model_negbin_loglinear {beaver} | R Documentation |
Negative Binomial Log-Linear Dose Response
Description
Model settings for a negative binomial distribution assuming
a log-linear model on the mean. This function is to be used within a call
to beaver_mcmc()
.
Usage
model_negbin_loglinear(mu_b1, sigma_b1, mu_b2, sigma_b2, w_prior = 1)
Arguments
mu_b1 , sigma_b1 , mu_b2 , sigma_b2 |
hyperparameters. See the model description below for context. |
w_prior |
the prior weight for the model. |
Value
A list with the model's prior weight and hyperparameter values.
Negative Binomial Log-Linear
Let be the
th subject on dose
.
The model is
The model is parameterized in terms of the mean of the negative binomial distribution and the usual probability parameter p. The prior on the mean is a log-linear model, and the prior on p at each dose is Uniform(0, 1). The model can adjust for baseline covariates, (
).
See Also
Other models:
beaver_mcmc()
,
model_negbin_emax()
,
model_negbin_exp()
,
model_negbin_indep()
,
model_negbin_linear()
,
model_negbin_logquad()
,
model_negbin_quad()
,
model_negbin_sigmoid_emax()