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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:
install.packages("predRupdate")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,
"Creatinine" = 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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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