0000000000625852
AUTHOR
Jyrki Möttönen
Impact of missing data mechanism on the estimate of change: a case study on cognitive function and polypharmacy among older persons
Piia Lavikainen,1,2 Esko Leskinen,3 Sirpa Hartikainen,1,2 Jyrki Möttönen,4 Raimo Sulkava,5 Maarit J Korhonen6 1Kuopio Research Centre of Geriatric Care, University of Eastern Finland, Kuopio, Finland; 2School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland; 3Department of Mathematics and Statistics, University of Jyväskylä, Jyväskylä, Finland; 4Department of Social Research, University of Helsinki, Helsinki, Finland; 5Department of Geriatrics, Institute of Public Health and Clinical Nutrition, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland; 6Department of Pharmacology, D…
Affine equivariant multivariate rank methods
The classical multivariate statistical methods (MANOVA, principal component analysis, multivariate multiple regression, canonical correlation, factor analysis, etc.) assume that the data come from a multivariate normal distribution and the derivations are based on the sample covariance matrix. The conventional sample covariance matrix and consequently the standard multivariate techniques based on it are, however, highly sensitive to outlying observations. In the paper a new, more robust and highly efficient, approach based on an affine equivariant rank covariance matrix is proposed and outlined. Affine equivariant multivariate rank concept is based on the multivariate Oja (Statist. Probab. …