The goal of predRupdate is to provide a suite of functions for validating a existing (i.e. previously developed) prediction/ prognostic model, and for applying model updating methods to said model, according to an available dataset.
The package can be installed from CRAN as follows:
You can install the development version of predRupdate from GitHub with::
# install.packages("devtools") devtools::install_github("GlenMartin31/predRupdate")
One main use of this package is to externally validate an existing (previously developed) prediction model. This can be achieved with the following code:
# create a data.frame of the model coefficients, with columns being variables coefs_table <- data.frame("Intercept" = -3.4, "SexM" = 0.306, "Smoking_Status" = 0.628, "Diabetes" = 0.499, "Creatine" = 0.538) #pass this into pred_input_info() Existing_Logistic_Model <- pred_input_info(model_type = "logistic", model_info = coefs_table) summary(Existing_Logistic_Model) #validate this model against an available dataset pred_validate(x = Existing_Logistic_Model, new_data = SYNPM$ValidationData, binary_outcome = "Y")
If you encounter a bug, please file an issue with a minimal reproducible example on GitHub.