get_prob: Compute sucess probabilities (tau_j's)

In pempi: Proportion Estimation with Marginal Proxy Information

Compute sucess probabilities (tau_j's)

Description

Compute joint probabilities of P(W = j, Y = k) for j, k = 0, 1.

Usage

get_prob(theta, pi0, alpha, beta, alpha0)

Arguments

theta	A numeric that provides the true prevalence of a given disease.
pi0	A numeric that provides the prevalence or proportion of people (in the whole population) who are positive, as measured through a non-random, but systematic sampling (e.g. based on medical selection).
alpha	A numeric that provides the False Negative (FN) rate for the sample R.
beta	A numeric that provides the False Positive (FP) rate for the sample R.
alpha0	A numeric that corresponds to the probability that a random participant has been incorrectly declared positive through the nontransparent procedure. In most applications, this probability is likely very close to zero.

Value

A vector containing tau1, tau2, tau3 and tau4.

Author(s)

Stephane Guerrier

Examples

prob1 = get_prob(theta = 0.02, pi0 = 0.01, alpha = 0, beta = 0, alpha0 = 0)
prob1
sum(prob1)

prob2 = get_prob(theta = 0.02, pi0 = 0.01, alpha = 0.001, beta = 0, alpha0 = 0.001)
prob2
sum(prob2)

pempi documentation built on Oct. 9, 2023, 5:10 p.m.