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, seed = 42)
#> Generating covariates
#> Generating cohorts
#> Generating outcomes
prediction <- predictPlp(model, plpData, plpData$cohorts)
#> predict risk probabilities using predictGlm
#> Prediction took 0.148 secs
#> Prediction done in: 0.155 secs
# see the predicted risk values
head(prediction)
#> rowId subjectId targetId cohortStartDate daysFromObsStart daysToCohortEnd
#> 1 1 2e+10 1 2010-09-05 398 864
#> 2 2 2e+10 1 2010-06-22 130 899
#> 3 3 2e+10 1 2009-04-18 998 105
#> 4 4 2e+10 1 2007-10-18 301 176
#> 5 5 2e+10 1 2011-06-30 256 587
#> 6 6 2e+10 1 2008-03-12 126 141
#> daysToObsEnd ageYear gender value
#> 1 1553 35 8507 0.3208213
#> 2 1311 38 8532 0.3543437
#> 3 827 36 8532 0.3318122
#> 4 1003 33 8507 0.2994329
#> 5 1217 39 8532 0.3658644
#> 6 414 38 8532 0.3543437