Related Experiment Video
Updated: Feb 10, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and
Seda Can1, Rens van de Schoot2, Joop Hox2
1İzmir University of Economics, İzmir, Turkey.
Abstract:
Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions.
Related Concept Videos
Variability: Analysis
The range is a simple measure of variability, indicating the difference between the highest and...
Maximum Deflection
The maximum deflection occurs at a specific point, known as point O, where the tangent to the deflection curve is horizontal. To find point O, the slope of the tangent at any...
Maximum Power Transfer
By substituting the entire circuit with...
Maximum Size of Aggregate
The Maximum Power Transfer Theorem
The load connected draws the current, and the circuit delivers the power to the load. The alternating current flowing through the load is determined using the rectangular form of voltages, currents, network impedance, and load impedance. The average power delivered to the load is obtained from the product of the square of current and load resistance.
The Sense of Self: Reflected Self-Appraisal and Social Comparison

