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Canonical Correlation Analysis on Vital Signs and Demographic Measures of Patients
Current Issue
Volume 5, 2018
Issue 5 (September)
Pages: 121-131   |   Vol. 5, No. 5, September 2018   |   Follow on         
Paper in PDF Downloads: 22   Since Oct. 10, 2018 Views: 1054   Since Oct. 10, 2018
Authors
[1]
Iheagwara Andrew Ihuoma, Department of Statistics, Imo State University, Owerri, Nigeria.
[2]
Okenwe Idochi, Department of Statistics, Ken Saro Wiwa Polytechnic, Bori, Rivers, Nigeria.
[3]
Ononogbu Amarachi Christiana, Department of Statistics, Michael Okpara University of Agriculture Umudike, Umuahia, Nigeria.
Abstract
This study examined the canonical correlation analysis on vital signs and demographic measures of 200 patients in the selected government owned hospital in Imo State Nigeria. Canonical correlation analysis focuses on the correlation between a linear combination of the variables in one set and a linear combination of the variables in another set. The objective of the study is to identify and quantify the association between two sets of variables. The data for this study were collected in an arrangement with the nurses of the selected government owned hospital in Imo State Nigeria. A total number of 200 patients were randomly selected and used for this study. An ethical approval was obtained from the Ethical committee of the selected hospitals. The consent of the subjects were sought and obtained and the consenting subjects were used by the patients, using the following inclusion criteria: They were normally balanced (i.e. the subjects were able to answer questions on name, age, sex, date of birth, marital status etc., consciously and correctly; All the patients (both in- and out-patients) within April 1, to April 18 2018 participated in this exercise, as the nurses did not allow them to know the rationale behind the vital signs and demographic measurements; Both male and female were recruited. The data for this study, which contain four criterion measures and three predictor variables, were analyzed using the “Stata” statistical software package. Based on the results obtained, and the hypotheses carried out, it was revealed that out of the three sample canonical correlations, the first two are significant, while the third one is insignificant. Finally, it was concluded that relationship exists between the vital signs and the demographic measures of the 200 patients.
Keywords
Canonical Correlations, Standardized Coefficients, Canonical Loadings, Correlation Matrix
Reference
[1]
William, R. D. and Matthew, G. (1984): Multivariate Analysis, Methods and Applications. John Wiley & Sons, New York.
[2]
Parkhomenko, E., Tritchler, D., and Beyene, J. (2009): Sparse Canonical Correlation Analysis with Application to Genomic Data Integration. Statistical Applications in Genetics and Molecular Biology: Vol. 8: Iss. 1, Article 1.60.
[3]
Johnson, R. A. and Wichern, D. W. (1992): Applied Multivariate Statistical Analysis, prentice Hall, Englewood Cliffs, New Jersey.
[4]
Lin, C. T., Huang, C. S., Yang, W. Y., Singh, A. K., Chuang, C. H. and Wang, Y. K. (2018). Real Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering. Journal of Healthcare Engineering Volume 2018, Article ID 5081258.
[5]
Jayadevan, C. M. (2018). A Canonical Correlation Analysis of Sectoral Composition of GDP and Development in Asia. Modern Economy, 9, 379-392.
[6]
Mussina, K. P. and Bachisse, M. (2018). Canonical Correlation Analysis between Business Sophistication and Macroeconomic Environment: A Secondary study of Countries Global competitiveness. Revista ESPACIOUS. Vol. 39, Number 18.
[7]
Idowu, O. A. and Titilola, O. O. (2018). Development of a canonical correlation model involving non linearity and asymmetric variables, Communications in Statistics - Theory and Methods, 47: 2, 399-414, DOI: 10.1080/03610926.2017.1303731
[8]
Johnson, R. A. and Wichern, D. W. (2007): Applied Multivariate Statistical Analysis, Sixth Edition. Pearson Prentice Hall, New Jersey.
[9]
Neil, H. T. (2002): Applied Multivariate Analysis. Springer-Verlag, New York Berlin Heidelberg.
[10]
Witten, D. M. and Tibshirani, R. (2009) Extensions of Sparse Canonical Correlation Analysis with Applications to Genomic Data. Statistical Applications in Genetics and Molecular Biology: Vol. 8: Iss. 1, Article 28.
[11]
Hoerl, A. E. (1962): Application of Ridge Analysis to Regression Problems. Chemical Engineering Progress. 58, 54-59.
[12]
Lee, W., Lee D, Lee Y., and Pawitan, Y. (2011): Sparse Canonical Covariance Analysis for High-throughput Data. Statistical Applications in Genetics and Molecular Biology: Vol. 10: Iss. 1, Article 30.
[13]
Lee, W., Lee, D, Lee Y., and Pawitan, Y. (2011): Sparse canonical covariance analysis. R package. http://www.meb.ki.se/yudpaw/.
[14]
Waaijenborg S., Verselewel. D. E., Witt, Hamer P. C., and Zwinderman, A. H. (2008): Quantifying the Association between Gene Expressions and DNA-Markers by Penalized Canonical Correlation Analysis. Statistical Applications in Genetics and Molecular Biology: Volume 7: Issue 1, Article 3.
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