Mediana (version 1.0.3)

DataStack: DataStack object

Description

This function generates data according to the specified data model.

Usage

DataStack(data.model, sim.parameters)

Arguments

data.model

defines a DataModel object.

sim.parameters

defines a SimParameters object.

Value

This function generates a data stack according to the data model and the simulation parameters objetcs. The object returned by the function is a DataStack object containing:A specific data.set of a DataStack object can be extracted using the ExtractDataStack function.

References

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

See Also

See Also DataModel and SimParameters and ExtractDataStack.

Examples

## Not run: 
#   # Generation of a DataStack object
#   ##################################
# 
#   # 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))
# 
# 
#   # Simulation Parameters
#   case.study1.sim.parameters = SimParameters(n.sims = 1000,
#                                              proc.load = 2,
#                                              seed = 42938001)
# 
#   # Generate data
#   case.study1.data.stack = DataStack(data.model = case.study1.data.model,
#                                      sim.parameters = case.study1.sim.parameters)
# 
#   # Print the data set generated in the 100th simulation run
#   # for the 2nd data scenario for both samples
#   case.study1.data.stack$data.set[[100]]$data.scenario[[2]]
# 
#   # Extract the same set of data
#   case.study1.extracted.data.stack = ExtractDataStack(data.stack = case.study1.data.stack,
#                                                       data.scenario = 2,
#                                                       simulation.run = 100)
#   # The same dataset can be obtained using
#   case.study1.extracted.data.stack$data.set[[1]]$data.scenario[[1]]$sample
#   # A carefull attention should be paid on the index of the result.
#   # As only one data.scenario has been requested
#   # the result for data.scenario = 2 is now in the first position (data.scenario[[1]]).
# ## End(Not run)


## Not run: 
#   #Use of a DataStack object in the CSE function
#   ##############################################
# 
#   # 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))
# 
# 
#   # Simulation Parameters
#   case.study1.sim.parameters = SimParameters(n.sims = 1000,
#                                              proc.load = 2,
#                                              seed = 42938001)
# 
#   # Generate data
#   case.study1.data.stack = DataStack(data.model = case.study1.data.model,
#                                      sim.parameters = case.study1.sim.parameters)
# 
#   # 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.stack,
#                             case.study1.analysis.model,
#                             case.study1.evaluation.model,
#                             case.study1.sim.parameters)
# ## End(Not run)