impute.degree: Imputes missing degree values

In RDS: Respondent-Driven Sampling

Imputes missing degree values

Description

Imputes missing degree values

Usage

impute.degree(
  rds.data,
  trait.variable = NULL,
  N = NULL,
  method = c("mean", "quantile"),
  quantile = 0.5,
  recruitment.lower.bound = TRUE,
  round.degree = TRUE
)

Arguments

rds.data	an rds.data.frame
trait.variable	the name of the variable in rds.data to stratify the imputation by
N	population size
method	If mean, the weighted mean value is imputed, otherwize a quantile is used.
quantile	If method is "quantile", this is the quantile that is used. Defaults to median
recruitment.lower.bound	If TRUE, then for each individual, the degree is taken to be the minimum of the number of recruits plus one, and the reported degree
round.degree	Should degrees be integer rounded.

Details

This function imputes degree values using the weighted mean or quantile values of the non-missing degrees. Weights are calcualted using Gile's SS if N is not NULL, or RDS-II if it is. If a trait variable is specified, means and quantile are calculated within the levels of the trait variable

Examples

data(faux)
rds.data <- faux
rds.data$network.size[c(1,2,30,52,81,101,108,111)] <- NA
impute.degree(rds.data)
impute.degree(rds.data,trait.variable="X")
impute.degree(rds.data,trait.variable="X",method="quantile")

RDS documentation built on Aug. 20, 2023, 9:06 a.m.