McCarty: McCarty Dataset

In NSUM: Network Scale Up Method

Description

This dataset contains the subpopulation sizes and parameters used for simulations involving the McCarty data.

Usage

data("McCarty")

Format

A list with the following 7 variables.

known

a vector of positive numbers, the sizes of known subpopulations.

unknown

a vector of positive numbers, the sizes of unknown subpopulations.

N

a positive number, the (known) total population size.

mu

a real number, the location parameter for the log-normal distribution of network degrees, with default 5.

sigma

a positive number, the scale parameter for the log-normal distribution of network degrees, with default 1.

rho

a vector of numbers between 0 and 1 with length equal to the total number of subpopulations, known and unknown, the dispersion parameters for the barrier effects, with defaults 0.1.

tauK

a vector of numbers between 0 and 1 with length equal to the total number of unknown subpopulations, the multipliers for the transmission biases, with defaults 1.

Details

The McCarty data set was obtained through random digit dialing within the United States. It contains responses from 1,375 adults from two surveys: survey 1 with 801 responses conducted in January 1998 and survey 2 with 574 responses conducted in January 1999.

Source

Killworth, P., Johnsen, E., McCarty, C., Shelley, G., and Bernard, H. (1998a), "A Social Network Approach to Estimating Seroprevalence in the United States," Social Networks, 20, 23-50.

Killworth, P., McCarty, C., Bernard, H., Shelley, G., and Johnsen, E. (1998b), "Estimation of Seroprevalence, Rape, and Homelessness in the United States using a Social Network Approach," Evaluation Review, 22, 289-308.

Examples

## load data
data(McCarty)

## simulate from model with barrier effects
sim.bar <- with(McCarty, nsum.simulate(100, known, unknown, N, model="barrier", 
                                       mu, sigma, rho))

NSUM documentation built on May 2, 2019, 9:28 a.m.