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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 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]
The identification of intervening variables and further replications of studies can also strengthen claims of causal inference. [3] Different methodological approaches make tradeoffs between statistical rigor (the ability to confidently attribute change to one variable or cause), qualitative depth, and finances available for research.
Wright correctly concluded that he needed a variable that correlated with either demand or supply but not both – that is, an instrumental variable. After much deliberation, Wright decided to use regional rainfall as his instrumental variable: he concluded that rainfall affected grass production and hence milk production and ultimately butter ...
The quasi-independent variable is the variable that is manipulated in order to affect a dependent variable. It is generally a grouping variable with different levels. Grouping means two or more groups, such as two groups receiving alternative treatments, or a treatment group and a no-treatment group (which may be given a placebo – placebos ...
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)
Judea Pearl defines a causal model as an ordered triple ,, , where U is a set of exogenous variables whose values are determined by factors outside the model; V is a set of endogenous variables whose values are determined by factors within the model; and E is a set of structural equations that express the value of each endogenous variable as a function of the values of the other variables in U ...
For example, if an outdoor experiment were to be conducted to compare how different wing designs of a paper airplane (the independent variable) affect how far it can fly (the dependent variable), one would want to ensure that the experiment is conducted at times when the weather is the same, because one would not want weather to affect the ...