Mediana (version 1.0.3)

CSE: Clinical Scenario Evaluation

Description

This function is used to perform the Clinical Scenario Evaluation according to the objects of class DataModel, AnalysisModel and EvaluationModel specified respectively in the arguments data, analysis and evaluation of the function.

Usage

CSE(data, analysis, evaluation, simulation)

Arguments

data

defines a DataModel or a DataStack object

analysis

defines an AnalysisModel object

evaluation

defines an EvaluationModel object

simulation

defines a SimParameters object

Value

The CSE function returns a list containing:

References

Benda, N., Branson, M., Maurer, W., Friede, T. (2010). Aspects of modernizing drug development using clinical scenario planning and evaluation. Drug Information Journal. 44, 299-315.

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

See Also

See Also DataModel, DataStack, AnalysisModel, EvaluationModel, SimParameters.

Examples

## Not run: 
# # Outcome parameter set 1
# outcome1.placebo = parameters(mean = 0, sd = 70)
# outcome1.treatment = parameters(mean = 40, sd = 70)
# 
# # Outcome parameter set 2
# outcome2.placebo = parameters(mean = 0, sd = 70)
# outcome2.treatment = parameters(mean = 50, sd = 70)
# 
# # Data model
# case.study1.data.model = DataModel() +
#                          OutcomeDist(outcome.dist = "NormalDist") +
#                          SampleSize(c(50, 55, 60, 65, 70)) +
#                          Sample(id = "Placebo",
#                                 outcome.par = parameters(outcome1.placebo, outcome2.placebo)) +
#                          Sample(id = "Treatment",
#                                 outcome.par = parameters(outcome1.treatment, outcome2.treatment))
# 
# 
# # Analysis model
# case.study1.analysis.model = AnalysisModel() +
#                              Test(id = "Placebo vs treatment",
#                                   samples = samples("Placebo", "Treatment"),
#                                   method = "TTest")
# 
# # Evaluation model
# case.study1.evaluation.model = EvaluationModel() +
#                                Criterion(id = "Marginal power",
#                                          method = "MarginalPower",
#                                          tests = tests("Placebo vs treatment"),
#                                          labels = c("Placebo vs treatment"),
#                                          par = parameters(alpha = 0.025))
# 
# # Simulation Parameters
# case.study1.sim.parameters = SimParameters(n.sims = 1000, proc.load = 2, seed = 42938001)
# 
# # Perform clinical scenario evaluation
# case.study1.results = CSE(case.study1.data.model,
#                           case.study1.analysis.model,
#                           case.study1.evaluation.model,
#                           case.study1.sim.parameters)
# 
# # Summary of the simulation results
# summary(case.study1.results)
# 
# # Get the data generated for the simulation
# case.study1.data.stack = DataStack(data.model = case.study1.data.model,
#                                    sim.parameters = case.study1.sim.parameters)
# 
# ## End(Not run)


## Not run: 
# #Alternatively, a DataStack object can be used in the CSE function
# # (not recommanded as the computational time is increased)
# 
# # Generate data
# case.study1.data.stack = DataStack(data.model = case.study1.data.model,
#                                    sim.parameters = case.study1.sim.parameters)
# 
# # Perform clinical scenario evaluation with data stack
# case.study1.results = CSE(case.study1.data.stack,
#                           case.study1.analysis.model,
#                           case.study1.evaluation.model,
#                           case.study1.sim.parameters)
# ## End(Not run)