Package com.bayesserver.causal
Class BackdoorCriterion
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- com.bayesserver.causal.BackdoorCriterion
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- All Implemented Interfaces:
Identification,Validation
public final class BackdoorCriterion extends Object implements Identification, Validation
Uses the 'Backdoor Criterion' to identify 'adjustment sets', that if found can be used to estimate the causal effect using theBackdoorInference. The version of the 'Backdoor Criterion' used is complete, and sometimes referred to as just the 'adjustment criterion'.Although the estimation can also be performed using Bayes Server, this criterion can also be used to identfy adjustment sets for use outside Bayes Server.
For more information see 'On the Validity of Covariate Adjustment for Estimating Causal Effects' - Shpitser et al 2012.
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Constructor Summary
Constructors Constructor Description BackdoorCriterion(Network network)Initializes a new instance of theBackdoorCriterionclass.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description NetworkgetNetwork()The Bayesian network on which the identification is based.IdentificationOutputidentify(Evidence evidence, Distribution query, IdentificationOptions options)Determines how to quantify a cause-effect relationship (for a particular criterion), but does not perform the actual estimation.IdentificationOutputidentify(List<CausalNode> treatments, List<CausalNode> outcomes, List<CausalNode> nonTreatmentEvidence, IdentificationOptions options)Determines how to quantify a cause-effect relationship (for a particular criterion), but does not perform the actual estimation.booleanisValid(Evidence evidence, Distribution query, ValidationOptions options)Tests whether adjustment inputs are valid, without raising an exception.booleanisValid(List<CausalNode> treatments, List<CausalNode> outcomes, List<CausalNode> nonTreatmentEvidence, ValidationOptions options)Tests whether adjustment inputs are valid, without raising an exception.voidvalidate(Evidence evidence, Distribution query, ValidationOptions options)Tests whether adjustment inputs are valid, and throws an exception if not, with an error message.voidvalidate(List<CausalNode> treatments, List<CausalNode> outcomes, List<CausalNode> nonTreatmentEvidence, ValidationOptions options)Tests whether adjustment inputs are valid, and throws an exception if not, with an error message.
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Constructor Detail
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BackdoorCriterion
public BackdoorCriterion(Network network)
Initializes a new instance of theBackdoorCriterionclass.- Parameters:
network- The Bayesian network.
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Method Detail
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getNetwork
public Network getNetwork()
The Bayesian network on which the identification is based.- Specified by:
getNetworkin interfaceIdentification
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validate
public void validate(Evidence evidence, Distribution query, ValidationOptions options)
Tests whether adjustment inputs are valid, and throws an exception if not, with an error message.- Specified by:
validatein interfaceValidation- Parameters:
evidence- Evidence which contains both one or more interventions (treatments X), and optionally other standard (non-intervention) evidence.query- One or more outcomes (effects) Y.options- Other options that govern how the calculations are performed. Some options are common to all criterion, and some will have additional options specific to that criterion.
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isValid
public boolean isValid(Evidence evidence, Distribution query, ValidationOptions options)
Tests whether adjustment inputs are valid, without raising an exception. If invalid, you can also callcom.bayesserver.causal.Validation#validate(IEvidence, IDistribution, IValidationOptions)'Validate' to throw an exception which contains an error message.- Specified by:
isValidin interfaceValidation- Parameters:
evidence- Evidence which contains both one or more interventions (treatments X), and optionally other standard (non-intervention) evidence.query- One or more outcomes (effects) Y.options- Other options that govern how the calculations are performed. Some options are common to all criterion, and some will have additional options specific to that criterion.- Returns:
trueif valid,falseotherwise.
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identify
public IdentificationOutput identify(Evidence evidence, Distribution query, IdentificationOptions options)
Determines how to quantify a cause-effect relationship (for a particular criterion), but does not perform the actual estimation.- Specified by:
identifyin interfaceIdentification- Parameters:
evidence- Evidence which contains both one or more interventions (treatments X), and optionally other standard (non-intervention) evidence.query- One or more outcomes (effects), often denoted Y.options- Other options that govern how the calculations are performed. Some options are common to all criterion, and some will have additional options specific to that criterion.- Returns:
- Information on how to calculate the requested cause-effect relationship.
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identify
public IdentificationOutput identify(List<CausalNode> treatments, List<CausalNode> outcomes, List<CausalNode> nonTreatmentEvidence, IdentificationOptions options)
Determines how to quantify a cause-effect relationship (for a particular criterion), but does not perform the actual estimation.- Specified by:
identifyin interfaceIdentification- Parameters:
treatments- One or more treatments/interventions (X).outcomes- One or more outcomes (effects), often denoted Y.nonTreatmentEvidence- Any other evidence other than interventions.options- Other options that govern how the calculations are performed. Some options are common to all criterion, and some will have additional options specific to that criterion.- Returns:
- Information on how to calculate the requested cause-effect relationship.
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validate
public void validate(List<CausalNode> treatments, List<CausalNode> outcomes, List<CausalNode> nonTreatmentEvidence, ValidationOptions options)
Tests whether adjustment inputs are valid, and throws an exception if not, with an error message.- Specified by:
validatein interfaceValidation- Parameters:
treatments- One or more treatments/interventions (X).outcomes- One or more outcomes (effects), often denoted Y.nonTreatmentEvidence- Any non-treatment evidence.options- Other options that govern how the calculations are performed. Some options are common to all criterion, and some will have additional options specific to that criterion.
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isValid
public boolean isValid(List<CausalNode> treatments, List<CausalNode> outcomes, List<CausalNode> nonTreatmentEvidence, ValidationOptions options)
Tests whether adjustment inputs are valid, without raising an exception. If invalid, you can also call {@link com.bayesserver.causal.Validation#validate(IList{CausalNode}, IList{CausalNode}, IList{CausalNode}, IValidationOptions)} 'Validate' to throw an exception which contains an error message.- Specified by:
isValidin interfaceValidation- Parameters:
treatments- One or more treatments/interventions (X).outcomes- One or more outcomes (effects), often denoted Y.nonTreatmentEvidence- Any non-treatment evidence.options- Other options that govern how the calculations are performed. Some options are common to all criterion, and some will have additional options specific to that criterion.- Returns:
trueif valid,falseotherwise.
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