The bifactor model provides a valuable tool for exploring dimensionality related questions. In the Discussion, we describe contexts where a bifactor analysis is most productively used, and we contrast bifactor with multidimensional IRT models (MIRT). We also describe implications of bifactor models for IRT applications, and raise some limitations.

The current study aims to explore the usefulness of a person-centered perspective to the study of workplace affective commitment (WAC). Five distinct profiles of employees were hypothesized based on their levels of WAC directed toward seven foci (organization, workgroup, supervisor, customers, job, work, and career). This study applied latent profile analyses and factor mixture analyses to a sample of 404 Canadian workers. The construct validity of the extracted latent profiles was verified by their associations with multiple predictors (gender, age, tenure, social relationships at work, workplace satisfaction, and organizational justice perceptions) and outcomes (in-role performance, organizational citizenship behaviors, and intent to quit). The analyses confirmed that a model with five latent profiles adequately represented the data: (a) highly committed toward all foci; (b) weakly committed toward all foci; (c) committed to their supervisor and moderately committed to the other foci; and (d) committed to their career and moderately uncommitted to the other foci; (e) committed mostly to their proximal work environment. These latent profiles present theoretically coherent patterns of associations with the predictors and outcomes, which suggests their adequate construct validity.

Although most theories draw upon the construct of school engagement in their conceptualization of the dropout process, research addressing its hypothesized prospective relation with dropout remains scarce and does not account for the academic and social heterogeneity of students who leave school prematurely. This study explores the reality of different life-course pathways of school engagement and their predictive relations to dropout. Using an accelerated longitudinal design, we used growth mixture modeling to generate seven distinct trajectories of school engagement with 12-to 16-year-old students (N = 13,300). A vast majority of students were classified into three stable trajectories, distinguishing themselves at moderate to very high levels of school engagement. We refer to these as developmentally normative pathways in light of their frequent occurrence and stability. Although regrouping only one-tenth of participants, four other nonnormative (or unexpected pathways) accounted for the vast majority of dropouts. Dropout risk was closely linked with unstable pathways of school engagement. We conclude by debating the delicate investment balance between universal strategies and more selective and differentiated strategies to prevent dropout. We also discuss the need to better understand why, within normative trajectories, some students with high levels of school engagement drop out of school.From a production of human capabilities perspective, which shares its preoccupations across disciplines concerned with children's development (Heckman, 2006), our industrial era is as exciting as it is daunting. The constant evolution of knowledge and its concomitant technology poses great demands on learners and educational systems alike (OECD, 2006). Consequently, governments have become increasingly concerned with performance indicators and generating policies that will increase the quality of both academic and social learning, especially for culturally and economically disadvantaged populations (Heckman, 2006;OECD, 2006). The goal is successful output of qualified students at the most basic level

School-based interventions should address the multiple facets of high school experiences to help adolescents successfully complete their basic schooling. Creating a positive social-emotional learning environment promises better adolescent achievement and, in turn, will contribute to a healthier lifestyle.

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