data_cat_vim: Mock data set for Variable Importance Analysis with...
In tlverse/tmle3mopttx: Targeted Maximum Likelihood Estimation of the Mean under Optimal Individualized Treatment
data_cat_vim R Documentation
Mock data set for Variable Importance Analysis with Categorical Treatment
Description
A dataset with a simple data structure O = (A, Y, W), where outcome (Y) is
binary and treatment (A) is categorical.
This is a simple dataset designed specifically to illustrate the TMLE estimation procedure.
Usage
data_cat_vim
Format
A data.frame with 6 columns.
- Y
A binary variable representing an outcome of interest.
- A
A binary variable representing an intervention of interest.
- W1
A categorical variable representing a covariate of interest.
- W2
A categorical variable representing a covariate of interest.
- W3
A categorical variable representing a covariate of interest.
- W4
A categorical variable representing a covariate of interest.
tlverse/tmle3mopttx documentation built on Aug. 9, 2022, 3:31 p.m.
R Package Documentation
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| data_cat_vim | R Documentation |
Mock data set for Variable Importance Analysis with Categorical Treatment
Description
A dataset with a simple data structure O = (A, Y, W), where outcome (Y) is binary and treatment (A) is categorical. This is a simple dataset designed specifically to illustrate the TMLE estimation procedure.
Usage
data_cat_vim
Format
A data.frame with 6 columns.
- Y
A binary variable representing an outcome of interest.
- A
A binary variable representing an intervention of interest.
- W1
A categorical variable representing a covariate of interest.
- W2
A categorical variable representing a covariate of interest.
- W3
A categorical variable representing a covariate of interest.
- W4
A categorical variable representing a covariate of interest.
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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