Evidence map›Paper›PMID 22499727›Full record

ArticleThe international journal of biostatistics2012

Designs combining instrumental variables with case-control: estimating principal strata causal effects.

Russell T Shinohara, Constantine E Frangakis, Elizabeth Platz, Konstantinos Tsilidis

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The international journal of biostatistics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Russell T ShinoharaJohns Hopkins University, Baltimore, MD, USA.
Constantine E Frangakis
Elizabeth Platz
Konstantinos Tsilidis

Funding

EPIDEMIOLOGY AND BIOSTATISTICS OF AGINGT32AG000247 · NIA · JOHNS HOPKINS UNIVERSITY · PI Karen J. Bandeen-Roche · 1996 to 2026
$13.2M
Research Infrastructure for the Hopkins Population CenterR24HD042854 · NICHD · JOHNS HOPKINS UNIVERSITY · PI HAO, LINGXIN · 2003 to 2017
$5.1M
Statistical Designs and Methods for Partially Controlled HIV/AIDS StudiesR01DA023879 · NIDA · JOHNS HOPKINS UNIVERSITY · PI FRANGAKIS, CONSTANTINE E · 2007 to 2010
$1.3M
NIA NIH HHS T32 AG000247NICHD NIH HHS R24 HD042854NIDA NIH HHS R01 DA023879
6 · The paper itself

Abstract

The instrumental variables framework is commonly used for the estimation of causal effects from cohort samples. However, the combination of instrumental variables with more efficient designs such as case-control sampling requires new methodological consideration. For example, as the use of Mendelian randomization studies is increasing and the cost of genotyping and gene expression data can be high, the analysis of data gathered from more cost-effective sampling designs is of prime interest. We show that the standard instrumental variables analysis does not appropriately estimate the causal effects of interest when the instrumental variables design is combined with the case-control design. We also propose a method that can estimate the causal effects in such combined designs. We illustrate the method with a study in oncology.

Indexed as

AgedBiostatisticsCase-Control StudiesCausalityCohort StudiesColorectal NeoplasmsC-Reactive ProteinData CollectionFemaleHumansMaleMiddle AgedModels, StatisticalPolymorphism, Single NucleotideRandom AllocationC-Reactive Protein

Identifiers

PMID22499727
PMCPMC3608098

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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.