Quadratic latent growth fits MAP longitudinal achievement data better than linear growth across ten states¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2013 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? In nested MLGM comparisons, all BIC differences between quadratic and linear models exceeded 10 in both reading and mathematics, favouring the quadratic model. → Wang 2013

Evidence¶

Wang 2013¶

Wang, S., Jiao, H. and Zhang, L. (2013) 'Validation of longitudinal achievement constructs of vertically scaled computerised adaptive tests: a multiple-indicator, latent-growth modelling approach', Int. J. Quantitative Research in Education, Vol. 1, No. 4, pp.383–407. https://www.nwea.org/research/publication/validation-of-longitudinal-achievement-constructs-of-vertically-scaled-computerised-adaptive-tests-a-multiple-indicator-latent-growth-modelling-approach/ doi:10.1504/ijqre.2013.058307

q2 · i? · associational · r2

Nested model comparisons of linear versus quadratic MLGM fitted to MAP reading and mathematics data in ten states, using AIC, BIC and χ2 difference tests. The article reports "all differences between quadratic and linear models are greater than 10" on BIC; no effect size is printed.

"For BIC, all differences between quadratic and linear models are greater than 10 in both reading and mathematics, which indicate that the quadratic model fits the data better than the linear model."

Discussion¶

Related Claims¶

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