Evidence map›Paper›PMID 36856217›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2023

[Comparison of 7 methods for sample size determination based on confidence interval estimation for a single proportion].

M Yu, X Shi, B Zou, S An

Abstract readEnglish Abstract
In one paragraph

Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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

4 authors.

M YuDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou 510515, China.
X ShiDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou 510515, China.
B ZouDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou 510515, China.
S AnDepartment of Biostatistics, School of Public Health, Southern Medical University, Guangzhou 510515, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare different methods for calculating sample size based on confidence interval estimation for a single proportion with different event incidences and precisions.

methodsWe compared 7 methods, namely Wald, AgrestiCoull add z2, Agresti-Coull add 4, Wilson Score, Clopper-Pearson, Mid-p, and Jefferys, for confidence interval estimation for a single proportion. The sample size was calculated using the search method with different parameter settings (proportion of specified events and half width of the confidence interval [ω=0.05, 0.1]). With Monte Carlo simulation, the estimated sample size was used to simulate and compare the width of the confidence interval, the coverage of the confidence interval and the ratio of the noncoverage probability.

resultsFor a high accuracy requirement (ω =0.05), the Mid-p method and Clopper Pearson method performed better when the incidence of events was low (

conclusionDifferent sample size determination methods based on confidence interval estimation should be selected for single proportions with different parameter settings.

Indexed as

Confidence IntervalsComputer SimulationMonte Carlo MethodProbabilitySample Sizebinary datainterval widthsample size estimationsingle proportion

Identifiers

PMID36856217
PMCPMC9978726

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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.