RDS.I.DS.estimates {RDS}R Documentation

RDS-I/DS Estimates

Description

This function computes the basic RDS-I/DS estimates for a categorical variable. This is the ``data smoothed'' version of RDS where it is assumed that the observed Markov process is reversible.

Usage

RDS.I.DS.estimates(rds.data, group.variable, network.variable)

Arguments

rds.data A data frame. This data frame must identify recruitment patters by a pair of fields named ``recruitment.id'' and ``recruiter.id''.
group.variable A categorical variable to be analyzed.
network.variable A string giving the name of the variable in the rds.data that contains the network sizes of survey respondents.

Value

A vector of proportion estimates constructed using the ``smoothed'' transition matrix.

Author(s)

W. Whipple Neely

References

Gile, K. J., Handcock, M. S., 2009b. Respondent-driven sampling: An assessment of current methodology. Under review, Nuffield College, University of Oxford.

Neely, W. W., 2009. Bayesian methods for data from respondent driven sampling. Dissertation in-progress, Department of Statistics, University of Wisconsin, Madison.

Salganik, M., Heckathorn, D. D., 2004. Sampling and estimation in hidden populations using respondent-driven sampling. Sociological Methodology 34, 193-239.

Volz, E., Heckathorn, D., 2008. Probability based estimation theory for Respondent Driven Sampling. The Journal of Official Statistics 24 (1), 79-97.

See Also

Examples

data(simulated)
RDS.I.DS.estimates(rds.data=simulated.data,group.variable='X',network.variable='network.size')

[Package RDS version 0.01 Index]