The Use of control, Moderatingand Mediating Variables in Business Research - Organizational Justice

THE USE OF CONTROL, MODERATING AND MEDIATING VARIABLES IN BUSINESS RESEARCH - ORGANIZATIONAL
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(26, November 2010)
The Use of control, Moderating and Mediating Variables in Business Research - Organizational Justice
This essay provides a general discussion of control, Moderating and Mediating Variables. It also provides some examples of research of how these variables in their research models respectively.
Control Variables
The phrase control variable has different definitions depending on the area in which it is applied. The control variable is that variable that is held constant or whose effect is eliminated for analyzing the relationship between other variables with no interferences. It should not be confused with controlled variable, which is just another term for independent variable. In research, control variable has to remain unchanged, as its affects the dependent variables and thus influences the outcome (Lockwood & Hoffman, 2002).
Control variables usually supply values that are constant to the model program that are usually used in several ways. The control variable is normally declared by the control statement, and gives the specification of their value. They are not reinitialized before every pass through the data, hence used in retention of values between passes. One can also use control variable to vary the logic of the program
For instance, if one has two versions of an equation for a variable Y, one can enter both versions in a model, and by the use of a control statement to select one of them, produces two different solutions to explore the effect that the choice of the equation has on the model. This can be illustrated in the following statement.
Select (case);
When (1) y = ...first version of equation...;
When (2) y = ...second version of equation...;
End;
Control case 1;, solve / out=case1; run;
Control case 2; solve / out=case2; run;
Moderating variable
This variable is one that has stronger contingent effects on the controlled variable and dependant variable relations. In correlation, a moderating variable is a third variable that influences the zero-order correlation of two variables. The effects of this variable are characterized statistically as an interaction, meaning that is a qualitative or quantitative variable that influences the direction of and/or the strength of a relationship between independent and dependent variables (Pearl, 2000). The moderation analysis in Business Research - Organizational Justice entails the use of linear multiple regression analysis. The two methods that are used in the identification of moderator variables are; sub-ground analysis and moderated regression analysis.
There are various assumptions that are involved in mediator variables, namely; when X variable is not randomized, causation has to be assumed. Another assumption is the moderator variable relation and lastly, the measurement of moderator variables.
For instance in a casual relationship, a summing that X is the predictor variable and then Y a casual variable, then Z becomes the moderator variable, that influences the casual relationship of X and Y. the effects of moderation can be represented the interaction between X and Z variable. In an equation that is that is multiple regression, the moderator variable is as
Y = α + β1X + β2Z+ β3XZ + έ
In the above model equation, the effects of interaction between X and Z (or coefficient), measures the moderation effects. In such like equation, the relation is linear.
In a more familiar analysis of variance, the basic effects of moderators can be represented as an interaction between a focal independent variable and a factor that clarifies appropriate environment for its operation (Pearl, 2000). It is good for moderator variables to be uncorrelated with both the predictor and the criterion to give clear interpretable interaction term (Baron, & David, 1986).
Mediating Variables
The...