Service/Object multiplier estimator

get_study_est_multiplier(
  data,
  service_var = "service_use",
  total_service = sum(data$service_use[data$hidden == 1]),
  seed_condition = "rds_from == -999",
  n_boot = 100,
  parallel_boot = FALSE,
  prefix = "rds",
  label = "multiplier"
)

Arguments

data: pass-through population data frame
service_var: name of variable that indicates service/object use by respondent
total_service: numeric value that indicates number of hidden population members who used the service. Defaults to truth from simulated dataset
seed_condition: character string containing condition to define seeds. Defaults to "rds_from == -999" that applies to simulated RDS samples
n_boot: number of bootstrap resamples
parallel_boot: logical, whether to compute bootstrap samples in parallel using foreach package
prefix: character prefix used for RDS sample variables
label: character string describing the estimator

Value

Data frame of service/object multiplier population size estimates for single study

Details

Function currently requires variable "hidden_visible_out" to be present in the data supplied and represent the hidden population out-report

References

Salganik, Matthew J. "Variance estimation, design effects, and sample size calculations for respondent-driven sampling." Journal of Urban Health 83, no. 1 (2006): 98. https://doi.org/10.1007/s11524-006-9106-x