total.degree — total.degree.estimator • networkreporting

estimate the total degree of the population network from sample degrees

Usage

total.degree.estimator(
  survey.data,
  d.hat.vals = "d",
  weights = NULL,
  missing = "ignore"
)

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
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
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

Value

the estimated total degree

Details

this computes the weighted sum of the respondents' estimated degrees.
' TODO – for now, it doesn't worry about missing values OR about differences between the frame and the universe