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Record W2588941913 · doi:10.1097/ede.0000000000000445

The Authors Respond

2016· letter· en· W2588941913 on OpenAlexaffabout
Charles Poole, Ian Shrier, Peng Ding, Tyler J. VanderWeele

Bibliographic record

VenueEpidemiology · 2016
Typeletter
Languageen
FieldMathematics
TopicAdvanced Causal Inference Techniques
Canadian institutionsMcGill UniversityJewish General Hospital
FundersNational Institute of Environmental Health Sciences
KeywordsHomogeneity (statistics)Odds ratioStatisticsStatisticMathematicsEconometricsSample size determinationStatistical hypothesis testingType I and type II errorsMedicinePsychology

Abstract

fetched live from OpenAlex

We thank Schmidt et al.1 for contributing their recent article and letter2 to the literature on heterogeneity of difference and ratio effect measures. The letter wisely emphasizes the relevance of structural limits on the risk difference (RD). Indeed, if RD = −0.30 among women and unexposed men have a risk of 0.20, RD homogeneity is impossible. The simulation results1 for the Q test statistic would be most relevant to the meta-analytic evidence we reviewed.3 With small sample sizes or small fractions of doubly exposed individuals, test size was greater than alpha in the RD homogeneity tests and less than alpha in the tests of odds ratio (OR) homogeneity. This disparity would push the power to detect heterogeneity upward for the RD tests and downward for the OR tests, a result consistent with our conjecture that differential power might be part of the explanation. Two of us (PD, TJV) are engaged in related methodologic work that has mathematically assessed the three-dimensional volume in the four-dimensional space (of the four outcome probabilities under the different exposure combinations) for which homogeneity holds on the risk difference, risk ratio, and OR scales. The respective volumes are 1.33 for the risk difference, 1.76 for the risk ratio, and 2.47 for the OR scale.4 Thus, relatively speaking, there are more values of the outcome probabilities for which OR homogeneity holds than risk ratio homogeneity and more values for which risk ratio homogeneity holds than risk difference homogeneity. However, these are simply mathematical statements over all possible outcome probabilities. The real question is what values the outcome probabilities take empirically with actual exposures and outcomes and how closely these probabilities approximate homogeneity on different scales. We are thus heartened by the agreement on the part of Schmidt et al.1 that the ultimate question is empirical and not theoretical. The suggestion to shun the RD has been made in the belief that it is usually much more heterogeneous than ratio measures such as the OR in empirical research settings. Although there are more heterogeneous possibilities for the RD than for the OR, it would be difficult to defend the assumption that each of those possibilities has the same probability, within or across the many studies that are actually conducted. As noted in our article,3 further evidence is therefore required before concluding that the risk difference is in fact a more heterogeneous measure. Charles Poole Department of Epidemiology Gillings School of Global Public Health University of North Carolina Chapel Hill, NC Ian Shrier Centre for Clinical Epidemiology Lady Davis Institute for Medical Research Jewish General Hospital McGill University Montreal, QC, Canada Peng Ding Departments of Epidemiology and Statistics Harvard University Cambridge, MA Tyler VanderWeele Departments of Epidemiology and Biostatistics Harvard T.H. Chan School of Public Health Harvard University Boston, MA [email protected]

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.061
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.348
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.061
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.424
GPT teacher head0.510
Teacher spread0.085 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations3
Published2016
Admission routes2
Has abstractyes

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