Evidence map›Paper›PMID 29268794›Full record

ArticlePopulation health metrics2017

Multivariable regression analysis of list experiment data on abortion: results from a large, randomly-selected population based study in Liberia.

Heidi Moseson, Caitlin Gerdts, Christine Dehlendorf, Robert A Hiatt, Eric Vittinghoff

Abstract readControlled Clinical Trial
PubMed Full text at PMC Publisher
In one paragraph

Article in Population health metrics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Estimating Prevalence of Abortion Using List Experiments: Findings from a Survey of Women in Delaware and Maryland.Women's health issues : official publication of the Jacobs Institute of Women's Health
    Article
  7. Article
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

5 authors.

Heidi MosesonDepartment of Epidemiology & Biostatistics, University of California, San Francisco, USA. hmoseson@gmail.com.ORCID 0000-0002-2488-2429
Caitlin GerdtsIbis Reproductive Health, 1330 Broadway St, Suite 1100, Oakland, CA, 94612, USA.
Christine DehlendorfDepartment of Family & Community Medicine, University of California, San Francisco, USA.
Robert A HiattDepartment of Epidemiology & Biostatistics, University of California, San Francisco, USA.
Eric VittinghoffDepartment of Epidemiology & Biostatistics, University of California, San Francisco, USA.

Funding

Social support and pregnancy outcomes in early adulthoodF31HD083017 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MOSESON LIDOW, HEIDI SERENE · 2015 to 2017
$97k
Eunice Kennedy Shriver National Institute of Child Health and Human Development 5F31HD083017-02NICHD NIH HHS F31 HD083017Society for Family Planning SFPRF7-S3
6 · The paper itself

Abstract

backgroundThe list experiment is a promising measurement tool for eliciting truthful responses to stigmatized or sensitive health behaviors. However, investigators may be hesitant to adopt the method due to previously untestable assumptions and the perceived inability to conduct multivariable analysis. With a recently developed statistical test that can detect the presence of a design effect - the absence of which is a central assumption of the list experiment method - we sought to test the validity of a list experiment conducted on self-reported abortion in Liberia. We also aim to introduce recently developed multivariable regression estimators for the analysis of list experiment data, to explore relationships between respondent characteristics and having had an abortion - an important component of understanding the experiences of women who have abortions.

methodsTo test the null hypothesis of no design effect in the Liberian list experiment data, we calculated the percentage of each respondent "type," characterized by response to the control items, and compared these percentages across treatment and control groups with a Bonferroni-adjusted alpha criterion. We then implemented two least squares and two maximum likelihood models (four total), each representing different bias-variance trade-offs, to estimate the association between respondent characteristics and abortion.

resultsWe find no clear evidence of a design effect in list experiment data from Liberia (p = 0.18), affirming the first key assumption of the method. Multivariable analyses suggest a negative association between education and history of abortion. The retrospective nature of measuring lifetime experience of abortion, however, complicates interpretation of results, as the timing and safety of a respondent's abortion may have influenced her ability to pursue an education.

conclusionOur work demonstrates that multivariable analyses, as well as statistical testing of a key design assumption, are possible with list experiment data, although with important limitations when considering lifetime measures. We outline how to implement this methodology with list experiment data in future research.

Indexed as

Abortion, InducedDisclosureResearch DesignSurveys and QuestionnairesAdultFemaleHumansLiberiaMultivariate AnalysisPregnancyRegression AnalysisRetrospective StudiesYoung AdultAbortionDesign effectFamily planningItem count techniqueLiberiaList experimentMethodsMultivariable regression analysis

Identifiers

PMID29268794
PMCPMC5740939

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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.