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Meta-analysis with the HADES EvidenceSynthesis Package

Source: R/Module-EvidenceSynthesis.R
EvidenceSynthesisModule.Rd

Module for for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study. This includes functions for performing meta-analysis and forest plots

Super class

Strategus::StrategusModule -> EvidenceSynthesisModule

Methods

Public methods

Inherited methods

Method new()

Initialize the module

Usage

EvidenceSynthesisModule$new()

Method execute()

Executes the EvidenceSynthesis package

Usage

EvidenceSynthesisModule$execute(
  connectionDetails,
  analysisSpecifications,
  executionSettings
)

Arguments

connectionDetails

An object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

analysisSpecifications

An object of type AnalysisSpecifications as created by createEmptyAnalysisSpecificiations().

analysisSpecifications

An object of type AnalysisSpecifications as created by createEmptyAnalysisSpecificiations().

executionSettings

An object of type ExecutionSettings as created by createCdmExecutionSettings() or createResultsExecutionSettings().

Method createResultsDataModel()

Create the results data model for the module

Usage

EvidenceSynthesisModule$createResultsDataModel(
  resultsConnectionDetails,
  resultsDatabaseSchema,
  tablePrefix = ""
)

Arguments

resultsConnectionDetails

The connection details to the results database which is an object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

resultsConnectionDetails

The connection details to the results database which is an object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

resultsDatabaseSchema

The schema in the results database that holds the results data model.

tablePrefix

A prefix to apply to the database table names (optional).

tablePrefix

A prefix to apply to the database table names (optional).

Method getResultsDataModelSpecification()

Get the results data model specification for the module

Usage

EvidenceSynthesisModule$getResultsDataModelSpecification(tablePrefix = "")

Arguments

tablePrefix

A prefix to apply to the database table names (optional).

tablePrefix

A prefix to apply to the database table names (optional).

Method uploadResults()

Upload the results for the module

Usage

EvidenceSynthesisModule$uploadResults(
  resultsConnectionDetails,
  analysisSpecifications,
  resultsDataModelSettings
)

Arguments

resultsConnectionDetails

The connection details to the results database which is an object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

resultsConnectionDetails

The connection details to the results database which is an object of class connectionDetails as created by the DatabaseConnector::createConnectionDetails() function.

analysisSpecifications

An object of type AnalysisSpecifications as created by createEmptyAnalysisSpecificiations().

analysisSpecifications

An object of type AnalysisSpecifications as created by createEmptyAnalysisSpecificiations().

resultsDataModelSettings

The results data model settings as created using [@seealso createResultsDataModelSettings()]

Method validateModuleSpecifications()

Validate the module specifications

Usage

EvidenceSynthesisModule$validateModuleSpecifications(moduleSpecifications)

Arguments

moduleSpecifications

The EvidenceSynthesis module specifications Create an evidence synthesis source

Method createEvidenceSynthesisSource()

Usage

EvidenceSynthesisModule$createEvidenceSynthesisSource(
  sourceMethod = "CohortMethod",
  databaseIds = NULL,
  analysisIds = NULL,
  likelihoodApproximation = "adaptive grid"
)

Arguments

sourceMethod

The source method generating the estimates to synthesize. Can be "CohortMethod" or "SelfControlledCaseSeries"

databaseIds

The database IDs to include. Use databaseIds = NULL to include all database IDs.

analysisIds

The source method analysis IDs to include. Use analysisIds = NULL to include all analysis IDs.

likelihoodApproximation

The type of likelihood approximation. Can be "adaptive grid" or "normal".

Returns

An object of type EvidenceSynthesisSource. Create parameters for a random-effects meta-analysis

Method createRandomEffectsMetaAnalysis()

Usage

EvidenceSynthesisModule$createRandomEffectsMetaAnalysis(
  alpha = 0.05,
  evidenceSynthesisAnalysisId = 1,
  evidenceSynthesisDescription = "Random-effects",
  evidenceSynthesisSource = NULL,
  controlType = "outcome"
)

Arguments

alpha

The alpha (expected type I error) used for the confidence intervals.

evidenceSynthesisAnalysisId

description

evidenceSynthesisDescription

description

evidenceSynthesisSource

description

controlType

description Create a parameter object for the function computeFixedEffectMetaAnalysis

Details

Use DerSimonian-Laird meta-analysis

Method createFixedEffectsMetaAnalysis()

Usage

EvidenceSynthesisModule$createFixedEffectsMetaAnalysis(
  alpha = 0.05,
  evidenceSynthesisAnalysisId = 1,
  evidenceSynthesisDescription = "Fixed-effects",
  evidenceSynthesisSource = NULL,
  controlType = "outcome"
)

Arguments

alpha

The alpha (expected type I error) used for the confidence intervals.

evidenceSynthesisAnalysisId

description

evidenceSynthesisDescription

description

evidenceSynthesisSource

description

controlType

description Create a parameter object for the function computeBayesianMetaAnalysis

Details

Create an object defining the parameter values.

Method createBayesianMetaAnalysis()

Usage

EvidenceSynthesisModule$createBayesianMetaAnalysis(
  chainLength = 1100000,
  burnIn = 1e+05,
  subSampleFrequency = 100,
  priorSd = c(2, 0.5),
  alpha = 0.05,
  robust = FALSE,
  df = 4,
  seed = 1,
  evidenceSynthesisAnalysisId = 1,
  evidenceSynthesisDescription = "Bayesian random-effects",
  evidenceSynthesisSource = NULL,
  controlType = "outcome"
)

Arguments

chainLength

Number of MCMC iterations.

burnIn

Number of MCMC iterations to consider as burn in.

subSampleFrequency

Subsample frequency for the MCMC.

priorSd

A two-dimensional vector with the standard deviation of the prior for mu and tau, respectively.

alpha

The alpha (expected type I error) used for the credible intervals.

robust

Whether or not to use a t-distribution model; default: FALSE.

df

Degrees of freedom for the t-model, only used if robust is TRUE.

seed

The seed for the random number generator.

evidenceSynthesisAnalysisId

description

evidenceSynthesisDescription

description

evidenceSynthesisSource

description

controlType

description Create EvidenceSynthesis diagnostics thresholds

Details

Create an object defining the parameter values.

Method createEsDiagnosticThresholds()

Threshold used to determine if we pass or fail diagnostics.

Usage

EvidenceSynthesisModule$createEsDiagnosticThresholds(
  mdrrThreshold = 10,
  easeThreshold = 0.25,
  i2Threshold = 0.4,
  tauThreshold = log(2)
)

Arguments

mdrrThreshold

What is the maximum allowed minimum detectable relative risk (MDRR)?

easeThreshold

What is the maximum allowed expected absolute systematic error (EASE).

i2Threshold

What is the maximum allowed I^2 (measure of between-database heterogeneity in random-effects models)?

tauThreshold

What is the maximum allowed tau (measure of between-database heterogeneity in Bayesian random-effects models)?

Returns

An object of type EsDiagnosticThresholds.

Method createModuleSpecifications()

Creates the module Specifications

Usage

EvidenceSynthesisModule$createModuleSpecifications(
  evidenceSynthesisAnalysisList,
  esDiagnosticThresholds = self$createEsDiagnosticThresholds()
)

Arguments

evidenceSynthesisAnalysisList

A list of objects of type EvidenceSynthesisAnalysis as generated by either the EvidenceSynthesisModule$createFixedEffectsMetaAnalysis() or EvidenceSynthesisModule$createBayesianMetaAnalysis() function.

esDiagnosticThresholds

An object of typeEsDiagnosticThresholds as generated by the EvidenceSynthesisModule$createEsDiagnosticThresholds() function.

Method clone()

The objects of this class are cloneable with this method.

Usage

EvidenceSynthesisModule$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.