Bayesian Methods for Exposure Misclassification Adjustment in a Mediation Analysis
Bibliographic record
Abstract
BACKGROUND: Soil-transmitted helminth infections have been found to be associated with child development. The objective was to investigate hemoglobin levels and malnutrition as mediators of the association between Ascaris infection and intelligence quotient (IQ) scores in children. METHODS: We conducted a longitudinal cohort study in Iquitos, Peru, between September 2011 and July 2016. A total of 1760 children were recruited at 1 year of age and followed up annually to 5 years. We measured Ascaris infection and malnutrition at each study visit, and hemoglobin levels were measured as of age 3. The exposure was defined as the number of detected Ascaris infections between age 1 and 5. We measured IQ scores at age 5 and used Bayesian models to correct exposure misclassification. RESULTS: We included a sample of 781 children in the analysis. In results adjusted for Ascaris misclassification, mean hemoglobin levels mediated the association between Ascaris infection and IQ scores. The natural direct effects (not mediated by hemoglobin) (95% CrI) and natural indirect effects (mediated by hemoglobin) (95% CrI) were compared with no or one infection: -0.9 (-4.6, 2.8) and -4.3 (-6.9, -1.6) for the effect of two infections; -1.4 (-3.8, 1.0) and -1.2 (-2.0, -0.4) for three infections; and -0.4 (-3.2, 2.4) and -2.7 (-4.3, -1.0) for four or five infections. CONCLUSION: Our results are consistent with the hypothesis that hemoglobin levels mediate the association between Ascaris infection and IQ scores. Additional research investigating the effect of including iron supplements in STH control programs is warranted.
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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 | 0.248 | 0.358 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.013 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.012 | 0.007 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.023 | 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".