View source: R/rds_bootstrap.r
rds.mc.boot.draws | R Documentation |
This algorithm picks a respondent from the survey to be a seed uniformly at random. it then generates a bootstrap draw by simulating the markov process forward for n steps, where n is the size of the draw required.
If you wish the bootstrap dataset to end up with
variables from the original dataset other than the
traits and degree, then you must specify this when
you construct dd
using the
'estimate.degree.distns
function.
rds.mc.boot.draws(chains, mm, dd, num.reps)
chains |
A list with the chains constructed from the survey
using |
mm |
The mixing model |
dd |
The degree distributions |
num.reps |
The number of bootstrap resamples we want |
See:
Salganik, Matthew J. "Variance estimation, design effects, and sample size calculations for respondent-driven sampling." Journal of Urban Health 83.1 (2006): 98-112.
A list of length num.reps
; each entry in
the list has one bootstrap-resampled dataset
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