Comments (2)
Hi Dan,
Thank you for your comments and questions. I will discuss them with my colleague Gernot and respond to you later.
The designPlan
already holds an internal reference to design
: Use designPlan$.design
Best,
Friedrich
from rpact.
Thank you for your interest in rpact.
I try to answer your question as follows:
An expectation is a theoretical quantity that needs not necessarily be "observable".
If you play dice, for example, the expected outcome is 3.5 = (1 + 2 + 3 + 4 + 5+ 6) / 6.
And there is no outcome "3.5"!
The same is true for the expected study duraction, the expected number of events, and the expected number of subjects.
Does this help?
Kind regards,
Gernot Wassmer
from rpact.
Related Issues (20)
- Example from help(plot.Dataset) seems incorrect HOT 2
- Misleading outputs regarding (cumulative) number of events in survival settings and possible bug HOT 3
- Inconsistent result on probabilities of stopping for futility when all populations are not selected in getSimulationEnrichmentRates() for rpact version 3.4.0 and 3.5.0 HOT 1
- calcSubjectsFunction: should clarify allocationRatioPlanned should be treated as vector instead of scalar HOT 2
- Installation Error rpact HOT 2
- Inconsistent naming of variables: Single and cumulative events per stage HOT 1
- Wrong calculation of accrual intensity for fixed sample survival design HOT 1
- peculiarity in getSimulationSurvival() in one iteration HOT 1
- Possible inconsistency in getSimulationSurvival() with specified thetaH0 and thetaH1 HOT 2
- Direction of One-Sided Alternatives
- Add support for population selection based on predictive/posterior probabilities in getSimulationEnrichmentMeans/Rates/Survival HOT 1
- Minor fixes HOT 1
- Final CI for non-inferiority sequential design HOT 1
- [Feature request] Better support for exact binomial tests (one- and two-sample)
- [Feature request] Enhanced support for count endpoints
- print() output: value of bindingFutility not correctly displayed
- [Request for Clarification, Improvement, or Removed Functionality] Calculation of "optimal" allocation ratio for survival outcomes. HOT 1
- Efficacy boundary (treatment effect scale) for two-sided tests not shown in summary() since version 4.0.0
- Automatic boundary calculation HOT 1
- Index Error HOT 2
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