What is it about?

OBJECTIVES: We employed the correspondence analysis (CA) biplot to estimate correlations between gender-age levels of cardiovascular disease (CVD) patients and their psychiatric and physical symptoms. Utilization of this correlation estimation can inform clinical practice by elucidating associations between certain psychiatric or physical symptoms and specific gender-age levels. METHOD: The CA biplot utilized here was designed to visually inspect row-column category associations in a two-dimensional plane and then to numerically estimate the category associations with correlations. To do so, we; (1) estimated dimensions from row and column categories with CA; (2) verified statistical significance of dimensions with a permutation test; (3) projected row and column categories in a plan constructed with the first two dimensions that were statistically significant; (4) visually inspected category associations in the plane; and (5) numerically estimated category associations with correlations. RESULTS: Consistent with the previous results, female CVD patients were more likely to experience psychiatric symptoms than the male patients. However, when examining the results by gender and age, both female and male patients in their fifties and sixties tended to experience elevated rates of the psychiatric symptoms. CONCLUSIONS: The correspondence analysis biplot can be useful for isolating key clinical concerns among any medical populations.

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Why is it important?

None of the clinical studies (especially CVD patients related studies) estimated correlations between natural categories (gender), discretized categories (age levels), and binary indicators (yes or no) for symptom presences. The current study was the first one along with important clinical implications: Female CVD patients were more likely to experience psychiatric symptoms than the male patients, but both female and male patients in their fifties and sixties tended to experience elevated rates of the psychiatric symptoms as well.

Perspectives

The correspondence analysis (CA) can be useful for isolating key clinical concerns among any medical populations. Many medical or clinical data are categorical, and the CA paradigm exercised here is useful for analysis of them. Especially, in the current study, unlike ordinary CA, we estimated category associations with correlations to enhance interpretations. With our estimation paradigm, any categorical associations can be estimated with correlations.

Dr. Se-Kang Kim
Fordham University

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This page is a summary of: Estimating correlations among cardiovascular patients' psychiatric and physical symptom indicators: The biplot in correspondence analysis approach, International Journal of Methods in Psychiatric Research, March 2018, Wiley,
DOI: 10.1002/mpr.1611.
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