CSE: Clinical Scenario Evaluation

In gpaux/Mediana: Clinical Trial Simulations

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:

simulation.results	a data frame containing the results of the simulations for each scenario.
analysis.scenario.grid	a data frame containing the grid of the combination of data and analysis scenarios.
data.structure	a list containing the data structure according to the DataModel object.
analysis.structure	a list containing the analysis structure according to the AnalysisModel object.
evaluation.structure	a list containing the evaluation structure according to the EvaluationModel object.
sim.parameters	a list containing the simulation parameters according to SimParameters object.
timestamp	a list containing information about the start time, end time and duration of the simulation runs.

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)

gpaux/Mediana documentation built on May 31, 2021, 1:22 a.m.