Literature DB >> 26403142

Sample size considerations for clinical research studies in nuclear cardiology.

Cody Chiuzan1, Erin A West2, Jimmy Duong2, Ken Y K Cheung2, Andrew J Einstein3.   

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.

Keywords:  Sample size; clinical research; nuclear cardiology

Mesh:

Year:  2015        PMID: 26403142     DOI: 10.1007/s12350-015-0256-7

Source DB:  PubMed          Journal:  J Nucl Cardiol        ISSN: 1071-3581            Impact factor:   5.952


  7 in total

1.  18F-FDG PET imaging of myocardial viability in an experienced center with access to 18F-FDG and integration with clinical management teams: the Ottawa-FIVE substudy of the PARR 2 trial.

Authors:  Arun Abraham; Graham Nichol; Kathryn A Williams; Ann Guo; Robert A deKemp; Linda Garrard; Ross A Davies; Lloyd Duchesne; Haissam Haddad; Benjamin Chow; Jean DaSilva; Rob S B Beanlands
Journal:  J Nucl Med       Date:  2010-03-17       Impact factor: 10.057

2.  A simple approximation for calculating sample sizes for comparing independent proportions.

Authors:  J L Fleiss; A Tytun; H K Ury
Journal:  Biometrics       Date:  1980-06       Impact factor: 2.571

3.  The prognostic value of transient ischemic dilatation with otherwise normal SPECT myocardial perfusion imaging: a cautionary note in patients with diabetes and coronary artery disease.

Authors:  Rami Doukky; Nathan Frogge; Yohannes A Bayissa; Gautam Balakrishnan; Jacob M Skelton; Kara Confer; Kalindi Parikh; Russell F Kelly
Journal:  J Nucl Cardiol       Date:  2013-08-09       Impact factor: 5.952

4.  The effect of ranolazine on the vasodilator-induced myocardial perfusion abnormality.

Authors:  Rajesh Venkataraman; Wael Aljaroudi; Luiz Belardinelli; Jaekyeong Heo; Ami E Iskandrian
Journal:  J Nucl Cardiol       Date:  2011-03-24       Impact factor: 5.952

5.  Incremental diagnostic benefit of resolution recovery software in patients with equivocal myocardial perfusion single-photon emission computed tomography (SPECT).

Authors:  Mohammed A Qutub; Taylor Dowsley; Iftikhar Ali; R Glenn Wells; Li Chen; Terrence D Ruddy; Benjamin J W Chow
Journal:  J Nucl Cardiol       Date:  2013-05-25       Impact factor: 5.952

6.  Evaluation of right ventricular volume and ejection fraction by gated (18)F-FDG PET in patients with pulmonary hypertension: comparison with cardiac MRI and CT.

Authors:  Lei Wang; Yan Zhang; Chaowu Yan; Jianguo He; Changming Xiong; Shihua Zhao; Wei Fang
Journal:  J Nucl Cardiol       Date:  2013-01-26       Impact factor: 5.952

7.  Sample size formulae for the Bayesian continual reassessment method.

Authors:  Ying Kuen Cheung
Journal:  Clin Trials       Date:  2013-08-21       Impact factor: 2.486

  7 in total
  1 in total

1.  Power and sample size in clinical studies.

Authors:  Todd M Brown
Journal:  J Nucl Cardiol       Date:  2015-09-25       Impact factor: 5.952

  1 in total

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