# Basic Concepts in SEM ## Basic Structural Equation Modelling Concepts

Understanding Basic Structural Equation Modelling Concepts is critical before scholars use SEM based software.

The video is dedicated to describing some critical terms in Structural Equation Modelling literature: Factor Loadings, Beta Coefficient, and Reliability.

Indicator loadings Are the bivariate correlations between a construct and the indicators. They determine an item’s absolute contribution to its assigned construct. Loadings are of primary interest in the evaluation of reflective measurement models but are also interpreted when formative measures are involved. They are also referred to as outer loadings. The recommended loading value is 0.70.

### What is Indicator Reliability?

Indicator reliability Is the square of a standardized indicator’s indicator loading. It represents how much of the variation in an item is explained by the construct and is referred to as the variance extracted from the item. Indicator loadings above 0.708 are recommended, since they indicate that the construct explains more than 50 percent of the indicator’s variance, thus providing acceptable indicator reliability. The calculation of indicator reliability can be performed by squaring the values in the indicator/factor loading. The squared value >= 0.50 indicates the indicator reliability is established.

### What is Beta Coefficient/Path Coefficient?

Are estimated path relationships in the structural model (i.e., between constructs in the model). They correspond to standardized betas in a regression analysis.

### What is Beta Coefficient/Path Coefficient?

Is a form of reliability used to judge the consistency of results across items on the same test. It determines whether the items measuring a construct are similar in their scores (i.e., if the correlations between items are strong).

### Reference

Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook.