multipleIDI: multiple integrated discrimination improvement
In OHDSI/PredictionComparison: Package for comparing patient level predictions developed using OHDSI's PatientLevelPreidiction package
Description
Usage
Arguments
Details
Value
Description
This function calculates the ntegrated discrimination improvement (IDI) metric for all model comparisons
Usage
1
multipleIDI(plpRunList)
Arguments
plpRunList
A list of objects returned runPlp() containing the trained model or the output when implementing an existing model
Details
Users need to input a lsit of two or more trained models (the output of runPlp()) or the output of running an existing model
Value
A data.frame containing the columns: Model1, Model2, IDI value and z-value (can be used for statistical significance). A positive value suggests Model1 is better than Model2. A negative values suggests the opposite.
OHDSI/PredictionComparison documentation built on July 14, 2020, 6:16 p.m.
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Description Usage Arguments Details Value
Description
This function calculates the ntegrated discrimination improvement (IDI) metric for all model comparisons
Usage
1 | multipleIDI(plpRunList)
|
Arguments
plpRunList |
A list of objects returned runPlp() containing the trained model or the output when implementing an existing model |
Details
Users need to input a lsit of two or more trained models (the output of runPlp()) or the output of running an existing model
Value
A data.frame containing the columns: Model1, Model2, IDI value and z-value (can be used for statistical significance). A positive value suggests Model1 is better than Model2. A negative values suggests the opposite.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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