# Get MBNMA model values

`get.model.vals.Rd`

Extracts specific information required for prediction from a time-course MBNMA model

## Arguments

- mbnma
An S3 object of class

`"mbnma"`

generated by running a time-course MBNMA model- E0
An object to indicate the value(s) to use for the response at time = 0 in the prediction. This can take a number of different formats depending on how it will be used/calculated. The default is 0 but this may lead to non-sensical predictions if Ratio of Means are modeled.

`numeric()`

A single numeric value representing the deterministic response at time = 0`formula()`

A formula representing a stochastic distribution for the response at time = 0. This is specified as a random number generator (RNG) given as a string, and can take any RNG distribution for which a function exists in R. For example:`~rnorm(n, 7, 0.5)`

.

- level
Can take either

`"treatment"`

to make predictions for treatments, or`"class"`

to make predictions for classes (in which case`object`

must be a class effect model).- lim
Specifies calculation of either 95% credible intervals (

`lim="cred"`

) or 95% prediction intervals (`lim="pred"`

).- link
Can take either

`"identity"`

(the default),`"log"`

(for modelling Ratios of Means (Friedrich et al. 2011) ) or`"smd"`

(for modelling Standardised Mean Differences - although this also corresponds to an identity link function).

## Value

A list containing named elements that correspond to different
time-course parameters in `mbnma`

. These elements contain MCMC results
either taken directly from `mbnma`

or (in the case of random time-course
parameters specified as `method="random"`

) randomly
generated using parameter values estimated in `mbnma`

.

Additional elements contain the following values:

`timecourse`

A character object that specifies the time-course used in`mbnma`

in terms of alpha, beta, mu, d and time. Consistency relative time-course parameters are specified in terms of mu and d.`time.params`

A character vector that indicates the different time-course parameters that are required for the prediction

@noRd