ABCal: a Python package for Author Bias Computation and Scientometric Plotting for Reviews and Meta-Analyses

Systematic reviews are critical summaries of the exiting literature on a given subject and, when combined with meta-analysis, provides a quantitative synthesis of evidence to direct and inform future research. Such reviews must, however, account for complex sources of between study heterogeneity and...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:bioRxiv
Hlavný autor: Le Clercq, L.S.
Médium: Paper
Jazyk:English
Vydavateľské údaje: Cold Spring Harbor Cold Spring Harbor Laboratory Press 09.11.2023
Cold Spring Harbor Laboratory
Vydanie:1.1
Predmet:
Bias
Geographical distribution
Reviews
Scientific Communication and Education
Scientometrics
Plots
Scientometrics
Reviews
Bias detection
Authorship
Author bias
ISSN:2692-8205, 2692-8205
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Systematic reviews are critical summaries of the exiting literature on a given subject and, when combined with meta-analysis, provides a quantitative synthesis of evidence to direct and inform future research. Such reviews must, however, account for complex sources of between study heterogeneity and possible sources of bias, such as publication bias. This paper presents the methods and results of a research study using a newly developed software tool called ABCal (version 1.0.2) to compute and assess author bias in the literature, providing a quantitative measure for the possible effect of overrepresented authors introducing bias to the overall interpretation of the literature. ABCal includes a new metric referred to as author bias, which is a measure of potential biases per paper when the frequency or proportions of contributions from specific authors are considered. The metric is able to account for a significant portion of the observed heterogeneity between studies included in meta-analyses. A meta-regression between observed effect measures and author bias values revealed that higher levels of author bias were associated with higher effect measures while lower author bias was evident for studies with lower effect measures. Furthermore, the software's capabilities to analyse authorship contributions and produce scientometric plots was able to reveal distinct patterns in both the temporal and geographic distributions of publications, which may relate to any evident publication bias. Thus, ABCal can aid researchers in gaining a deeper understanding of the research landscape and assist in identifying both key contributors and holistic research trends.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://github.com/LSLeClercq/ABCal
Bibliografia:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
Competing Interest Statement: The authors have declared no competing interest.
ISSN:2692-8205
2692-8205
DOI:10.1101/2023.11.07.565991