Study Some Risk Factors of Spontaneous Abortion by Using Canonical Correlation Analysis | ||
| journal of kirkuk University For Administrative and Economic Sciences | ||
| Volume 12, Issue 2, December 2022, Pages 317-333 PDF (1.4 M) | ||
| Authors | ||
| Abbas Gulmurad Beg Murad; Sozan Saber Haider | ||
| journal of kirkuk University For Administrative and Economic Sciences | ||
| Abstract | ||
| Canonical correlation analysis (CCA) means a involving several dimensions investigative statistical procedure that operates on the same concept as the principal component analysis. The primary occasion of it is the expedition of correlations between two sets of variables on the identical exploratory items. Furthermore, the PCA technique deals with one case study data only. It tries to decrease the general dimensional of the sample data using several linear collections of the primary variables.Some more packages can be downloaded and installed likewise (mainly the R programming codes insides packages CCA, CCP, insides CC).The case study be formed of two sample data where each dataset represents (100) pregnant women localities in the Sulaimani General Hospital. The first dataset contains measurements of biological metrics of two variables (Type of abortion, duration of abortion in weeks), and the second dataset contains measurements of three variables (wife's age, Occupation, and residence).The main idea is to by some means correlate both sets to explain what biometrics can correlate which each other. The way of replying this is to implement canonical correlation procedure described with additional tools to expedite the understanding of the outcomes in this study. | ||
| Keywords | ||
| Canonical Correlation Analysis; CCA; canonical variates; Canonical variation; Sample Correlation Matrix; Principal Components Analysis; PCA | ||
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