Factor Scores in Small Samples: Recommendations and Solutions

Simultaneous estimation of structural and measurement models in structural equation modeling (SEM) is not always tenable in small samples. In such cases, it may be necessary or advantageous to obtain scores. Current scoring recommendations draw predominantly from simulations with sample sizes greater than N = 200. This paper extends these recommendations to small N, directly comparing factor scores to sum scores. In addition, scores computed from an essentially tau-equivalent factor model are introduced as an alternative scoring option aimed at balancing the competing benefits of sum scores and factor scores. Findings largely suggest that factor scores from an essentially tau-equivalent factor model are advantageous when considering convergence and stability, even when not supported by the data, so long as departures from their assumptions are not substantial. They are obtainable when congeneric factor models fail to converge and have similar correlations with true scores compared with typical factor scores in samples at or less than N = 200.