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Psychometrika

, Volume 56, Issue 3, pp 433–447 | Cite as

Fitting longitudinal reduced-rank regression models by alternating least squares

  • Catrien C. J. H. Bijleveld
  • Jan De Leeuw
Article

Abstract

An alternating least squares method for iteratively fitting the longitudinal reduced-rank regression model is proposed. The method uses ordinary least squares and majorization substeps to estimate the unknown parameters in the system and measurement equations of the model. In an example with cross-sectional data, it is shown how the results conform closely to results from eigenanalysis. Optimal scaling of nominal and ordinal variables is added in a third substep, and illustrated with two examples involving cross-sectional and longitudinal data.

Key words

reduced-rank regression state space analysis optimal scaling 

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Copyright information

© The Psychometric Society 1991

Authors and Affiliations

  • Catrien C. J. H. Bijleveld
    • 1
  • Jan De Leeuw
    • 2
  1. 1.Department of PsychometricsLeiden UniversityThe Netherlands
  2. 2.Departments of Psychology and MathematicsUniversity of California at Los AngelesUSA

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