exp_links {phylosamp}

Calculate expected number of links in a sample

Description

This function calculates the expected number of observed pairs in the sample that are linked by the linkage criteria. The function requires the sensitivity \eta and specificity \chi of the linkage criteria, and sample size M. Assumptions about transmission and linkage (single or multiple) can be specified.

Usage

exp_links(eta, chi, rho, M, R = NULL, assumption = "mtml")

Arguments

eta

scalar or vector giving the sensitivity of the linkage criteria

chi

scalar or vector giving the specificity of the linkage criteria

rho

scalar or vector giving the proportion of the final outbreak size that is sampled

M

scalar or vector giving the number of cases sampled

R

scalar or vector giving the effective reproductive number of the pathogen (default=NULL)

assumption

a character vector indicating which assumptions about transmission and linkage criteria. Default = 'mtml'. Accepted arguments are:

1. 'stsl' for the single-transmission single-linkage assumption (prob_trans_stsl()).

2. 'mtsl' for the multiple-transmission single-linkage assumption (prob_trans_mtsl()).

3. 'mtml' for the multiple-transmission multiple-linkage assumption (prob_trans_mtml()).

Value

scalar or vector giving the expected number of observed links in the sample

Author(s)

John Giles, Shirlee Wohl, and Justin Lessler

See Also

Other obs_pairs: obs_pairs_mtml(), obs_pairs_mtsl(), obs_pairs_stsl()

Examples

# The simplest case: single-transmission, single-linkage, and perfect sensitivity
exp_links(eta=1, chi=0.9, rho=0.5, M=100, assumption='stsl')

# Multiple-transmission and imperfect sensitivity
exp_links(eta=0.99, chi=0.9, rho=1, M=50, R=1, assumption='mtsl')

# Small outbreak, larger sampling proportion
exp_links(eta=0.99, chi=0.95, rho=1, M=50, R=1, assumption='mtml')

# Large outbreak, small sampling proportion
exp_links(eta=0.99, chi=0.95, rho=0.05, M=1000, R=1, assumption='mtml')