CondiS_X: CondiS-X Function
In yizhuo-wang/CondiS: Censored data imputation for direct modeling
Description
Usage
Arguments
Examples
Description
This function allows you to improve the imputed survival time by incorporating covariate information.
Usage
1
CondiS_X(pred_time, status, covariates, method)
Arguments
pred_time
The imputed follow up time for right-censored data.
status
The censoring indicator, normally 0=right censored, 1=event at time.
covariates
The additional patient data that is presumably associated with the survival time.
method
Choose from 8 machine learning algorithms; the default is "glm".
Examples
1
CondiS(survival_dat)
yizhuo-wang/CondiS documentation built on Dec. 24, 2021, 1:19 a.m.
R Package Documentation
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Description Usage Arguments Examples
Description
This function allows you to improve the imputed survival time by incorporating covariate information.
Usage
1 | CondiS_X(pred_time, status, covariates, method)
|
Arguments
pred_time |
The imputed follow up time for right-censored data. |
status |
The censoring indicator, normally 0=right censored, 1=event at time. |
covariates |
The additional patient data that is presumably associated with the survival time. |
method |
Choose from 8 machine learning algorithms; the default is "glm". |
Examples
1 | CondiS(survival_dat)
|
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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