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Simple mediation model. The independent variable causes the mediator variable; the mediator variable causes the dependent variable. In statistics, a mediation model seeks to identify and explain the mechanism or process that underlies an observed relationship between an independent variable and a dependent variable via the inclusion of a third hypothetical variable, known as a mediator ...
The same is true for intervening variables (a variable in between the supposed cause (X) and the effect (Y)), and anteceding variables (a variable prior to the supposed cause (X) that is the true cause). When a third variable is involved and has not been controlled for, the relation is said to be a zero order relationship. In most practical ...
The model's implications for what the data should look like for a specific set of coefficient values depends on: a) the coefficients' locations in the model (e.g. which variables are connected/disconnected), b) the nature of the connections between the variables (covariances or effects; with effects often assumed to be linear), c) the nature of ...
A variable is considered dependent if it depends on an independent variable. Dependent variables are studied under the supposition or demand that they depend, by some law or rule (e.g., by a mathematical function), on the values of other variables. Independent variables, in turn, are not seen as depending on any other variable in the scope of ...
The first modern KBBI dictionary was published during the 5th Indonesian Language Congress on 28 October 1988. The first edition contains approximately 62,000 entries. The dictionary was compiled by a team led by the Head of the Language Center, Anton M. Moeliono , with chief editors Sri Sukesi Adiwimarta and Adi Sunaryo.
In statistics there is a synonym for intervening variable - "mediator variable". See Mediation (statistics). It seems that some crossreferences or merging needed. —Preceding unsigned comment added by 90.189.181.244 17:38, 5 March 2011 (UTC) Reply
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In statistics, identifiability is a property which a model must satisfy for precise inference to be possible. A model is identifiable if it is theoretically possible to learn the true values of this model's underlying parameters after obtaining an infinite number of observations from it.