pmmFit: Predictive mean matching using lasso
In PatientLevelPrediction: Develop Clinical Prediction Models Using the Common Data Model
pmmFit R Documentation
Predictive mean matching using lasso
Description
Predictive mean matching using lasso
Usage
pmmFit(data, k = 5, alpha = 1)
Arguments
data
An andromeda object with the following fields:
xObs: covariates table for observed data
xMiss: covariates table for missing data
yObs: outcome variable that we want to impute
k
The number of donors to use for matching (default 5)
alpha
Elastic-net mixing parameter (1 = lasso, 0 = ridge)
PatientLevelPrediction documentation built on March 9, 2026, 5:07 p.m.
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| pmmFit | R Documentation |
Predictive mean matching using lasso
Description
Predictive mean matching using lasso
Usage
pmmFit(data, k = 5, alpha = 1)
Arguments
data |
An andromeda object with the following fields: xObs: covariates table for observed data xMiss: covariates table for missing data yObs: outcome variable that we want to impute |
k |
The number of donors to use for matching (default 5) |
alpha |
Elastic-net mixing parameter ( |
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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