Using Entropy Working Correlation Matrix in Generalized Estimating Equation for Stock Price Change Model

Longitudinal studies involving binary responses are widely applied in medical, health and economic science research, have focused increasingly on how various independent variables affect responses over time. These studies involve repeated observations on a subject and thus correlation within each subject is expected. Correct inferences can only be obtained by taking into account the correct specification of within-subject correlation structure between repeated observations. In recent years, non-normal longitudinal data is analyzed by Generalized Estimating Equations (GEE) method. Goodness-of-fit statistics have been suggested for selecting an appropriate working correlation structure in GEE with longitudinal binary data. The purpose of this article to provide an overview of the GEE approach for analyzing correlated binary data and to choose the structure of the correlation matrix between repeated observations for model comparison, using data from Istanbul Stock Exchange (ISE) to increase on the return.