rdssampleC {RDS}

Create RDS samples with given characteristics

Description

Create RDS samples with given characteristics

Usage

rdssampleC(
  net,
  nnodes = network.size(net),
  nsamp0,
  fixinitial,
  nsamp,
  replace,
  coupons,
  select = NULL,
  bias = NULL,
  rds.samp = NULL,
  seed.distribution = NULL,
  attrall = FALSE,
  trait.variable = "disease",
  nsims = 1,
  seeds = NULL,
  prob.network.recall = 1,
  verbose = TRUE
)

Arguments

net

the network object from which to draw a sample

nnodes

the number of nodes in the network [at least as default]

nsamp0

the number of seeds to be drawn (i.e. the size of the 0th wave of sampling)

fixinitial

a variable that indicates the distribution from which to draw the initial seeds, if the seeds variable is NULL and the seed.distribution variable is NULL

nsamp

number of individuals in each RDS sample

replace

sampling with replacement

coupons

number of coupons

select

not used

bias

not used

rds.samp

not used

seed.distribution

a variable [what kind?] that indicates the distribution from which to draw the initial seeds

attrall

Whether all the information about the sample should be returned [??]

trait.variable

attribute of interest

nsims

number of RDS samples to draw

seeds

an array of seeds. Default is NULL, in which case the function draws the seeds from the nodes of the network.

prob.network.recall

simulates the probability that an individual will remember any particular link

verbose

Print verbose output

Value

A list with the following elements: nsample: vector of indices of sampled nodes wsample: vector of waves of each sampled node degsample: vector of degrees of sampled nodes attrsample: vector of attrs of sampled nodes toattr: vector of numbers of referrals to attrsd nodes tonoattr: vector of number of referrans to unattrsd nominators: recruiter of each sample