This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are compared. For IFA, diagonally weighted least squares and unweighted least squares estimations using items polychoric correlation matrices are compared. Two hundred and ten conditions were simulated in a Monte Carlo study considering: one to three factor structures (either, independent and correlated in two levels), medium or low quality of items, three different levels of item asymmetry and five sample sizes. Results showed that IFA procedures achieve equivalent and accurate parameter estimates; in contrast, FA procedures yielded biased parameter estimates. Therefore, we do not recommend classical FA under the conditions considered. Minimum requirements for achieving accurate results using IFA procedures are discussed.

Este artículo busca explicar el carácter explosivo de las fases iniciales de diversos ciclos de protestas (entre ellos el estallido social ocurrido en Chile en 2019). Para ello formulamos un modelo teórico que explica los estallidos sociales en función de la sintonización, sincronización y amplificación de la experiencia emocional que se produce en las interacciones sociales que ocurren en las protestas, las cuales podrían entenderse como espacios rituales. Este modelo lo evaluamos preliminarmente en un estudio cuantitativo realizado con jóvenes estudiantes universitarios. Los resultados muestran que experimentar intensamente emociones displacenteras se asocia a una mayor participación y a invitar a otros a participar. La experiencia de protestar se desarrolla en redes interpersonales fuertes, y participar produce emociones placenteras, las que se asocian a interpretar exitosamente la manifestación. Estos resultados confirman la importancia de las emociones y las interacciones sociales como elementos potenciadores del carácter explosivo de las fases iniciales de los ciclos de protestas.

Nowadays it is customary to incorporate emotions as explanatory variables of protest participation, since numerous studies have provided evidence for their relevance. However, the incorporation of emotions in quantitative research continues to emphasise the effect of a limited set of emotions (normally one or two with negative valence, such as anger or contempt) that are modelled as mediators between non-emotional motives and participation. This makes it difficult to test the joint effect that multiple emotions appear to have, as has been reported in qualitative research. The present research aims to address these gaps in the quantitative literature by applying structural equation modelling to a survey administered to a random sample of 500 inhabitants of a region of Chile in which a long cycle of territorial protests occurred. Our results confirm some hypotheses derived from qualitative research by showing that emotions are in fact experienced in arrays, that emotions with positive valence play a relevant role in explaining participation, and that several emotions mediate the effect of non-emotional motives and participation. It is also clear that emotions experienced by the population are significantly interrelated, thus a study of the direct or mediating effects of any given emotion must also address other emotions experienced intensely by subjects. This evidence could help to modify and improve the way in which emotions are integrated into formal quantitative models of protest participation.

The aim of this research was to evaluate the mediating effect of the value orientations of collectivism and individualism on the relationship between ethnic identity and well-being, the latter conceived from the worldview of Andean natives. For this purpose, under an observational and cross-sectional design, 395 Lickan-Antay adults (57% women) living in areas of indigenous development and in two cities in northern Chile were surveyed. We used the Lickan-Antay BLA32 well-being scale, a short version of the Portrait 21 Values Questionnaire to measure individualistic and collectivistic values, and an adapted version of the Ethnic Identity Scale. The results show that ethnic identity had a direct positive effect on all three dimensions of well-being (harmony with community life, ethnic harmony and harmony with nature), and total indirect effects on all five dimensions of well-being, one of them originating mainly from collectivist orientations. Individualistic orientations also showed a positive, though less intense, mediating effect on well-being. We conclude that collectivist and individualistic motivational patterns coexist in Lickan-Antay natives and explain an important part of the relationship between ethnic identity and well-being. Finally, we discuss our results and suggest replication of this study in other ethnic contexts to assess the generalizability of these findings to other native peoples of the Andean region of South America.

Use of subject scores as manifest variables to assess the relationship between latent variables produces attenuated estimates. This has been demonstrated for raw scores from classical test theory (CTT) and factor scores derived from factor analysis. Conclusions on scores have not been sufficiently extended to item response theory (IRT) theta estimates, which are still recommended for estimation of relationships between latent variables. This is because IRT estimates appear to have preferable properties compared to CTT, while structural equation modeling (SEM) is often advised as an alternative to scores for estimation of the relationship between latent variables. The present research evaluates the consequences of using subject scores as manifest variables in regression models to test the relationship between latent variables. Raw scores and three methods for obtaining theta estimates were used and compared to latent variable SEM modeling. A Monte Carlo study was designed by manipulating sample size, number of items, type of test, and magnitude of the correlation between latent variables. Results show that, despite the advantage of IRT models in other areas, estimates of the relationship between latent variables are always more accurate when SEM models are used. Recommendations are offered for applied researchers.

The idea that item response theory (IRT) models yield invariant parameter estimates is widely accepted among scholars interested in achieving truly scientific measurements in social and behavioral sciences. Starting from a conceptual and mathematical definition of invariance, this article presents a critical examination of the theoretical and empirical support for the property of invariance with regard to populations and samples of items and subjects by means of simulated data. The distinction between internal and external invariance is introduced to clarify the meaning and limitations of invariance in IRT models. Furthermore, the consequences of “giving in to the sirens’ call” of achieving invariant measurements in behavioral sciences are also discussed.