LogisticLogNormalSub-class | R Documentation |

This is the usual logistic regression model with a bivariate normal prior on the intercept and log slope.

The covariate is the dose *x* minus the reference dose *x^{*}*:

*logit[p(x)] = α + β \cdot (x - x^{*})*

where *p(x)* is the probability of observing a DLT for a given dose
*x*.

The prior is

*(α, \log(β)) \sim Normal(μ, Σ)*

The slots of this class contain the mean vector and the covariance matrix of the bivariate normal distribution, as well as the reference dose.

`mean`

the prior mean vector

*μ*`cov`

the prior covariance matrix

*Σ*`refDose`

the reference dose

*x^{*}*

model <- LogisticLogNormalSub(mean = c(-0.85, 1), cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2), refDose = 50)

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