Generalized canonical correlation analysis with missing values

Albers CJ, Gower JC (2010) A general approach to handling missing values in procrustes analysis. Adv Data Anal Classif 4: 223–237

Bijmolt TH, Wedel M (1999) A comparison of multidimensional scaling methods for perceptual mapping. J Mark Res 36: 277–285

Borg I, Leutner D (1985) Measuring the similarity between MDS configurations. Multivar Behav Res 20: 325–334

Carroll JD (1968) Generalization of canonical correlation analysis to three or more sets of variables. In: Proceedings of the American psychological association, pp 227–228

Gifi A (1990) Nonlinear multivariate analysis. Wiley, Chichester

Green PE, Carroll JD (1988) A simple procedure for finding a composite of several multidimensional scaling solutions. J Acad Mark Sci 16: 25–35

Horst P (1961) Generalized canonical correlation and their applications to experimental data. J Clin Psychol 17: 331–347

Hotelling H (1936) Relations between two sets of variates. Biometrika 28: 321–377

Kettenring JR (1971) Canonical analysis of several sets of variables. Biometrika 58: 433–451

Little R, Rubin DB (1987) Statistical analysis with missing data. Wiley, New York

Magnus J, Neudecker H (1999) Matrix differential calculus with applications in statistics and econometrics. Wiley, Chichester

Meulman JJ (1982) Homogeneity analysis of incomplete data. DSWO Press, Leiden

Rubin DB (1987) Multiple imputation for nonresponse in surveys. Wiley, New York

Shibayama T (1988) Kessokuchi o fukumu testo sukoa no tahenryoukaiseki (multivariate analysis of test scores with missing data). Unpublished Doctoral Dissertation, Faculty of Education, University (in Japanese)

Shibayama T (1995) A linear composite method for test scores with missing values. Niigata daigaku kyouikugakubu kiyou (Memoirs of the Faculty of Education, Niigata University) 36: 445–455

Steenkamp J-BEM, Van Trijp HCM, Ten Berge JMF (1994) Perceptual mapping based on idiosyncratic sets of attributes. J Mark Res 31: 15–27

Takane Y (1995) Seiyakutsuki Shuseibunbunsekihou (Constrained principal component analysis). Asakurashoten, Tokyo

Takane Y, Oshima-Takane Y (2003) Relationships between two methods for dealing with missing data in principal component analysis. Behaviormetrika 30: 145–154

Ten Berge JMF, Kiers HAL, Commandeur JJF (1993) Orthogonal procrustes rotation for matrices with missing values. British J Math Stat Psychol 46: 119–134

Van de Velden M, Bijmolt TH (2006) Generalized canonical correlation analysis of matrices with missing rows: a simulation study. Psychometrika 71: 323–331

Van der Burg E (1988) Nonlinear canonical correlation and some related techniques. DSWO Press, Leiden

Zanakis SH, Alvarez C, Li V (2007) Socio-economic determinants of HIV/AIDS pandemic and nations efficiencies. Eur J Oper Res 176: 1811–1838