Summarises the covariateData to calculate the mean and standard deviation per covaraite if the labels are input it also stratifies this by class label and if the trainRowIds and testRowIds specifying the patients in the train/test sets respectively are input, these values are also stratified by train and test set
covariateSummary(
covariateData,
cohort,
labels = NULL,
strata = NULL,
variableImportance = NULL,
featureEngineering = NULL
)Arguments
- covariateData
The covariateData part of the plpData that is extracted using
getPlpData- cohort
The patient cohort to calculate the summary
- labels
A data.frame with the columns rowId and outcomeCount
- strata
A data.frame containing the columns rowId, strataName
- variableImportance
A data.frame with the columns covariateId and value (the variable importance value)
- featureEngineering
(currently not used ) A function or list of functions specifying any feature engineering to create covariates before summarising
Value
A data.frame containing: CovariateCount CovariateMean and CovariateStDev plus these values for any specified stratification
Details
The function calculates various metrics to measure the performance of the model