Evidence map›Paper›PMID 30067828›Full record

ArticlePloS one2018

Dissemination of novel biostatistics methods: Impact of programming code availability and other characteristics on article citations.

Amy E Wahlquist, Lutfiyya N Muhammad, Teri Lynn Herbert, Viswanathan Ramakrishnan, Paul J Nietert

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Amy E WahlquistDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America.ORCID 0000-0002-6134-0573
Lutfiyya N MuhammadDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America.
Teri Lynn HerbertDepartment of Library Science and Informatics, Medical University of South Carolina, Charleston, SC, United States of America.ORCID 0000-0002-6120-0423
Viswanathan RamakrishnanDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America.
Paul J NietertDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States of America.

Funding

Subproject Title: Clinical Research Education, Mentoring and Career Development CoreU54GM104941 · NIGMS · UNIVERSITY OF DELAWARE · PI Robert E Akins · 2013 to 2026
$60.5M
South Carolina Clinical & Translational Research Institute (SCTR)UL1TR001450 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T., FLUME, PATRICK A · 2015 to 2024
$41.1M
Resource CoreP30AR072582 · NIAMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI JAMES C OATES · 2017 to 2026
$8.5M
MUSC Minority Student Development ProgramR25GM072643 · NIGMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ERGUL, ADVIYE, RINKER, JENNIFER ANNE · 2005 to 2023
$5.8M
NCATS NIH HHS UL1 TR001450NIAMS NIH HHS P30 AR072582NIGMS NIH HHS R25 GM072643NIGMS NIH HHS U54 GM104941
6 · The paper itself

Abstract

backgroundAs statisticians develop new methodological approaches, there are many factors that influence whether others will utilize their work. This paper is a bibliometric study that identifies and quantifies associations between characteristics of new biostatistics methods and their citation counts. Of primary interest was the association between numbers of citations and whether software code was available to the reader.

methodsStatistics journal articles published in 2010 from 35 statistical journals were reviewed by two biostatisticians. Generalized linear mixed models were used to determine which characteristics (author, article, and journal) were independently associated with citation counts (as of April 1, 2017) in other peer-reviewed articles.

resultsOf 722 articles reviewed, 428 were classified as new biostatistics methods. In a multivariable model, for articles that were not freely accessible on the journal's website, having code available appeared to offer no boost to the number of citations (adjusted rate ratio = 0.96, 95% CI = 0.74 to 1.24, p = 0.74); however, for articles that were freely accessible on the journal's website, having code available was associated with a 2-fold increase in the number of citations (adjusted rate ratio = 2.01, 95% CI = 1.30 to 3.10, p = 0.002). Higher citation rates were also associated with higher numbers of references, longer articles, SCImago Journal Rank indicator (SJR), and total numbers of publications among authors, with the strongest impact on citation rates coming from SJR (rate ratio = 1.21 for a 1-unit increase in SJR; 95% CI = 1.11 to 1.32).

conclusionThese analyses shed new insight into factors associated with citation rates of articles on new biostatistical methods. Making computer code available to readers is a goal worth striving for that may enhance biostatistics knowledge translation.

Indexed as

BibliometricsBiostatisticsLinear ModelsPublications

Identifiers

PMID30067828
PMCPMC6070251

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.