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(),
  ...
)

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.
...	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.

See Also

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

RDS documentation built on Sept. 11, 2024, 8:13 p.m.