Ontobiostat Relation that involve directed causal relation Directed causal relation as defined in the causal diagram with directed edge (unidrected age or bidirected edge). One variable or more are on the causal path between two variables with a directed relation. One variable or more are on the causal path between ancestor and descendant involved in a Share_ancestor relation One variable or more are on the causal path between ancestor and descendant involved in a Share_descedant relation Inverse relations inferred Two variables that could be correlated as a result of causal relation or non directed relation Two variables that share a common cause. Two variables have a common consequence that is constant, adjusted or matched. asymétrique, transitif, irreflexif hasParent When A isCauseof B, then A is a counterfactual probabilistic cause of B. A is an indirect cause of B when A cause C and C cause B. $Clinical_Datawarehouse_Database$ $Healthcare_claims_Database$ $Protocol_prospective_Database$ $Registry_Database$ $Survey_Database$ All variable need a definition because two identical variable may have different definition Minimal duration of exposition to be considered exposed minimal duration of the outcome before it can be diagnosed 0.0 100.0 The maount of NA may lead to avoid variable $bounded$ $complete$ $constant$ $incomplete$ In mathematics, a constant is a non-varying value, i.e. completely fixed or fixed in the context of use. The term usually occurs in opposition to variable (i.e. variable quantity), which is a symbol that stands for a value that may vary. In polynomials, polynomial function of degree 2 is generally denoted as a x^2 + b x + c, where a, b and c are constants (or parameters), while x is the variable, a placeholder for the argument of the function being studied. source: http://en.wikipedia.org/wiki/Constant_%28mathematics%29. HUPSO $dichotomous$ $ordinal$ $polychotomous$ $quantitative$ STATO and HPSO ontology provide these entities as subclass of variable Need to know if the variable is measured (or observed) vs unmeasured. During the collection, NA value was enable or not. OntoBioStat:Adhered Patient formally benefit from an intervention OntoBioStat:Adjusted Covariate used in a model in addition of exposure and the outcome OntoBioStat:Author_Point_of_view Who perceive OntoBioStat:Available Being exposed to x is logistically possible. OntoBioStat:Collection_method Method or algorithm for data extraction 2 OntoBioStat:Collider Attention c'est une définition générique non reliée à la problématique E -> O is variable that is a common consequence of two or more others variables OntoBioStat:Collider_Confounder Confounder due to adjustment, stratification or matching on a collider . Known as collider-strafication bias. http://purl.obolibrary.org/obo/OBCS_0000039 OntoBioStat:Condition Exist and Symptomatic and Investigated by a Healthcare_Provider with an examination that exist and available and indicated to be prescribed then delivered/taken to diagnosed disease Disease or symptoms OntoBioStat:Confounder_like Covariate that is cause by confounder and cause exposure or outcome http://purl.obolibrary.org/obo/OBCS_0000039 OntoBioStat:Covariate Variable that are not exposure and not outcome OntoBioStat:Decision_maker who decide and/or acte OntoBioStat:Delivered Drug is delivered or provided OntoBioStat:Differential_Bias_Unadjusted_Confounder Exposure lead to bias that cannot be corrected OntoBioStat:Direct_Confounder http://purl.obolibrary.org/obo/OBCS_0000039 OntoBioStat:Environmental_Exposure exposure coming from outside the subject $constant$ OntoBioStat:Excluded excluded patients OntoBioStat:Exist what precede everything OntoBioStat:Explicative_Variable Also called Independent variable that explain the outcome also called Dependent variable OntoBioStat:Exposure_stressor Variable defined as exposure is defined by causality question OntoBioStat:Health_Behaviour exist and available and indicated (authorized) and prescribed (auto prescribed) and delivered and taken Health behaviour corresponds to any patient behaviour that could improve or aggravate health. OntoBioStat:Indicated Patient caracteristics indicate a given intervention OntoBioStat:Indirect_Confounder http://purl.obolibrary.org/obo/OBCS_0000039 OntoBioStat:Inferred_Missing_data_mechanism Mechanism that generated missing values OntoBioStat:Inferred_Variable Inferred_Variable correspond to the results of inferences from axioms and swrl rules. 2 OntoBioStat:Interaction covariable cause a causal relation http://purl.obolibrary.org/obo/OBCS_0000112 OntoBioStat:Interaction_Confounder Interaction responsible for confounding OntoBioStat:Interaction_Couple OntoBioStat:Interaction_Single One variable interacting on a causal relation between two variables without any other relation OntoBioStat:Intervention_Effect Exist and Available and Indicated and Prescribed by a Prescriptor and Delivered and Taken Any intervention provided by another individual that the patient himself OntoBioStat:Investigated action of launching investigation OntoBioStat:Location where does the variable take place OntoBioStat:MAR Values are missing at random OntoBioStat:MCAR Values are missing completly at random OntoBioStat:MNAR Values are missing not at random OntoBioStat:Matched Covariate used for matching patients OntoBioStat:Measured Measured with a method of measurement 1 1 1 1 OntoBioStat:Mediator is a variable on the causal path between exposure and outcome http://purl.obolibrary.org/obo/OBCS_0000111 OntoBioStat:Mediator_Differential_Confounder Mediator that cause a necessary variable is a confounder OntoBioStat:Meta_Variable Meta_Variable: supplementary data about the variable. OntoBioStat:Method_of_Measurement The method of measurement includes clinical and para clinical examination, questionnaire, interview, etc. OntoBioStat:Missing_Value_Reasons Variables responsible for missingness 3 OntoBioStat:Multiple_Interaction covariable cause more than one causal relation http://purl.obolibrary.org/obo/OBCS_0000012 OntoBioStat:Necessary_Variable Implicit and generic variables needed for the realization of a theoretical variable. OntoBioStat:Outcome the outcome or endpoint enable to judge the exposure effect OntoBioStat:Path_Modifier Method to correct bias by modifying causal path between exposure and outcome. A path modifier is not a variable anymore. OntoBioStat:Period when does the variable take place OntoBioStat:Ponderated Covariate used for ponderation OntoBioStat:Prescribed Exposure is prescribed OntoBioStat:Proxy_Confounder Covariate as proxy of agiven confounder OntoBioStat:Pure_effect_modification when there is an effect only if the two variables are positive OntoBioStat:Reverse_Causality the outcome could cause exposure OntoBioStat:Status Status take in consideration a large quantity of variable such as economic status, race, cognition, sex, gender etc. Status corresponds to a fact such as patient X is a male. OntoBioStat:Stratified Covariate used for stratification OntoBioStat:Synergistically_Antagonistically when combining 2 variables lead to increase or decrease occurence of an other OntoBioStat:Theoretical_Variable Gather all categories of variables OntoBioStat:Unajusted_Confounder Confounder that cannot be adjusted for because of strong selection bias such as contraindication or absolute indication OntoBioStat:Variable a variable is a data item which can assume any of a set of values, either as determined by an agent or as randomly occuring through observation. STATO Ontobiostat true NRC_exposure true NRC_outcome true Sign_DD_Share_ancestor true Sing_ID_Share_ancestor true Sign_II_Share_ancestor true Sign_DD true Sign_ID true Sign_II true Proxy_Confounder false true Indirect_Cause true Indirect_Confounder true Indirect_Share_Ancestor true Collider_Confounder true Reverse_Causality true Share_Ancestor true MNAR true NRE_exposure true Interaction_Confounder_Out true Interaction_Confounder_Exp true NRHB_exposure true Necessary_Rules_Intervention_Exposure true Differential_Bias_Unadjusted_Confounder true Sign DD Share descendant true Sign DI Share descendant true Sign II Share descendant true Indirect_Share_Descendant true Share_Descendant true Mediator_Confounder true Pure_effect_modification true Synergy true Interaction_Single true METAVAR_COV $complete$