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