nsum.estimator: nsum.estimator

In dfeehan/networkreporting: Tools for using Network Reporting Estimators

nsum.estimator

Description

compute network scale-up (nsum) estimate of the hidden population's size. if the degree ratio and information transmission rate are both 1 (the defaults), this is the Killworth estimator.

Usage

nsum.estimator(
  survey.data,
  d.hat.vals = "d",
  d.tot.hat = NULL,
  y.vals = "y",
  total.popn.size = NULL,
  deg.ratio = 1,
  tx.rate = 1,
  weights = NULL,
  killworth.se = FALSE,
  missing = "ignore",
  verbose = FALSE,
  ...
)

Arguments

survey.data	the dataframe with survey results
d.hat.vals	the name or index of the column that contains each respondent's estimated degree; note that if d.total.hat is specified, then this argument (d.hat.vals) is ignored
d.tot.hat	if not NULL, then the estimated total degree of the population (i.e., the average degree times the number of people); if NULL, then use d.hat.vals (see above)
y.vals	the name or index of the column that contains the count of hidden popn members known
total.popn.size	NULL, NA, or a size
deg.ratio	the degree ratio, \frac\bard_T\bard; defaults to 1
tx.rate	the information transmission rate; defaults to 1
weights	if not NULL, weights to use in computing the estimate. this should be the name of the column in the survey.data which has the variable with the appropriate weights. these weights should be construted so that, eg, the mean of the degrees is estimated as (1/n) * \sum_i w_i * d_i
killworth.se	if not NA, return the Killworth et al estimate of
missing	if "ignore", then proceed with the analysis without doing anything about missing values. if "complete.obs" then only use rows that have no missingness for the computations (listwise deletion). care must be taken in using this second option
verbose	if TRUE, print messages to the screen
...	extra parameters to pass on to the bootstrap fn, if applicable

Details

TODO – cite Killworth estimator, our methods paper TODO – add refs to deg ratio and tx rate stuff...

Value

the nsum estimate of the hidden population's size (as a prevalence or an absolute number, depending on total.popn.size)

dfeehan/networkreporting documentation built on May 17, 2023, 1:06 a.m.