Factor Analytic Models: Viewing the Structure of an Assessment Instrument From Three Perspectives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The overarching purpose of this article is to present a nonmathematical introduction to the application of confirmatory factor analysis (CFA) within the framework of structural equation modeling as it applies to psychological assessment instruments. In the interest of clarity and ease of understanding, I model exploratory factor analysis (EFA) structure in addition to first- and second-order CFA structures. All factor analytic structures are based on the same measuring instrument, the Beck Depression Inventory-II (BDI-II; Beck, Steer, & Brown, 1996). Following a "walk" through the general process of CFA modeling, I identify several common misconceptions and improper application practices with respect to both EFA and CFA and tender caveats with a view to preventing further proliferation of these pervasive practices.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it