The article explores a factor analysis model that considers errors of varying sizes. The researchers introduce estimators that account for this variability in errors. They show that ignoring these differences can lead to inaccurate results. By comparing different approaches in a simulation study, they demonstrate the importance of accounting for heteroscedastic errors in factor analysis.