Julious, S.A. orcid.org/0000-0002-9917-7636 (2019) Calculation of confidence intervals for a finite population size. Pharmaceutical Statistics, 18 (1). pp. 115-122. ISSN 1539-1604
Abstract
For any estimate of response, confidence intervals are important as they help quantify a plausible range of values for the population response. However, there may be instances in clinical research when the population size is finite, but we wish to take a sample from the population and make inference from this sample. Instances where you can have a fixed population size include when undertaking a clinical audit of patient records or in a clinical trial a researcher could be checking for transcription errors against patient notes. In this paper, we describe how confidence interval calculations can be calculated for a finite population. These confidence intervals are narrower than confidence intervals from population samples. For the extreme case of when a 100% sample from the population is taken, there is no error and the calculation is the population response. The methods in the paper are described using a case study from clinical data management.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 John Wiley & Sons, Ltd. This is an author produced version of a paper subsequently published in Pharmaceutical Statistics. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Binary response; clinical audit; confidence interval; data management; finite population |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Nov 2018 15:52 |
Last Modified: | 10 May 2024 15:08 |
Status: | Published |
Publisher: | Wiley |
Refereed: | Yes |
Identification Number: | 10.1002/pst.1901 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:138616 |