < n_lost + n_died and any observations containing missing values for those variables are also removed.