The partial least squares (PLS) is a popular path modeling technique commonly used in social sciences. The traditional PLS algorithm deals with variables measured on interval scales while data are often collected on ordinal scales. A reformulation of the algorithm, named Ordinal PLS (OrdPLS), is introduced, which properly deals with ordinal variables. Some simulation results show that the proposed technique seems to perform better than the traditional PLS algorithm applied to ordinal data as they were metric, in particular when the number of categories of the items in the questionnaire is small (4 or 5) which is typical in the most common practical situations.

Cantaluppi, G., Boari, G., A Partial Least Squares Algorithm Handling Ordinal Variables, in Abdi, H., Esposito Vinzi, V., Russolillo, G., Saporta, G., Trinchera, L. (ed.), The Multiple Facets of Partial Least Squares and Related Methods, Springer International Publishing, Cham 2016: 295- 306. 10.1007/978-3-319-40643-5_22 [http://hdl.handle.net/10807/94178]

A Partial Least Squares Algorithm Handling Ordinal Variables

Cantaluppi, Gabriele
Primo
;
Boari, Giuseppe
Ultimo
2016

Abstract

The partial least squares (PLS) is a popular path modeling technique commonly used in social sciences. The traditional PLS algorithm deals with variables measured on interval scales while data are often collected on ordinal scales. A reformulation of the algorithm, named Ordinal PLS (OrdPLS), is introduced, which properly deals with ordinal variables. Some simulation results show that the proposed technique seems to perform better than the traditional PLS algorithm applied to ordinal data as they were metric, in particular when the number of categories of the items in the questionnaire is small (4 or 5) which is typical in the most common practical situations.
2016
Inglese
The Multiple Facets of Partial Least Squares and Related Methods
978-3-319-40641-1
Springer International Publishing
Cantaluppi, G., Boari, G., A Partial Least Squares Algorithm Handling Ordinal Variables, in Abdi, H., Esposito Vinzi, V., Russolillo, G., Saporta, G., Trinchera, L. (ed.), The Multiple Facets of Partial Least Squares and Related Methods, Springer International Publishing, Cham 2016: 295- 306. 10.1007/978-3-319-40643-5_22 [http://hdl.handle.net/10807/94178]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/94178
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