Evidence map›Paper›PMID 35312926›Full record

ArticleEuropean journal of epidemiology2022

Generalizability and effect measure modification in sibling comparison studies.

Arvid Sjölander, Sara Öberg, Thomas Frisell

Abstract read
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Article in European journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–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

24 citing papers in PubMed.

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  8. First trimester antidepressant use and miscarriage: a population-based cohort study using Clinical Practice Research Datalink GOLD.The British journal of general practice : the journal of the Royal College of General Practitioners · 2025
    Article
  9. Article
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  15. Maternal early pregnancy body mass index and risk of sleep apnea in the offspring.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024
    Article
  16. Article
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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

3 authors.

Arvid SjölanderKarolinska Institutet, Nobels väg 12 A, 171 77, Stockholm, Sweden. arvid.sjolander@ki.se.ORCID http://orcid.org/0000-0001-5226-6685
Sara ÖbergKarolinska Institutet, Nobels väg 12 A, 171 77, Stockholm, Sweden.
Thomas FrisellKarolinska Institutet, Maria Aspmans Gata 30A, 17164, Solna, Sweden.

Funding

Vetenskapsrådet 2016-01355Vetenskapsrådet 2020-01188
6 · The paper itself

Abstract

Sibling comparison studies have the attractive feature of being able to control for unmeasured confounding by factors that are shared within families. However, there is sometimes a concern that these studies may have poor generalizability (external validity) due to the implicit restriction to families that are covariate-discordant, i.e., those families where at least two siblings have different levels of at least one of the covariates (exposure or confounders) under investigation. Even if this selection mechanism has been noted by many authors, previous accounts of the problem tend to be brief. The purpose of this paper is to provide a formal discussion of the implicit restriction to covariate-discordant families in sibling comparison studies. We discuss when and how this restriction may impair the generalizability of the study, and we show that a similar generalizability problem may in fact arise even when all families are covariate-discordant, e.g. even if the exposure is continuous so that all siblings have different exposure levels. We show how this problem can be solved by using a so-called marginal between-within model for estimation of marginal exposure effects. Finally, we illustrate the theoretical conclusions with a simulation study.

Indexed as

SiblingsComputer SimulationHumansBiasCausal inferenceEffect measure modificationSibling comparison study

Identifiers

PMID35312926
PMCPMC9209381

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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.