Open Conference Systems, 50th Scientific meeting of the Italian Statistical Society

Font Size: 
The study of relationship between financial performance and sports success in Italian Football Championship clubs through the Longitudinal generalized estimating equation models
Pasquale Sarnacchiaro, Anna Crisci, Luigi D'Ambra

Last modified: 2018-05-24


Football is undoubtedly the most powerful and most popular sport in Italy, linking communities and stirring emotions. The main goal of any Football Championship club is to achieve sport results. Nevertheless, football has also become one of the most profitable industries, with a significant economic impact in infrastructure development, sponsorships, TV rights and transfers of players. The study of the relationship between sport and economic results attracts the interest of many scholars belonging to different disciplines. Very informative is considered the connection between the points in the championship and the resource allocation strategies. The aim of this paper is to give a very useful interpretation of this last link using the Generalized Estimating Equation (GEE) for longitudinal data.

The main idea behind GEE is to generalize and extend the classical likelihood equation for a Generalized Linear Model by including the covariance matrix of the responses. The biggest advantage of the GEE is that we do not need to specify the whole distribution of the response. Only the mean structure, the mean-variance relationship and specification of the covariance structure need to be defined. Moreover, diagnostic measures and graphical methods for checking the adequacy of GEE method are shown


1. Gosho, M., Hamada, C., & Yoshimura, I. (2011). Criterion for the Selection of a Working Correlation Structure in the Generalized Estimating Equation Approach for Longitudinal Balanced Data. Communications in Statistics Theory and Methods, 40(21), 3839-3856.

2. Liang, K.Y. & Zeger, S.L. (1986). Longitudinal data analysis using generalized linear models. Biometrika, 73, 13–22.

3. Pan, W. (2001). Akaike's Information Criterion in Generalized Estimating Equations. Biometrics, 57(1), 120-125.

4. Park, T., & Lee, S.Y. (2004). Model diagnostic plots for repeated measure data. Biometrical Journal 46,441-452

5. Zeger, S.L., Liang, K.Y., (1986). Longitudinal data analysis for discrete and continuous outcomes. Biometrics 42, 121

Full Text: PDF