TY - JOUR
T1 - A review of multivariate methods of analysing refractive data with dioptric power matrices
AU - Chetty, Elizabeth
AU - Rubin, Alan
N1 - Publisher Copyright:
© 2022. The Author(s). Licensee: AOSIS. This work is licensed under the Creative Commons Attribution License.
PY - 2022
Y1 - 2022
N2 - Background: There are three components to refractive state, namely sphere, cylinder and axis. Similarly, central corneal power is also composed of three components, namely the power along the flat meridian, the power along the steep meridian and the axis of the flat meridian. Most studies that investigate refractive data and corneal power analyse each of the three components individually rather than as a trivariate entity. In doing so, pertinent information may inadvertently be omitted. Aim: The purpose of this review is to provide a brief overview of the multivariate statistics that are available to analyse multivariate data such as dioptric power. This will enable readers to better understand research that is analysed using these methods. Method: An extensive review of databases such as Google Scholar, Science Direct and ResearchGate was done to gather publications on the topic of multivariate statistical analysis. Keywords such as multivariate statistical analysis, dioptric power, stereo-pairs, polar profiles and hypothesis testing were used to conduct the search. Results: The debate for the need to analyse dioptric power using multivariate statistical methods has been a long-standing one. For this review, more than 40 publications were analysed to provide a simplified overview of the multivariate statistical methods that can be used to analyse dioptric power. Conclusion: The use of multivariate statistical methods is a valuable tool in analysing and understanding dioptric power holistically and may provide more insights for research involving refractive error and corneal power.
AB - Background: There are three components to refractive state, namely sphere, cylinder and axis. Similarly, central corneal power is also composed of three components, namely the power along the flat meridian, the power along the steep meridian and the axis of the flat meridian. Most studies that investigate refractive data and corneal power analyse each of the three components individually rather than as a trivariate entity. In doing so, pertinent information may inadvertently be omitted. Aim: The purpose of this review is to provide a brief overview of the multivariate statistics that are available to analyse multivariate data such as dioptric power. This will enable readers to better understand research that is analysed using these methods. Method: An extensive review of databases such as Google Scholar, Science Direct and ResearchGate was done to gather publications on the topic of multivariate statistical analysis. Keywords such as multivariate statistical analysis, dioptric power, stereo-pairs, polar profiles and hypothesis testing were used to conduct the search. Results: The debate for the need to analyse dioptric power using multivariate statistical methods has been a long-standing one. For this review, more than 40 publications were analysed to provide a simplified overview of the multivariate statistical methods that can be used to analyse dioptric power. Conclusion: The use of multivariate statistical methods is a valuable tool in analysing and understanding dioptric power holistically and may provide more insights for research involving refractive error and corneal power.
KW - dioptric power
KW - dioptric power space
KW - hypothesis testing
KW - multivariate statistical analysis
KW - polar profiles
KW - stereo-pairs
UR - http://www.scopus.com/inward/record.url?scp=105003849624&partnerID=8YFLogxK
U2 - 10.4102/aveh.v81i1.714
DO - 10.4102/aveh.v81i1.714
M3 - Article
AN - SCOPUS:105003849624
SN - 2413-3183
VL - 81
JO - African Vision and Eye Health
JF - African Vision and Eye Health
IS - 1
M1 - a714
ER -