Description Usage Arguments Value Author(s) Examples
This function computes the prior model probabilities of the candidate models
1 | model_priors(fullModel, discreteSurv = TRUE, modelPrior = "flat")
|
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?
|
a numerical vector with the prior model probabilities
Rachel Heyard
1 2 3 4 5 6 | # 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')
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