Practice of Epidemiology Assessment of Selection Bias in the Canadian Case-Control Study of Residential Magnetic Field Exposure and Childhood Leukemia
Bibliographic record
Abstract
The authors evaluated the role of selection bias in the 1999 Canadian case-control study of residential magnetic field exposure and childhood leukemia. They included cases, participating controls, and first-choice nonparticipat-ing controls in their analyses. Exposure was assessed by wire coding, a classification system based on the distribution line characteristics near homes. Although an imperfect measure of magnetic field exposure, wire coding is the only method applicable to nonparticipating subjects. First-choice nonparticipant controls tended to be of lower socioeconomic status than their replacements (non-first-choice participant controls), and lower socio-economic status was related to higher wire code categories. The odds ratios for developing childhood leukemia in the highest exposure category were 1.6 (95 % confidence interval: 1.0, 2.6) when the actual participating controls were used and 1.3 (95 % confidence interval: 0.8, 2.1) when the first-choice ideal controls were used, regardless of their participation. Overall, the authors conclude that, although there is some evidence for control selection or participation bias in the Canadian study, it is unlikely to explain entirely the observed association betweenmagnetic field exposure and childhood leukemia. Inherent problems in exposure assessment for nonparticipating subjects, however, limit the interpretations of these results, and the role of selection bias cannot entirely be dismissed on the basis of these results alone. case-control studies; child; electromagnetic fields; epidemiologic methods; leukemia; selection bias
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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 | 0.447 | 0.674 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".