ric_regression: GLM-based RIC estimator. Needs a GLM regression object and...
In aminadibi/RIC: Relative Impact Characteristic Curve
Description
Usage
Arguments
Value
Description
In real world clinical trials and observational studies, net treatment effect is generally not available at the indivdiaul level.
However, G-Computation can be used to estimate net benefit by fitting a regression. ric_regression calculates relevant RIC statistics using the appropriate
regression object and dataset.
Usage
1
ric_regression(reg_object, pred_data)
Arguments
reg_object
a glm regression object (results of model fitting)
pred_data
data for G-computation. It must have a marker column named x and a treatment column named tx. Note that if there is variable follow-up time they should all be set to a unique value (e.g., one unit of time) in the prediction dataset to estimate rate
Value
RIC estimates
aminadibi/RIC documentation built on Aug. 12, 2019, 4:13 a.m.
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Description Usage Arguments Value
Description
In real world clinical trials and observational studies, net treatment effect is generally not available at the indivdiaul level. However, G-Computation can be used to estimate net benefit by fitting a regression. ric_regression calculates relevant RIC statistics using the appropriate regression object and dataset.
Usage
1 | ric_regression(reg_object, pred_data)
|
Arguments
reg_object |
a glm regression object (results of model fitting) |
pred_data |
data for G-computation. It must have a marker column named x and a treatment column named tx. Note that if there is variable follow-up time they should all be set to a unique value (e.g., one unit of time) in the prediction dataset to estimate rate |
Value
RIC estimates
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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