Editing Path analysis (statistics) (section)

==Path modeling==
Typically, path models consist of independent and dependent variables depicted graphically by boxes or rectangles. Variables that are independent variables, and not dependent variables, are called  'exogenous'. Graphically, these exogenous variable boxes lie at outside edges of the model and have only single-headed arrows exiting from them. No single-headed arrows point at exogenous variables. Variables that are solely dependent variables, or are both independent and dependent variables, are termed 'endogenous'. Graphically, endogenous variables have at least one single-headed arrow pointing at them.

In the model below, the two exogenous variables (Ex<sub>1</sub> and Ex<sub>2</sub>) are modeled as being [[correlation|correlated]] as depicted by the double-headed arrow. Both of these variables have direct and indirect (through En<sub>1</sub>) effects on En<sub>2</sub> (the two dependent or 'endogenous' variables/factors).  In most real-world models, the endogenous variables may also be affected by variables and factors stemming from outside the model (external effects including measurement error).  These effects are depicted by the "e" or error terms in the model.

[[Image:Path example.JPG]]

Using the same variables, alternative models are conceivable.  For example, it may be hypothesized that Ex<sub>1</sub> has only an indirect effect on En<sub>2</sub>, deleting the arrow from Ex<sub>1</sub> to En<sub>2</sub>; and the likelihood or 'fit' of these two models can be compared statistically.