Regression to the Mean: A Statistical Phenomenon of Worthy Consideration in Anemia Research
Bibliographic record
Abstract
BACKGROUND: Regression to the mean (RTM) is a statistical phenomenon where second measurements are more likely to be closer to the mean. This is particularly observed in those with baseline values further from the mean. Anemic individuals (hemoglobin <120 g/L) are often recruited when evaluating iron supplementation programs, as they are more likely to elicit a greater hemoglobin response; however, they are also at greater risk for RTM as their baseline values are lower than the overall population mean. OBJECTIVE: The aim was to calculate and apply RTM to a previously conducted iron supplementation trial of women in Cambodia at increasingly severe baseline anemia cutoffs (hemoglobin <120 g/L, <115 g/L, and <110 g/L). METHODS: = 185) for 12 wk. Hemoglobin was measured at baseline and at 12 wk (endline), and change in hemoglobin was calculated in each group for each cutoff. RTM was calculated in the placebo group at each cutoff and applied to the change observed at each cutoff in the iron group to obtain the RTM-free effect. RESULTS: In the placebo group, mean change in hemoglobin increased as cutoffs became more extreme (0.9 g/L to 1.9 g/L in those with baseline hemoglobin <120 g/L and <110 g/L, respectively). RTM estimates similarly increased: 1.0 g/L (<120 g/L), 1.3 g/L (<115 g/L), and 1.8 g/L (<110g/L). When applying RTM to the iron group, we found that ∼10% of the "treatment effect" could be attributable to RTM at each cutoff. However, iron supplementation was still effective in increasing hemoglobin, with an increased effect in those with lower baseline values, as proven by the RTM-free effect at each cutoff: 8.7 g/L (<120 g/L), 10.9 g/L (<115 g/L), and 13.6g/L (<110 g/L). CONCLUSIONS: RTM may have accounted for ∼10% of the observed change in hemoglobin following iron supplementation; however, appropriate use of a placebo group in the statistical analyses of the trial controls for this potential RTM effect.
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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 | 0.188 | 0.371 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.017 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".