As the most frequently used tool for measuring empathy, the Interpersonal Reactivity Index (IRI) is often scored by researchers arbitrarily and casually. Many commonly used IRI scoring approaches and their corresponding measurement models are unverified, which may make the conclusions of subsequent variable relation studies controversial and even misleading. We make the first effort to summarize these measurement models and to evaluate rationality of the common scoring methods of the IRI by confirmatory factor analysis, focusing on model fitting, factor loading, and model-based reliability simultaneously. The results show that most of these models do not fit well, indicating that the scoring approaches of the IRI corresponding to these models may be problematic. Relatively speaking, better scoring approaches of the IRI include summing empathic concern (EC) and perspective taking (PT) as the total score of the IRI and reporting the score of PT as cognitive empathy.

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Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is often found to be substantially better than that of ICM-CFA. The present study first illustrated the method used to estimate composite reliability under ESEM and then compared the difference between ESEM and ICM-CFA in terms of composite reliability estimation under various indicators per factor, target factor loadings, cross-loadings, and sample sizes. The results showed no apparent difference in using ESEM or ICM-CFA for estimating composite reliability, and the rotation type did not affect the composite reliability estimates generated by ESEM. An empirical example was given as further proof of the results of the simulation studies. Based on the present study, we suggest that if the model fit of ESEM (regardless of the utilized rotation criteria) is acceptable but that of ICM-CFA is not, the composite reliability estimates based on the above two models should be similar. If the target factor loadings are relatively small, researchers should increase the number of indicators per factor or increase the sample size.

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