Calculate optimal sample size for detecting differential transmission with imperfect specificity

Function to solve for optimal sample size when the specificity isn't 1

relR_samplesize_solve(
  R_a,
  R_b,
  p_a,
  N,
  alpha = 0.05,
  alternative = c("two_sided", "less", "greater"),
  power = 0.8,
  sensitivity = 1,
  specificity = 1,
  overdispersion = NULL,
  allow_impossible_m = FALSE
)

Arguments

R_a: Numeric (Positive). The assumed R among the group in the denominator of the ratio. Input value must be greater than 0.
R_b: Numeric (Positive). The assumed R among the group in the numerator of the ratio. Input value must be greater than 0.
p_a: Numeric. The proportion of the population in group a. Must be between 0 and 1.
N: Numeric (Positive). The size of the infected pool. Only one of rho or N should be specified.
alpha: Numeric. The desired alpha level. Default: 0.05
alternative: Character. Specifies the alternative hypothesis. Must be: two_sided (Default), less, or greater
power: Numeric. The desired power. Must be a value between 0 and 1. Default: 0.8.
sensitivity: Numeric. The sensitivity of the linkage criteria. Must be between 0 and 1. Default: 1.
specificity: Numeric. The specificity of the linkage criteria. Must be between 0 and 1. Default: 1.
overdispersion: Numeric (Positive). An overdispersion parameter, set if the assumed distribution of the number of edges is negative binomial. If NULL the assumed distribution is Poisson (equivalent to an overdispersion parameter of infinity) Default: NULL Note that this is equivalent to setting the overdispersion parameter to Inf.
allow_impossible_m: Logical. Indicates whether a value for m can be returned that is greater than the input N. Default: FALSE.

Value

The sample size