ArticleJournal of postgraduate medicine2025
2. Types of data and data collation for efficient processing.
Article in Journal of postgraduate medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
abstractData are the soul of most empirical research. Adequate data collection and their proper collation are essential to arrive at right conclusions. These conclusions are mostly drawn from the statistical analysis of properly collated data. Since the methods of statistical analysis are different for different types of data, a clear understanding of various types of data is necessary for their efficient processing. Whereas broad types of data-quantitative and qualitative-are well known, some researchers struggle with the proper collation of ordinal data and quantitative categories. Additionally, some young researchers need guidance on preparing tables to communicate their results effectively. Graphics add muscles to the skeleton of data and need to be judiciously chosen. This article provides details of various types of data, their adequacy, and their proper collation, including a brief on tables and graphics. Almost all medical researchers carry out these activities - thus, this may have wide ramifications. Although this article primarily targets postgraduate students and young researchers, our interaction with a diverse group of researchers suggests that many experienced researchers may also find this article useful in the management of their data for reaching the right conclusions.
Indexed as
Identifiers
What Socratic 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 Socratic graph.