Medical research is the core of clinical practice and its advancements, eventually
leading to evidence-based practices. In any academic writing, a statistician is involved
in various stages of research, from the initial planning phase to the final analysis,
to ensure accuracy and transparency in scholarly manuscripts.[1] Biostatistics is
a pivotal tool in any biomedical research, and inadequate knowledge of biostatistical
fundamentals can have far-reaching consequences, even incorrect method selection or
misrepresentation of data.[2,3] We assessed the current state of statistical analysis
in research papers published in the Indian Journal of Anaesthesia (IJA) by a Google
survey-based questionnaire. The primary objective was to gain insight into how authors
engaged with statistical analysis, collaborated with a statistician, their training
in statistics and their confidence in interpreting the statistical observations.
Data for this was collected over one month by sending a survey questionnaire of 10
questions to 44 random corresponding authors of original research articles recently
published in IJA, using Google Forms to collect responses. The survey questions were
pre-validated by experts with vast experience in research and biostatistics. Each
question was strategically prepared to explore various aspects of statistical analysis
in research papers. The participants were informed about the anonymity and confidentiality
of all responses to the survey. Out of 44 authors contacted via email, 20 participants
responded. After completing the study, we downloaded the data into a Microsoft Excel
sheet and summarised the data by radar charting [Figure 1].
Figure 1
Summary of survey findings
The study revealed that collaboration with statisticians is widespread among authors.
Among the respondents, 36% involved the statistical department of their institutes,
while 40% engaged private statisticians. This diversity in collaboration strategies
highlights the acknowledgement of the complexity inherent in statistical analysis.[4
5
6
7
8] Moreover, 24% of participants conducted statistical analysis themselves, demonstrating
their willingness to be deeply involved in research methodology using basic and advanced
statistical techniques. Authors with varying levels of statistical knowledge bring
different perspectives to research, which is a good thing. It means they can offer
unique and valuable insights.[6
7
8
9] A significant observation from the study was that a substantial number of authors
(72%) lacked formal training or coursework in statistics, with only 22% having completed
relevant coursework or formal statistical training. This observation prompts early
collaboration with experts in biostatistics.[6
7
8
9
10] Nevertheless, it underscores a distinct requirement for enhanced statistical education,
especially within medical research. Enhancing statistical literacy among authors can
lead to better informed decisions during study design, data collection and analysis,
ultimately improving the research quality.[8
9
10
11
12]
The authors’ varied confidence levels in interpreting and communicating statistical
results were another notable aspect of the study. Although most respondents indicated
a moderate confidence level, there was some variability in their responses.[13
14
15
16] Addressing this inconsistency through targeted training and support from journals
can empower authors to engage more effectively with statistical methodologies. The
study further revealed that many authors have been asked to provide additional resources
and justification for the statistical analysis used in their research. This common
occurrence underscores the rigorous scrutiny of research papers.[14
15
16
17] Furthermore, insufficient comprehension of the mathematical principles underpinning
statistical techniques and statistical fundamentals may result in inappropriate utilisation
of software packages and data errors, necessitating reanalysis of statistical data
during the review process.[16
17
18
19
20]
We also explored authors’ perspectives on recognising statisticians in research publications.
Most respondents (64%) favoured acknowledging statisticians in the acknowledgement
section of research papers. However, 20% considered statisticians eligible for co-authorship.
Acknowledgement follows established ethical norms and recognises statisticians’ assistance
without assigning authorship.[8-11] Conversely, co-authorship signifies statisticians’
substantial contribution and collaborative role in the research.[12
13
14
15
16
17] The nuanced viewpoints emphasise the importance of transparent communication between
authors and statisticians to ensure that recognition aligns with the nature and extent
of their involvement.[5,6,18
19
20
21] It is worth noting that there may be constraints or guidelines for naming statisticians
as co-authors, which could potentially hinder collaboration. Nevertheless, collaborative
efforts between researchers and statisticians are critical for ensuring robust study
designs, accurate analyses and meaningful interpretations.[22]
Authors should view the feedback provided by reviewers or editors as an opportunity
to improve the clarity and comprehensiveness of their statistical methods sections.[5
6
7,9,11
12
13
14
15
16
17] By providing comprehensive descriptions of statistical analyses, authors can ensure
that readers and reviewers can assess the robustness of the study design and validity
of the conclusions drawn.[4
5
6
7
8
9
10
11,19,23,24] Transparent reporting enhances research credibility and contributes to
scientific knowledge advancement.[22
23
24]
The study's limitations include a restricted survey of only corresponding authors
from IJA, potentially not representing all authors’ perspectives, and a small sample
size. Expanding the study to authors from a broader range of journals could yield
more comprehensive insights.
In conclusion, the survey highlights several essential aspects of the collaboration
of statisticians, authors and research publications. Collaboration with statisticians
is ubiquitous, and authors employ diverse strategies to ensure robust statistical
analysis. Transparent reporting of statistical methodologies is essential for research
reproducibility and integrity. Effective collaboration between authors and statisticians
can lead to more robust research outcomes and higher-quality publications, ultimately
advancing the field of anaesthesiology and scientific research.