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Statistical guidelines for clinical studies of human vision
Author(s) -
Armstrong Richard A,
Davies Leon N,
Dunne Mark C M,
Gilmartin Bernard
Publication year - 2011
Publication title -
ophthalmic and physiological optics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.147
H-Index - 66
eISSN - 1475-1313
pISSN - 0275-5408
DOI - 10.1111/j.1475-1313.2010.00815.x
Subject(s) - bonferroni correction , variety (cybernetics) , computer science , advice (programming) , statistical hypothesis testing , statistical model , statistical power , statistical analysis , sample size determination , data science , parametric statistics , statistics , medical physics , machine learning , medicine , artificial intelligence , mathematics , programming language
Citation information: Armstrong RA, Davies LN, Dunne MCM & Gilmartin B. Statistical guidelines for clinical studies of human vision. Ophthalmic Physiol Opt 2011, 31 , 123–136. doi: 10.1111/j.1475‐1313.2010.00815.x Abstract Statistical analysis of data can be complex and different statisticians may disagree as to the correct approach leading to conflict between authors, editors, and reviewers. The objective of this article is to provide some statistical advice for contributors to optometric and ophthalmic journals, to provide advice specifically relevant to clinical studies of human vision, and to recommend statistical analyses that could be used in a variety of circumstances. In submitting an article, in which quantitative data are reported, authors should describe clearly the statistical procedures that they have used and to justify each stage of the analysis. This is especially important if more complex or ‘non‐standard’ analyses have been carried out. The article begins with some general comments relating to data analysis concerning sample size and ‘power’, hypothesis testing, parametric and non‐parametric variables, ‘bootstrap methods’, one and two‐tail testing, and the Bonferroni correction. More specific advice is then given with reference to particular statistical procedures that can be used on a variety of types of data. Where relevant, examples of correct statistical practice are given with reference to recently published articles in the optometric and ophthalmic literature.