gumbel.est: Estimate baseline parameters in the Gumbel-Hougaard model for...
In WR: Win Ratio Analysis of Composite Time-to-Event Outcomes
Description
Usage
Arguments
Value
References
See Also
Examples
Description
Estimate baseline parameters in the Gumbel–Hougaard model
described in base for sample size calculation using pilot study data.
Usage
1
gumbel.est(id, time, status)
Arguments
id
A vector of unique patient identifiers.
time
A numeric vector of event times.
status
A vector of event type variable; 2 = nonfatal event, 1 = death,
and 0 = censoring.
Value
A list containing lambda_D for λ_D,
lambda_H for λ_H, and kappa for κ
in the Gumbel–Hougaard model.
References
Mao, L., Kim, K. and Miao, X. (2021). Sample size formula for general win ratio analysis.
Biometrics, https://doi.org/10.1111/biom.13501.
See Also
Examples
1
# see the example for WRSS
WR documentation built on Nov. 27, 2021, 1:06 a.m.
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Description Usage Arguments Value References See Also Examples
Description
Estimate baseline parameters in the Gumbel–Hougaard model
described in base for sample size calculation using pilot study data.
Usage
1 | gumbel.est(id, time, status)
|
Arguments
id |
A vector of unique patient identifiers. |
time |
A numeric vector of event times. |
status |
A vector of event type variable; 2 = nonfatal event, 1 = death, and 0 = censoring. |
Value
A list containing lambda_D for λ_D,
lambda_H for λ_H, and kappa for κ
in the Gumbel–Hougaard model.
References
Mao, L., Kim, K. and Miao, X. (2021). Sample size formula for general win ratio analysis. Biometrics, https://doi.org/10.1111/biom.13501.
See Also
Examples
1 | # see the example for WRSS
|
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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