International Journal of Advanced Statistics and Probability
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Open Access journal
ISSN (Print) 2307-9045 - ISSN (Online) 2307-9045
Published by Science Publishing Corporation [12 journals]
- Identification of correlation structure using rotated factor loadings
Authors: Iberedem Iwok, Nwikpe B. J
Pages: 8 - 16
Abstract: This work seeks to identify the correlation structure of variables in terms of few underlying but unobservable factors. The method was applied to age and five different tests results obtained from 200 patients in a hospital. Two factors were identified using the scree plot and the Kaiser criterion. The factor loadings obtained by the method of principal components gave an inadequate fit to the data. An algebraic approach was applied using orthogonal rotation, and the loadings were found to give a clear and interpretable pattern. Consequently, the variables: age, fasting blood sugar and diastolic blood pressure were found to cluster about the first factor F1 called Age-Cardiovascular factor. Similarly, the remaining variables malaria, typhoid and haemoglobin clustered about the second factor F2 and the given name was Hemo-typhomalaria factor. Diagnostic checks were carried out and the factor model generated by the rotated loadings was found to be adequate.
Issue No: Vol. 5, No. 1 (2017)
- Multivariate statistical process control approach to monitor quality of
chloroquine phosphate tablet (bp250mg) in Dana pharmaceutical company
Authors: Umar Abubakar Adamu, Gulumbe Shehu Usman, Dikko Hussaini Garba
Pages: 1 - 7
Abstract: Recently, much attention has been raised on effects of high increase in drugs counterfeiting and sub-standard quality which leads to many casualties in Nigeria. The Multivariate Statistical Process Control Charts approach was employed to examine such defects especially in assessing the official physico-chemical quality of chloroquine phosphate tablet (BP250mg) which claimed to contain the required quality properties. The Multivariate Exponentially Weighted Moving Average (MEWMA) Control Chart gives a powerful and reliable control chart than the widely used Hotelling’s T2˗Control Chart, which detects the smallest shift in the product process means and have minimum process variability. Also, the Matrix of scatter plots indicated the existence of relationship among the process variables and the Principal Component Analysis (PCA) minimized the rate of dimensionality of the process variability, which captured most of the variables outliers and retained the first Principal Components (PC) that explained over 99% variability of the product. To this end, the study results shows that the product quality characteristics (process variables) is under control (stable) and conform to international standard as specified by BP 2002.
Issue No: Vol. 5, No. 1 (2016)