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Planned missing data in early literacy interventions: A replication study with an additional gold standard

INTRODUCTION: In a digital early literacy intervention RCT, children born late preterm fell behind peers when in a control condition, but outperformed them when assigned to the intervention. Results did however not replicate previous findings. Replication is often complicated by resource quality. Go...

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Detalles Bibliográficos
Autores principales: Rippe, Ralph C. A., Merkelbach, Inge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8007029/
https://www.ncbi.nlm.nih.gov/pubmed/33780486
http://dx.doi.org/10.1371/journal.pone.0249175
Descripción
Sumario:INTRODUCTION: In a digital early literacy intervention RCT, children born late preterm fell behind peers when in a control condition, but outperformed them when assigned to the intervention. Results did however not replicate previous findings. Replication is often complicated by resource quality. Gold Standard measures are generally time-intensive and costly, while they closely align with, and are more sensitive to changes in, early literacy and language performance. A planned missing data approach, leaving these gold standard measures incomplete, might aid in addressing the origin(s) of non-replication. METHODS: Participants after consent were 695 p Dutch primary school pupils of normal and late preterm birth. The high-quality measures, in additional to simpler but complete measures, were intentionally administered to a random subsample of children. Five definitions of gold standard alignment were evaluated. RESULTS: Two out of five gold standard levels improved precision compared to the original results. The lowest gold standard level did not lead to improvement: precision was actually diminished. In two gold standard definitions, an alphabetical factor and a writing-only factor the model estimates were comparable to the original results. Only the most precise definition of the gold standard level replicated the original results. CONCLUSION: Gold standard measures could only be used to improve model efficiency in RCT-designs under sufficiently high convergent validity.