Related Experiment Video
Updated: Mar 27, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
The Determinacy of Variables in Structural Equation Models
Abstract:
The indeterminacy of variables in a structural equation model - a path model with latent variables - is considered. It is shown that when the variables in the structural ]model are all manifest, the error-terms - disturbances - are uniquely determined given the parameters and the data; when the variables in the structural model are all latent, the error-terms have indeterminate components that are simple linear transformations of the indeterminate I components of the common factor model; and when they are mixed, a sufficient condition for the error-term associated with a manifest variable to be uniquely determined is that there is no directed path to it from a latent variable. Moreover, for error-terms that are indeterminate due to the effects of latent variables it is demonstrated that error-term analysis along the lines of residual analysis can be employed by the use of suitable estimates of the latent variables.
More Related Videos
08:27Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
Published on: September 27, 2019
09:00Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
Published on: August 16, 2024
Related Concept Videos
Constraints and Statical Determinacy
Determination of Expected Frequency
Statically Indeterminate Problem Solving
Gaussian Elimination: Problem Solving
Indeterminate Structure
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as: