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Although the dispute between formative models and reflective models is not exactly recent, it is still alive in current literature, largely in the context of structural equation model. There are many aspects of SEM that should be considered in deciding the right approach. This work is intended to be a brief presentation of the state of the art for SEM based on covariance matrices. I outline the different positions on five particular issues: causality, selection of observed measures, internal consistency, identifiability and measurement error.
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Stored only when both papers are in the corpus — 37 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.