Estimate death rates from sibling history data

Usage

sibling_estimator(
  sib.dat,
  ego.id,
  sib.id,
  sib.frame.indicator,
  sib.sex = "sex",
  cell.config,
  weights,
  boot.weights = NULL,
  return.boot = FALSE,
  discretize.exp = FALSE
)

Arguments

sib.dat: The long-form sibling history dataset (likely produced by prep_dhs_sib_histories)
ego.id: String with the name of the column of sib.dat that has the ID of the survey respondent
sib.id: String with the name of the column of sib.dat that has the sibling ID
sib.frame.indicator: String with the name of the column in sib.dat containing a 0/1 coded variable indicating whether or not each sib is in the frame population
sib.sex: String with the name fo the column of sib.dat that has the sibling's sex
cell.config: An object containing the configuration of cells; see TODO for more information
weights: String with the name of the column of sib.dat that has the sampling weight
boot.weights: Optional dataframe with bootstrap resampled weights. See Details for more info.
return.boot: If TRUE, and if boot.weights is specified, then return each bootstrap estimate
discretize.exp: Boolean for whether or not expsoure should be discretized. Not yet implemented.

Value

a list with two entries: asdr.ind, individual visibility asdr estimates; and asdr.agg, aggregate visibility asdr estimates

Details

If you want estimated sampling variances, you can pass in a data frame boot.weights. boot.weights is assumed to have a column that is named whatever the ego.id is, and then a series of columns named boot_weight_1, ..., boot_weight_M.