Why does the Dyad-4PNO model of Kern and Culpepper (2020) fit real data?

2020 · doi:10.31234/osf.io/razq9
preprint OA: closed CC-BY-4.0
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Abstract

This note aims to elucidate why the Dyad-4PNO model of Kern and Culpepper (2020) can be expected to fit real data reasonably well. The main result is that the Dyad-4PNO approximates a latent tree model. We offer a simple proof of identifiability, and draw some implications for psychological measurement in practice.

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europepmc
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License: CC-BY-4.0