ArticleExperimental biology and medicine (Maywood, N.J.)2022
Statistical considerations for outcomes in clinical research: A review of common data types and methodology.
Article in Experimental biology and medicine (Maywood, N.J.), 2022. 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.
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- MEX3A is a diagnostic, independent prognostic biomarker and a promising therapeutic target in glioblastoma.Frontiers in oncology · 2025Article
- Comparison of oxcarbazepine metabolite concentrations measured by EMIT-based Siemens Viva-ProEFrontiers in pharmacology · 2025Article
- Machine learning-based predictive model for high- grade cytokine release syndrome in chimeric antigen receptor T-cell therapy.Frontiers in immunology · 2025Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the increasing number and variety of clinical trials and observational data analyses, producers and consumers of clinical research must have a working knowledge of an array of statistical methods. Our goal with this body of work is to highlight common types of data and analyses in clinical research. We provide a brief, yet comprehensive overview of common data types in clinical research and appropriate statistical methods for analyses. These include continuous data, binary data, count data, multinomial data, and time-to-event data. We include references for further studies and real-world examples of the application of these methods. In summary, we review common continuous and discrete data, summary statistics for said data, common hypothesis tests and appropriate statistical tests, and underlying assumption for the statistical tests. This information is summarized in tabular format, for additional accessibility.
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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.