The endogenous variables value is established by the conditions of the other variables in the structure. The exogenous variables value in independent of the conditions of the other variables in the structure. The difference between the endogenous and exogenous variables is the endogenous depends solely on the structure and the exogenous depend on outside elements.
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The distinction between these two types of variables is whether the variable regress on another variable or not. Like in a linear regression the dependent variable (DV) regresses on the independent variable (IV), meaning that the DV is being predicted by the IV. Within SEM modelling this means that the exogenous variable is the variable that another variable regresses on. Exogenous variables can be recognized in a graphical version of the model, as the variables sending out arrowheads, denoting which variable it is predicting. A variable that regresses on a variable is always an endogenous variable even if this same variable is used as an variable to be regressed on.
An intervening variable is a hypothetical internal state that is used to explain relationships between observed variables
correlation * * * * * Only if the relationship is linear. For example, the correlataion between y and x when y = x2 is zero. But a very strong relationship between the two variables.
Positive correlation is a relationship between two variables in which both variables move in tandem that is in the same direction.
relationship between 2 variables