Evidence map›Paper›PMID 31689456›Full record

ArticleJournal of clinical epidemiology2020

Simulations and directed acyclic graphs explained why assortative mating biases the prenatal negative control design.

Paul Madley-Dowd, Dheeraj Rai, Stanley Zammit, Jon Heron

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In one paragraph

Article in Journal of clinical epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Paul Madley-DowdCentre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Biomedical Research Centre, University of Bristol, Bristol, UK. Electronic address: p.madley-dowd@bristol.ac.uk.
Dheeraj RaiCentre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Biomedical Research Centre, University of Bristol, Bristol, UK; Avon and Wiltshire Partnership NHS Mental Health Trust, Bristol, UK.
Stanley ZammitCentre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Biomedical Research Centre, University of Bristol, Bristol, UK; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK.
Jon HeronCentre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; NIHR Biomedical Research Centre, University of Bristol, Bristol, UK.

Funding

Department of HealthMedical Research Council G9815508Medical Research Council MC_PC_19009Medical Research Council MR/L010305/1Wellcome TrustWellcome Trust 203776/Z/16/A
6 · The paper itself

Abstract

objectiveThe negative control design can be used to provide evidence for whether a prenatal exposure-outcome association occurs by in utero mechanisms. Assortative mating has been suggested to influence results from negative control designs, although how and why has not yet been adequately explained. We aimed to explain why mutual adjustment of maternal and paternal exposure in regression models can account for assortative mating. STUDY DESIGN AND

settingWe used directed acyclic graphs to show how bias can occur when modeling maternal and paternal effects separately. We empirically tested our claims using a simulation study. We investigated how increasing assortative mating influences the bias of effect estimates obtained from models that do and do not use a mutual adjustment strategy.

resultsIn models without mutual adjustment, increasing assortative mating led to increased bias in effect estimates. The maternal and paternal effect estimates were biased by each other, making the difference between them smaller than the true difference. Mutually adjusted models did not suffer from such bias.

conclusionsMutual adjustment for maternal and paternal exposure prevents bias from assortative mating influencing the conclusions of a negative control design. We further discuss issues that mutual adjustment may not be able to resolve.

Indexed as

Models, StatisticalBiasComputer SimulationFemaleHumansMaleMaternal ExposurePaternal ExposurePregnancyPrenatal Exposure Delayed EffectsRegression AnalysisSmokingAssortative matingBiasCausal inferenceDirected acyclic graphsNegative controlPrenatalSimulation

Identifiers

PMID31689456
PMCPMC7001034

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.