Evidence map›Paper›PMID 26403142›Full record

ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2015

Sample size considerations for clinical research studies in nuclear cardiology.

Cody Chiuzan, Erin A West, Jimmy Duong, Ken Y K Cheung, Andrew J Einstein

Abstract read
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In one paragraph

Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Power and sample size in clinical studies.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2015
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Cody ChiuzanDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA. cc3780@cumc.columbia.edu.
Erin A WestDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA.
Jimmy DuongDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA.
Ken Y K CheungDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA.
Andrew J EinsteinDivision of Cardiology, Departments of Medicine and Radiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, 10032, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sample size calculation is an important element of research design that investigators need to consider in the planning stage of the study. Funding agencies and research review panels request a power analysis, for example, to determine the minimum number of subjects needed for an experiment to be informative. Calculating the right sample size is crucial to gaining accurate information and ensures that research resources are used efficiently and ethically. The simple question "How many subjects do I need?" does not always have a simple answer. Before calculating the sample size requirements, a researcher must address several aspects, such as purpose of the research (descriptive or comparative), type of samples (one or more groups), and data being collected (continuous or categorical). In this article, we describe some of the most frequent methods for calculating the sample size with examples from nuclear cardiology research, including for t tests, analysis of variance (ANOVA), non-parametric tests, correlation, Chi-squared tests, and survival analysis. For the ease of implementation, several examples are also illustrated via user-friendly free statistical software.

Indexed as

Data Interpretation, StatisticalResearch DesignSample SizeCardiologyClinical Trials as TopicComputer SimulationModels, StatisticalNuclear Medicineclinical researchnuclear cardiologySample size

Identifiers

PMID26403142

What OpenQuestion holds

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Registered trials

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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.