convertBinTEtoCls: Converting a binary yes-no treatment effect task to a...
In AlekseyBuzmakov/FCAPS.R: A tool for preparation of the data for FCAPS software
Description
Usage
Arguments
Details
Value
View source: R/treatment-effect.R
Description
The function converts a binary Y and binary Trt variables to a single classification variable
based on following ideas.
Usage
1
convertBinTEtoCls(Y, Trt, file)
Arguments
Y
is 1-0 (or true-false) variable indicating the response variable in the treatment effect, e.g., if there is a visit of a customer or not
Trt
is 1-0 variable, indicating if the observation was in the treatment group, e.g., the customers recieved a promo has 1, and customers from the control group has 0.
file
is the path to the file where to store the result
Details
1. Weisberg H.I., Pontes V.P. Post hoc subgroups in clinical trials: Anathema or analytics? // Clin. Trials. SAGE Publications, 2015. Vol. 12, № 4. P. 357–364.
2. Tian L. et al. A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates // J. Am. Stat. Assoc. Taylor & Francis, 2014. Vol. 109, № 508. P. 1517–1532.
The resulting file is supposed to be used with BinaryClassificationOEst module of FCAPS software
Value
NULL if file is given, and the content of the file if the file is empty
AlekseyBuzmakov/FCAPS.R documentation built on May 20, 2020, 12:42 a.m.
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Description Usage Arguments Details Value
View source: R/treatment-effect.R
Description
The function converts a binary Y and binary Trt variables to a single classification variable based on following ideas.
Usage
1 | convertBinTEtoCls(Y, Trt, file)
|
Arguments
Y |
is 1-0 (or true-false) variable indicating the response variable in the treatment effect, e.g., if there is a visit of a customer or not |
Trt |
is 1-0 variable, indicating if the observation was in the treatment group, e.g., the customers recieved a promo has 1, and customers from the control group has 0. |
file |
is the path to the file where to store the result |
Details
1. Weisberg H.I., Pontes V.P. Post hoc subgroups in clinical trials: Anathema or analytics? // Clin. Trials. SAGE Publications, 2015. Vol. 12, № 4. P. 357–364.
2. Tian L. et al. A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates // J. Am. Stat. Assoc. Taylor & Francis, 2014. Vol. 109, № 508. P. 1517–1532.
The resulting file is supposed to be used with BinaryClassificationOEst module of FCAPS software
Value
NULL if file is given, and the content of the file if the file is empty
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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