title: [An analysis of subhealth status based on partial least squares].
abstract: 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.
  
  
  CONCLUSIONS
  PLS has certain reference value in establishing subhealth discrimination models. It can also play an important part in item selection of the scale.
authors.affiliation: Department of Health Nutrition, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
authors.forename: Zhong-ping
authors.initials: ZP
authors.lastname: Li
authors.forename: Yue
authors.initials: Y
authors.lastname: Su
authors.forename: Hong-yi
authors.initials: HY
authors.lastname: Shen
authors.forename: Xiao-tian
authors.initials: XT
authors.lastname: Zhang
authors.forename: Lin
authors.initials: L
authors.lastname: Fan
mesh_terms: D000328:Adult; D000465:Algorithms; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D055815:Young Adult