Improving the reliability of the Reliable Change Index
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 reliable change index (RCI) is a tool for evaluating change at the individual level. It compliments standard group-level change estimates and is central to evaluating clinical significance for interventions. In principle, the RCI provides common criteria for evaluating individual change. However, current practices use sample-specific estimates to create these criteria. Because sample estimates are subject to sampling error, these criteria are also subject to sampling error and therefore differ across studies. We illustrate how current practices can lead to differing criteria for reliable change and use simulations to identify the impact of sampling error on the RCI. Excessive error in the RCI began for the average sample when N < 30, and samples only comfortably avoided the risk of excessive error when N > 100. Finally, small errors in estimating a measure’s reliability sometimes had profound effects on the RCI. Recommendations on use of the RCI are provided.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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