AnalysisStack: AnalysisStack object

Description Usage Arguments Value References See Also Examples

View source: R/AnalysisStack.R

Description

This function generates analysis results according to the specified data and analysis models.

Usage

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AnalysisStack(data.model, analysis.model, sim.parameters)

Arguments

data.model

defines a DataModel object.

analysis.model

defines a AnalysisModel object.

sim.parameters

defines a SimParameters object.

Value

This function generates an analysis stack according to the data and analysis models and the simulation parameters objetcs. The object returned by the function is a AnalysisStack object containing:

description

a description of the object.

analysis.set

a list of size n.sims defined in the SimParameters object. This list contains the analysis results generated for each data scenario (first level), and for each test and statistic defined in the AnalysisModel object. The results generated for the ith simulation runs and the jth data scenario are stored in analysis.stack$analysis.set[[i]][[j]]$result (where analysis.stack is a AnalysisStack object). Then, this list is composed of three lists:

  • tests return the unadjusted p-values for to the tests defined in the AnalysisModel object.

  • statistic return the statistic defined in the AnalysisModel object.

  • test.adjust return a list of adjusted p-values according to the multiple testing procedure defined in the AnalysisModel object. The lenght of this list corresponds to the number of MultAdjProc objects defined in the AnalysisModel object. Note that if no MultAdjProc objects have been defined, this list contains the unadjusted p-values.

analysis.scenario.grid

a data frame indicating all data and analysis scenarios according to the DataModel and AnalysisModel objects.

analysis.structure

a list containing the analysis structure according to the AnalysisModel object.

sim.parameters

a list containing the simulation parameters according to SimParameters object.

A specific analysis.set of a AnalysisStack object can be extracted using the ExtractAnalysisStack function.

References

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

See Also

See Also DataModel, AnalysisModel and SimParameters and ExtractAnalysisStack.

Examples

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## Not run: 
# Generation of an AnalysisStack 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))

# Analysis model
case.study1.analysis.model = AnalysisModel() +
  Test(id = "Placebo vs treatment",
       samples = samples("Placebo", "Treatment"),
       method = "TTest") +
  Statistic(id = "Mean Treatment",
            method = "MeanStat",
            samples = samples("Treatment"))


# Simulation Parameters
case.study1.sim.parameters = SimParameters(n.sims = 1000,
                                           proc.load = 2,
                                           seed = 42938001)

# Generate results
case.study1.analysis.stack = AnalysisStack(data.model = case.study1.data.model,
                                           analysis.model = case.study1.analysis.model,
                                           sim.parameters = case.study1.sim.parameters)

# Print the analysis results generated in the 100th simulation run
# for the 2nd data scenario for both samples
case.study1.analysis.stack$analysis.set[[100]][[2]]

# Extract the same set of data
case.study1.extracted.analysis.stack =
  ExtractAnalysisStack(analysis.stack = case.study1.analysis.stack,
                       data.scenario = 2,
                       simulation.run = 100)

# 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 ($analysis.set[[1]][[1]]).

## End(Not run)

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