ArticleJournal of Taibah University Medical Sciences2023
Statistics in medical research: Common mistakes.
Article in Journal of Taibah University Medical Sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Statistical Reporting Quality in Physical Medicine and Rehabilitation Journals: A Comparative Analysis of SCI-E and TR Indexed Publications.The Eurasian journal of medicine · 2026Article
- Use and misuse of ANOVA in in vitro biomaterials studies: A methodological analysis of the last ten years in the Journal of Clinical and Experimental Dentistry.Journal of clinical and experimental dentistry · 2026Review
- Bridging the methodological gap in multitrauma literature: a competency-based educational framework and clinical appraisal filter.Turkish journal of medical sciences · 2026Article
- Sampling Methods and Sample Size Determination in Clinical Research: An Educational Review.Journal of general and family medicine · 2026Review
- A simple guide to the use of Student's t-test, Mann-Whitney U test, Chi-squared test, and Kruskal-Wallis test in biostatistics.BioData mining · 2025Article
- Statistical Significance versus Clinical Relevance: Key Considerations in Interpretation Medical Research Data.Indian journal of community medicine : official publication of Indian Association of Preventive & Social MedicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The misuse of statistics in medical studies has been discussed extensively with the conclusion that it is both unethical and can have serious clinical consequences. These errors can contribute to incorrect conclusions, compromise the validity of studies, and overestimate or underestimate the effects of treatment. To avoid making these errors, it is critical to consider their presence and understand statistical concepts. This practice will ultimately lead to the use of appropriate statistical techniques for specific research questions and the calculation of an appropriate sample size to guarantee adequate statistical power. Common statistical errors in medical research include sampling bias, the incorrect determination of sample, failing to adjust for multiple comparisons, misinterpreting p-values as a measure of effect size or clinical relevance, choosing incorrect tests for a particular data set, type I and II errors, data fishing, and publication bias. It is important that researchers interpret their results using appropriate statistical concepts by soliciting feedback from specialist statisticians.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.