The proposed seasonal growth model combines polynomial terms for year-to-year growth with piecewise terms for within-year gains and losses¶
Claim · All claims
Evidence · 1 study · designr?·q2
Currency · newest study 2022 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? The model integrates polynomial terms that estimate year-to-year growth with piecewise terms that directly estimate within-year gains and losses. → James Soland 2022
Evidence¶
James Soland 2022¶
James Soland, Yeow Meng Thum. (2022). Estimating and comparing growth using longitudinal interim achievement data with seasonal trends. Journal of Research on Educational Effectiveness 15(3) 635-654. https://doi.org/10.1080/19345747.2021.2018744
q2 · i? · design · r?
Definitional statement of the model's design from the abstract: it combines polynomial features estimating "year-to-year growth" with piecewise features that "directly estimate within-year gains/losses." This is a design description, not a measured comparison.
"The model is designed to combine features from traditional polynomial models that estimate year-to-year growth but ignore within-year gains and losses with those from piecewise models, which directly estimate within-year gains/losses but do not include terms for year-to-year growth."
Discussion¶
Related Claims¶
- Interim achievement data exhibit distinctly seasonal patterns that few existing statistical models can approximate — related
- Across 90 grade-subject-level conditions, the three-piece piecewise model showed the lowest deviance for 64% of student-level and 78% of school-level models, outperforming both compound polynomial candidates — related
- The 2025 MAP Growth norms adopted a two-year, two-level piecewise mixed-effects design because two consecutive years of data are sufficient for within-year and adjacent-year growth norms — related
- Ignoring summer loss can impact which schools are identified as low performers under federal accountability — related
- Mean achievement in the studied cohort shows a saw-tooth seasonal pattern, with within-year gains followed by summer declines (summer learning loss) — related
- The CP model fits seasonal achievement data better than a traditional polynomial growth model on RMSE, AIC, and BIC while reducing residual autocorrelation — a narrower finding that bears on this claim
- Seasonality affects estimates of school effectiveness — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
seasonal-model-combines-polynomial-and-piecewise-features |
title |
The proposed seasonal growth model combines polynomial terms for year-to-year growth with piecewise terms for within-year gains and losses |
description |
The proposed seasonal growth model combines polynomial terms for year-to-year growth with piecewise terms for within-year gains and losses |
status |
review |
evidence_strength |
weak |
newest_evidence |
2022 |
generated |
by process:wiki-ingest on 2026-10-08 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — james-soland-2022 |
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