Year: 2014
Type: article
Abstract: Statistical analysis of research results mainly uses confidence intervals and hypothesis tests to capture the uncertainty rising from our study being on a sample of participants drawn from a much larger population, in which our interest mainly lies. 1 But beyond the issue of sampling variation there are other sources of uncertainty that may be even more important to consider.In measurement, a distinction is made between precision, which is how variable are measurements on the same person by the same method made at the same time, and accuracy, which is how close the measurement is to what we actually want to know.For example, if we were to ask a group of patients on two occasions how much alcohol they typically consume, this would enable us to estimate precision, how repeatable answers are, but not how close these answers are to how much they actually drink, which we might suspect to be higher.In the same way, a confidence interval tells us about the precision of research results, what would happen if we were to repeat the same study, not their accuracy, which is how close the study is to the truth.
Source: BMJ
DOI: 10.1136/bmj.g7065
Authors: D. G. Altman, J. M. Bland
Institutions: University of Oxford, University of York
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: bronze
Funder: Cancer Research UK
Award: G3587225636
OpenAlex ID: W2093842769