RI-CLPMs control unmeasured time-invariant covariates better than CLPMs, but neither controls unmeasured time-varying covariates well¶
Claim · All claims
Evidence · 1 study · associationalr2·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? Unmeasured time-invariant covariates affect RI-CLPM trait factors but not the within-person autoregressive factors used to test directional ordering, giving RI-CLPMs an interpretational advantage over CLPMs. → Herbert W. Marsh 2022
Evidence¶
Herbert W. Marsh 2022¶
Herbert W. Marsh, Reinhard Pekrun, & Oliver Lüdtke. (2022). Directional Ordering of Self-Concept, School Grades, and Standardized Tests Over Five Years: New Tripartite Models Juxtaposing Within- and Between-Person Perspectives. Educational Psychology Review. https://doi.org/10.1007/s10648-022-09662-9
q2 · i? · associational · r2
Methodological exposition (type d/e) in the section on the role of covariates, explaining the RI-CLPM's statistical independence of random intercepts and within-person components. The article notes "both models provide limited protection concerning unmeasured time-varying covariates."
"Thus, unmeasured (undecomposed between-person) time-invariant covariates might affect the sizes of the (decomposed between-person) global trait factors. However, they do not affect the within-person autoregressive factors used to test directional ordering"
Discussion¶
Related Claims¶
- Adding lag-2 paths to CLPMs substantially improves fit and provides stronger controls for preexisting differences, positioning extended CLPMs as viable alternatives to RI-CLPMs — related
- Simulation evidence shows RI-CLPM estimates are biased when the true model is a CLPM with lag-2 effects, and fit statistics cannot decide between the two — related
- Across basic and extended RI-CLPMs and CLPMs of five-wave secondary-school data, math self-concept and achievement show consistent reciprocal (bidirectional) directional ordering — related
- With young primary-school readers, REM support appeared in CLPMs but not RI-CLPMs, motivating tests with older students — related
- The RI-CCLPM-C indicates a positive self-concept effect on achievement even when data are generated without any direct effects between self-concept and achievement — related
- Reanalyses of simulated and PALMA data provide converging support for the extended reciprocal effects model, including an effect of academic self-concept on achievement — related
- The extended REM was robust to several alternative modeling specifications proposed by Sorjonen et al. — related
- Random-intercept and lag2 panel models rest on different assumptions and offer alternative perspectives on controlling covariates — related
- RI-CLPM random-intercept correlations between grades and emotions (median |r| = 0.46) were stronger than the undecomposed CLPM correlations (median |0.34|) — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
ri-clpm-unmeasured-covariate-control |
title |
RI-CLPMs control unmeasured time-invariant covariates better than CLPMs, but neither controls unmeasured time-varying covariates well |
description |
RI-CLPMs control unmeasured time-invariant covariates better than CLPMs, but neither controls unmeasured time-varying covariates well |
status |
review |
evidence_strength |
weak |
newest_evidence |
2022 |
generated |
by process:wiki-ingest on 2026-10-19 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — herbert-w-marsh-2022 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.