Analyser l’interaction de variables latentes : une exemplification méthodologique de la méthode d’équations structurelles avec interaction latente1
Bibliographic record
Abstract
Le présent article est une exemplification méthodologique de la méthode LMS (Latent Moderated Structural Equations) disponible dans le logiciel Mplus. Des données recueillies pour étudier la motivation d’adolescentes (n = 434) en éducation physique serviront à présenter la méthodologie à suivre pour évaluer l’interaction de variables latentes dans des modèles d’équations structurelles. Le texte focalise sur la compréhension générale du lecteur quant à l’application de cette méthode et un accent est mis sur la présentation et l’interprétation des résultats. En terminant, les avantages de la méthode LMS sont mis de l’avant et des pistes d’exemplifications méthodologiques sont proposées.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.047 | 0.136 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".