Principal components analysis /

Principal components analysis offers researchers a 'feel' for analysing particular sets of multidimensional data. It is particularly useful in coping with multicolinearity in regression analysis, a persistent problem in behavioral and social science data sets.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Dunteman, George H. (George Henry), 1935-
Μορφή: Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Newbury Park : Sage Publications, �1989.
Σειρά:Quantitative applications in the social sciences ; no. 07-069.
Θέματα:
Διαθέσιμο Online:http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=24769
Πίνακας περιεχομένων:
  • 1. Introduction
  • Example
  • 2. Basic concepts of principal components analysis
  • 3. geometrical properties of principal components
  • Example
  • 4. Decomposition properties of principal components
  • Decomposition of the variables
  • Spectral decomposition of the correlation or covariance matrix
  • 5. Principal components of patterned correlation matrices
  • Example
  • 6. Rotation of principal components
  • Example
  • 7. Using principal components to select a subset of variables
  • Example
  • 8. Principal components versus factor analysis
  • Example
  • Factor rotation
  • 9. Uses of principal components in regression analysis
  • Regression on principal components
  • Principal components regression
  • Example
  • 10. Using principal components to detect outlying and influential observations
  • 11. Use of principal components in cluster analysis
  • 12. Use of principal components analysis in conjunction with other multivariate analysis procedures
  • Use of principal components in discriminant analysis
  • Example
  • Use of principal components in canonical correlation analysis
  • 13. Other techniques related to principal components
  • Principal coordinate analysis
  • Correspondence analysis.