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[An analysis of subhealth status based on partial least squares]
Zhong-ping Li1, Yue Su, Hong-yi Shen
1Department of Health Nutrition, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Objective:
To explore the discrimination model of subhealth with statistical method of partial least squares (PLS).
Methods:
This study was based on the Subhealth State Rating Scale (SHSRS). A total of 88 subhealth subjects (scoring less than 85 in SHSRS) and 64 healthy people (scoring over 85 in SHSRS) were enrolled randomly. Information regarding the clinical symptoms was screened by stepwise regression as independent variables. Mathematical models were established by leave-one-out in PLS program for subhealth recognition before and after stepwise regression respectively. Accuracy rates were observed and compared by using the Visual Basic 6.0.
Results:
The practical accuracy rate of PLS models in subhealth recognition was 89.47%, and increased to 92.10% after stepwise regression for variables.
Conclusion:
PLS has certain reference value in establishing subhealth discrimination models. It can also play an important part in item selection of the scale.
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