| fauxmadrona2 {sspse} | R Documentation |
A Pair of Simulated RDS Data Sets with no seed dependency
Description
This is a faux set used to illustrate how the estimators for multiple Respondent-Driven sampling surveys perform under different populations and RDS schemes.
Format
A list with the first element being an rds.data.frame of the first survey and the
second element being an rds.data.frame of the second survey.
Details
The population is based on fauxmadrona from the RDS package.
It is a population with N=1000 nodes from which two successive respondent-driven samples are drawn.
For the first survey, the sample size is 200 so
that there is a relatively small sample fraction (20%). There is homophily
on disease status (R=5) and there is differential activity by disease status
whereby the infected nodes have mean degree twice that of the uninfected
(w=1.8).
In the sampling, the seeds are chosen randomly from the full population, so there is no dependency induced by seed selection.
Each sample member is given 2 uniquely identified coupons to distribute to other members of the target population in their acquaintance. Further each respondent distributes their coupons completely at random from among those they are connected to.
For the second sample the sample size is 250. The second survey has an additional variable recapture
indicating if the respondent was also surveyed in the first survey.
Each survey is represented as an rds.data.frame and they are stored in a list with two elements.
Source
The original network is included in the RDS package as
fauxmadrona.network, a network object.
The RDS package
also includes a third respondent-driven sample from the network and is referred to as
fauxmadrona.
Use data(package="sspse") to get a full list
of datasets.
References
Gile, Krista J., Handcock, Mark S., 2010 Respondent-driven Sampling: An Assessment of Current Methodology, Sociological Methodology, 40, 285-327. doi:10.1111/j.1467-9531.2010.01223.x.
Kim, Brian J. and Handcock, Mark S. 2021 Population Size Estimation Using Multiple Respondent-Driven Sampling Surveys, Journal of Survey Statistics and Methodology, 9(1):94–120. doi:10.1093/jssam/smz055.