Predict the risk of the outcome using the input plpModel for the input plpData
Arguments
- plpModel
An object of type
plpModel- a patient level prediction model- plpData
An object of type
plpData- the patient level prediction data extracted from the CDM.- population
The population created using createStudyPopulation() who will have their risks predicted or a cohort without the outcome known
- timepoint
The timepoint to predict risk (survival models only)
Examples
coefficients <- data.frame(
covariateId = c(1002),
coefficient = c(0.05)
)
model <- createGlmModel(coefficients, intercept = -2.5)
data("simulationProfile")
plpData <- simulatePlpData(simulationProfile, n = 50)
#> Generating covariates
#> Generating cohorts
#> Generating outcomes
prediction <- predictPlp(model, plpData, plpData$cohorts)
#> predict risk probabilities using predictGlm
#> Prediction took 0.099 secs
#> Prediction done in: 0.101 secs
# see the predicted risk values
head(prediction)
#> rowId subjectId targetId cohortStartDate daysFromObsStart daysToCohortEnd
#> 1 1 2e+10 1 2009-09-07 920 29
#> 2 2 2e+10 1 2011-10-10 608 881
#> 3 3 2e+10 1 2008-02-09 627 856
#> 4 4 2e+10 1 2012-06-30 950 341
#> 5 5 2e+10 1 2008-12-03 165 745
#> 6 6 2e+10 1 2010-07-30 900 211
#> daysToObsEnd ageYear gender value
#> 1 645 42 8507 0.4013123
#> 2 1455 37 8507 0.3429895
#> 3 1374 37 8532 0.3429895
#> 4 1108 39 8532 0.3658644
#> 5 1313 35 8532 0.3208213
#> 6 231 37 8532 0.3429895