TBFmultinomial (version 0.1.3)

model_priors: Prior model probability

Description

This function computes the prior model probabilities of the candidate models

Usage

model_priors(fullModel, discreteSurv = TRUE, modelPrior = "flat")

Arguments

fullModel

formula of the model including all potential variables

discreteSurv

Boolean var telling us whether a 'simple' multinomial regression is looked for or if the goal is a discrete survival-time model for multiple modes of failure is needed.

modelPrior

what prior should be used on the model space? modelPrior should be included in {'flat','dependent'} where 'flat' means a uniform pior and 'dependent' sets a multiplicity-corrected model prior on the model space.

Value

a numerical vector with the prior model probabilities

Examples

# NOT RUN {
# the definition of the full model with three potential predictors:
FULL <- outcome ~ ns(day, df = 4) + gender + type + SOFA
# here we define time as a spline with 3 knots

priors <- model_priors(fullModel = FULL, discreteSurv = TRUE,
                       modelPrior = 'dependent')
# }