ArticleHeliyon2023
Dangers of including outcome at baseline as a covariate in latent change score models: Results from simulations and empirical re-analyses.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- The latent difference score model is a viable alternative to arithmetic difference score-based anchor-driven minimal important change calculation.Journal of patient-reported outcomes · 2026Trial
- Inconclusive mutually reinforcing effects between associative learning and fluid intelligence: simulated reanalyses and a comment on Ren et al. (2026).Frontiers in psychology · 2026Article
- Teachers' and Parents' Assessments of Primary School Children's Intellectual Investment as Predictors of Change in Need for Cognition.Journal of Intelligence · 2025Article
- Corrigendum: Curiosity does help to protect against anxiety and depression symptoms but not conversely.Journal of affective disorders · 2023Article
- Regression to the mean in latent change score models: an example involving breastfeeding and intelligence.BMC pediatrics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Latent change score modeling is a type of structural equation modeling used for estimating change over time. Often change is regressed on the initial value of the outcome variable. However, similarly to other regression analyses, this procedure may be susceptible to regression to the mean. The present study employed simulations as well as re-analyses of previously published data, claimed to indicate reciprocal promoting effects of vocabulary and matrix reasoning on each other's longitudinal development. Both in simulations and empirical re-analyses, when adjusting for initial value on the outcome, latent change score modeling tended to indicate an effect of a predictor on the change in an outcome even when no change had taken place. Furthermore, analyses tended to indicate a paradoxical effect on change both forward and backward in time. We conclude that results from latent change score modeling are susceptible to regression to the mean when adjusting for the initial value on the outcome. Researchers are recommended not to regress change on the initial value included in the calculation of the change score when employing latent change score modeling but, instead, to define this parameter as a covariance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.