The trade-off between factor score determinacy and the preservation of inter-factor correlations
Andr\'e Beauducel, Norbert Hilger, Tobias Kuhl

TL;DR
This study investigates the trade-off between factor score determinacy and the preservation of inter-factor correlations, showing that small gains in determinacy often lead to large biases in inter-correlations, and proposes a method to balance these aspects.
Contribution
It introduces a practical approach to compute correlation-preserving factor score predictors that balance determinacy and inter-correlation bias.
Findings
Small improvements in factor score determinacy cause large inter-correlation biases.
Correlation-preserving predictors can reduce bias without significant loss of determinacy.
A syntax is provided to compare and compute different factor score predictors.
Abstract
Regression factor score predictors have the maximum factor score determinacy, i.e., the maximum correlation with the corresponding factor, but they do not have the same inter-correlations as the factors. As it might be useful to compute factor score predictors that have the same inter-correlations as the factors, correlation-preserving factor score predictors have been proposed. However, correlation-preserving factor score predictors have smaller correlations with the corresponding factors (factor score determinacy) than regression factor score predictors. Thus, higher factor score determinacy goes along with bias of the inter-correlations and unbiased inter-correlations go along with lower factor score determinacy. The aim of the present study was therefore to investigate the size of the trade-off between factor score determinacy and bias of inter-correlations by means of a simulation…
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Taxonomy
TopicsAdvanced Statistical Modeling Techniques · Mental Health Research Topics
