Mediana (version 1.0.8)

Design: Design object

Description

This function creates an object of class Design which can be added to an object of class DataModel.

Usage

Design(enroll.period = NULL,
       enroll.dist = NULL,
       enroll.dist.par = NULL,
       followup.period = NULL,
       study.duration = NULL,
       dropout.dist = NULL,
       dropout.dist.par = NULL)

Arguments

enroll.period

defines the length of the enrollment period.

enroll.dist

defines the enrollment distribution.

enroll.dist.par

defines the parameters of the enrollment distribution (optional).

followup.period

defines the length of the follow-up period for each patient in study designs with a fixed follow-up period, i.e., the length of time from the enrollment to planned discontinuation is constant across patients. The user must specify either followup.period or study.duration.

study.duration

defines the total study duration in study designs with a variable follow-up period. The total study duration is defined as the length of time from the enrollment of the first patient to the discontinuation of the last patient.

dropout.dist

defines the dropout distribution.

dropout.dist.par

defines the parameters of the dropout distribution.

Details

Objects of class Design are used in objects of class DataModel to specify the design parameters used in event-driven designs if the user is interested in modeling the enrollment (or accrual) and dropout (or loss to follow up) processes that will be applied to the Clinical Scenario. Several objects of class Design can be added to an object of class DataModel.

Note that the length of the enrollment period, total study duration and follow-up periods are measured using the same time units.

If enroll.dist = "UniformDist", the enroll.dist.par should be let to NULL (then enrollment distribution will be uniform during the enrollment period).

If enroll.dist = "BetaDist", the enroll.dist.par should contain the parameter of the beta distribution (a and b). These parameters must be derived according to the expected enrollment at a specific timepoint. For example, if half the patients are expected to be enrolled at 75% of the enrollment period, the beta distribution is a Beta(log(0.5)/log(0.75), 1). Generally, let q be the proportion of enrolled patients at p% of the enrollment period, the Beta distribution can be derived as follows:

• If q > p, the Beta distribution is Beta(a,1) with a = log(p) / log(q)

• If q < p, the Beta distribution is Beta (1,b) with b = log(1-p) / log(1-q)

• Otherwise the Beta distribution is Beta(1,1)

If dropout.dist = "UniformDist", the dropout.dist.par should contain the dropout rate. This parameter must be specified using the prop parameter, such as dropout.dist.par = parameters(prop = 0.1) for a 10% dropout rate.

References

http://gpaux.github.io/Mediana/

See Also

See Also DataModel.

Examples

# NOT RUN {
## Create DataModel object with a Design Object
data.model = DataModel() +
             Design(enroll.period = 9,
                    study.duration = 21,
                    enroll.dist = "UniformDist",
                    dropout.dist = "ExpoDist",
                    dropout.dist.par = parameters(rate = 0.0115))

## Create DataModel object with several Design Objects
design1 = Design(enroll.period = 9,
                 study.duration = 21,
                 enroll.dist = "UniformDist",
                 dropout.dist = "ExpoDist",
                 dropout.dist.par = parameters(rate = 0.0115))

design2 = Design(enroll.period   = 18,
                 study.duration = 24,
                 enroll.dist = "UniformDist",
                 dropout.dist = "ExpoDist",
                 dropout.dist.par = parameters(rate = 0.0115))

data.model = DataModel() +
             design1 +
             design2
# }