SurvGSD v1.0.0
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Group Sequential Design for a Clinical Trial with Censored Survival Data
Sample size calculation utilizing the information fraction and the alpha spending function
in a group sequential clinical trial with censored survival data from underlying generalized
gamma survival distributions or log-logistic survival distributions.
Hsu, C.-H., Chen, C.-H, Hsu, K.-N. and Lu, Y.-H. (2018) A useful design utilizing the
information fraction in a group sequential clinical trial with censored survival data.
To appear in Biometrics.
Functions in SurvGSD
| Name | Description | |
| General.tau | Information fractions under a generalized gamma survival distribution or a log-logistic survival distribution. | |
| Find.h | To find parameter of a uniform dropout censoring distribution under a generalized gamma survival distribution or a log-logistic survival distribution. | |
| SSize.FixAlter | Maximum sample size for a group sequential test under a generalized gamma survival distribution or a log-logistic survival distribution. | |
| No Results! | ||
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Details
| Type | Package |
| License | GPL-2 | GPL-3 |
| Encoding | UTF-8 |
| LazyData | true |
| RoxygenNote | 6.0.1 |
| NeedsCompilation | no |
| Packaged | 2018-05-15 01:05:22 UTC; yhchen |
| Repository | CRAN |
| Date/Publication | 2018-05-16 14:09:03 UTC |
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[](http://www.rdocumentation.org/packages/SurvGSD)
