Preliminary communication

PARTIAL LEAST SQUARES REGRESSION ANALYSIS: EXAMPLE OF MOTOR FITNESS DATA

Ivan Serbetar ; Faculty of Teacher Education, University of Zagreb, Croatia

Abstract

Based on the research example, the article attempts to describe the partial least squares regression (PLS) as a tool used for modelling the explanatory variables for the prediction of the dependents. The research was carried out on the fitness data of 52 children, nine anthropometric variables were used as predictors, while the dependents were composed of five motor fitness tests. A two-component model was obtained where a small fraction of the dependent variation (R2Y = .20) was explained by predictors (R2X=.64). The Q2 indicator of the predictive capability of the model was rather low (.16). The main advantages of the PLS were demonstrated: the simultaneous handling of multiple independents and dependents.

Keywords

partial least squares regression; PLS; modelling; anthropometric variables; motor fitness data prediction

Hrčak ID:

94324

URI

https://hrcak.srce.hr/94324

Publication date:

23.12.2012.

Article data in other languages: croatian

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