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Get MBNMA model values

get.model.vals.Rd

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

Usage

get.model.vals(
  mbnma,
  E0 = 0,
  level = "treatments",
  lim = "cred",
  link = "identity"
)

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").

Can take either "identity" (the default), "log" (for modelling Ratios of Means friedrich2011MBNMAtime) 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