Multivariate Approach to Partial Correlation Analysis

  • Casmir Chidiebere O
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Abstract

Multivariate approach to generate variance covariance and partial correlation coefficients of one or more independent variables has been the concern of advanced statisticians and users of statistical tools. This work tackled the problem by keeping one or some variables constant and partitioned the variance covariance matrices to find multivariate partial correlations. Due to the challenges that faced the analysis and computation of complex variables, this research used matrix to ascertain the level of relationship that exist among these variables and obtained correlation coefficients from variance covariance matrices. It was proved that partial correlation coefficients are diagonal matrices that are normally distributed. (Work count = 101).

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APA

Casmir Chidiebere, O. (2015). Multivariate Approach to Partial Correlation Analysis. Science Journal of Applied Mathematics and Statistics, 3(3), 165. https://doi.org/10.11648/j.sjams.20150303.20

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