Abstract
The application of mean and covariance structure analysis with quantitative data is increasing. However, latent means analysis with qualitative data is not as widespread. This article summarizes the procedures to conduct an analysis of latent means of dichotomous data from an item response theory approach. We illustrate the implementation of these procedures in an empirical example referring to the organizational context, where a multi-group analysis was conducted to compare the latent means of three employee groups in two factors measuring personal preferences and the perceived degree of rewards from the organization. Results show that higher personal motivations are associated with higher perceived importance of the organization, and that these perceptions differ across groups, so that higher-level employees have a lower level of personal and perceived motivation. The article shows how to estimate the factor means and the factor correlation from dichotomous data, and how to assess goodness of fit. Lastly, we provide the M-Plus syntax code in order to facilitate the latent means analyses for applied researchers.
