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Summary

The goal of the networkreporting package is to help people use network reporting methods.

In traditional survey methods, respondents report about themselves. In network report methods, survey respondents report about the people to whom they are socially connected. Thus, network reporting methods can be thought of a generalization of traditional surveys. Many existing methods rely on this kind of indirect reporting and are thus network reporting methods:

  • network scale-up method
  • sibling method
  • multiplicity sampling
  • network surivial method
  • generalized network scale-up method
  • confidant method
  • neighborhood method

Although many of the methods that rely on indirect reporting have been regarded as distinct in the past, there is great value in developing a unified statistical framework to deal with common problems that all of these methods share. This unified framework also enables us to develop new network reporting methods. This package will help you use both existing network reporting methods and any new network reporting methods that you develop.

For more information on network reporting methods see:

  • Feehan, Dennis (2015) "Network reporting methods", Ph.D. Dissertation. Office of Population Research, Princeton University.

The development of this software was supported by a grant from the National Institutes of Health (R01-HD075666).

Installing

You can install:

  • the latest released version from CRAN with

    install.packages("networkreporting")
  • the latest development version from github with

    install.packages("devtools")
    devtools::install_github("dfeehan/networkreporting")

Vignettes

The networkreporting package enables you to use several methods that many people currently think of as distinct. Here are some vignettes for how to use the package:

Issues

If you would like to suggest a feature or report a bug, please create an issue

Citation

If you use our package for your research, please cite it so that we can continue to develop it.

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Version

Install

install.packages('networkreporting')

Monthly Downloads

8

Version

0.1.1

License

MIT + file LICENSE

Maintainer

Dennis M Feehan

Last Published

December 5th, 2016

Functions in networkreporting (0.1.1)

df.to.kpvec

turn a dataframe into a known population vector
estimate.error

given an estimated subpopn size or prevalence and the correct value, produce some measurements of how close the esimate is
kp.degree.estimator

kp.degree.estimator (DEPRECATED)
killworth.se

killworth.se
example.knownpop.dat

Example known population data
example.survey

Example household survey data
gwsm.estimator

indirect estimator (generalized weight share method / gwsm)
kp.estimator_

Average personal network size estimates using known population method
add.kp

attach known populations to a dataframe
kp.individual.estimator

Individual personal network size estimates using the known population method
nsum.estimator

nsum.estimator
nsum.internal.validation

nsum.internal.validation
summation.estimator

summation.estimator
report.aggregator_

aggregate a reported quantity by groups
multiplicity.estimator

multiplicity.estimator
plot_meanties_truth

plot_meanties_truth
parse.total.popn.size

handle the total.popn.size argument in a uniform way across several functions
rdsII.estimator

rdsII.estimator
networkreporting

Network reporting estimators
network.survival.estimator_

network survival estimator
total.degree.estimator

total.degree
topcode.var

topcode a vector of numerical values
topcode.data

topcode a group of variables