Evidence map›Paper›PMID 42519545›Full record

ArticleAnnals of Ibadan postgraduate medicine2025

A NARRATIVE REVIEW OF SAMPLE SIZE ESTIMATION FOR QUANTITATIVE EPIDEMIOLOGICAL AND CLINICAL STUDY DESIGNS.

T M Ipinnimo

Abstract read
In one paragraph

Article in Annals of Ibadan 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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

T M IpinnimoDepartment of Community Medicine, Federal Teaching Hospital, Ido-Ekiti, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Sample size estimation is a crucial step in conducting valid and reliable research. It is the most common question researchers ask biostatisticians, as these investigators often face the problem of estimating the correct sample size for their research. Aim: This article aims to discuss the methods of sample size estimation in quantitative epidemiological and clinical research, presenting key principles and commonly used techniques in a simplified manner. Discussion: Unlike the previously published reviews, this article presents simple, straightforward, and easy-to-understand sample size formulas as well as basic principles on sample size estimation of common study designs in epidemiological and clinical research. In addition, explanations were provided on different statistical theories and concepts, such as outcome variable, confidence level, power, and effect size, which are important considerations in estimating scientifically appropriate sample size. Conclusion: Based on the descriptions and simplified formulas in this article, researchers can easily estimate a sample size that aligns with their study design and outcome measures, enabling more robust and reliable estimates and ensuring that the findings can be generalised to the wider population.

Indexed as

DeterminationEstimationFormulaResearchSample sizeStudy design

Identifiers

PMID42519545
PMCPMC13383087

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.