compute.weights: Compute estimates of the sampling weights of the respondent's...

In RDS: Respondent-Driven Sampling

Compute estimates of the sampling weights of the respondent's observations based on various estimators

Description

Compute estimates of the sampling weights of the respondent's observations based on various estimators

Usage

compute.weights(
  rds.data,
  weight.type = c("Gile's SS", "RDS-I", "RDS-I (DS)", "RDS-II", "Arithmetic Mean", "HCG"),
  N = NULL,
  subset = NULL,
  control = control.rds.estimates(),
  outcome.variable = NULL,
  hcg.wave.fallback = FALSE,
  cont.breaks = 3,
  ...
)

Arguments

rds.data	An rds.data.frame that indicates recruitment patterns by a pair of attributes named “id” and “recruiter.id”.
weight.type	A string giving the type of estimator to use. The options are "Gile's SS", "RDS-I", "RDS-II", "RDS-I/DS", and "Arithemic Mean". It defaults to "Gile's SS".
N	An estimate of the number of members of the population being sampled. If NULL it is read as the population.size.mid attribute of the rds.data frame. If that is missing, the weights will sum to 1. Note that this parameter is required for Gile's SS.
subset	An optional criterion to subset rds.data by. It is an R expression which, when evaluated, subset the data. In plain English, it can be something like subset = seed > 0 to exclude seeds. It can also be the name of a logical vector of the same length of the outcome variable where TRUE means include it in the analysis. If NULL then no subsetting is done.
control	A list of control parameters for algorithm tuning. Constructed using control.rds.estimates.
outcome.variable	The name of the variable defining the groups. Required for the group-model weight types ("RDS-I", "RDS-I (DS)" and "HCG").
hcg.wave.fallback	Logical. Internal use: allows the HCG weights to fall back to recruitment-wave ordering when recruitment times are absent. Used by the bootstrap machinery; direct HCG weight computations require recruitment time unless small.fraction=TRUE.
cont.breaks	The number of groups a continuous outcome is discretized into for the group-model weight types.
...	Additional parameters passed to the individual weighting algorithms.

Value

A vector of weights for each of the respondents. It is of the same size as the number of rows in rds.data. Subjects with missing outcome values receive weight 0 for the group-model weight types; they are retained internally (as their own group) while the weights are fit, so that recruitment chains passing through them are preserved.

See Also

rds.I.weights, gile.ss.weights, vh.weights

RDS documentation built on Oct. 21, 2026, 1:06 a.m.