likelihood_logit: likelihood_logit function

Description Usage Arguments Value

Description

This function computes the likelihood for the empirical bayesian model. It uses the logit transformation to estimate p (simpler)

Usage

1
likelihood_logit(param, Z)

Arguments

param

is a vector of length L+2, where the L first vectors are sigma (the standard deviations for each of the different type1 studies), q=logit(p)=param[L+1], where p is the probability that theta is 0 (trans(q)=p) and tau=param[L+2], the sd of theta.

Z

a vector of z values (see bayesian_modules)

Value

the value of the likelihood


azolling/EBmodules documentation built on May 11, 2019, 5:17 p.m.