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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 ...
In statistics, the Sobel test is a method of testing the significance of a mediation effect. The test is based on the work of Michael E. Sobel, [1] [2] and is an application of the delta method.
In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]
An economic variable can be exogenous in some models and endogenous in others. In particular this can happen when one model also serves as a component of a broader model.
Informally, in attempting to estimate the causal effect of some variable X ("covariate" or "explanatory variable") on another Y ("dependent variable"), an instrument is a third variable Z which affects Y only through its effect on X.
In this situation, the term hidden variables is commonly used (reflecting the fact that the variables are meaningful, but not observable). Other latent variables correspond to abstract concepts, like categories, behavioral or mental states, or data structures.
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
In statistics and social sciences, an antecedent variable is a variable that cannot help to explain the apparent relationship (or part of the relationship) between other variables that are nominally in a cause and effect relationship.