Description Usage Arguments Value
This function computes the likelihood for the empirical bayesian model. It uses the logit transformation to estimate p (simpler)
1 | likelihood_logit(param, Z)
|
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) |
the value of the likelihood
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