During the last decades, a vertical exploration of statistical
methodology in the ground of longitudinal data has been observed.
One of the most exciting developments in this area is the
Generalized Estimating Equation (GEE). This is a widely used
approach that does not require the complete specification of the
joint distribution of repeated measurements. In addition, GEE takes
into account which results in attaining more efficiency in
estimating parameters of marginal models. The model used in this
study was developed by Barnhart & Williamson (1998). To test
the goodness-of-fit we have applied model based and empirically
corrected tests according to their implication. In their suggested
GEE approach the correlation between two responses was not
considered. Here an alternative procedure is proposed based on GEE
where the correlation between two responses was considered. This
study has also indicated that the model with only main effects did
not fit the data well. There is a significant region, time and
interaction effect. The identity correlation structure provides
most efficient estimates to represent the relationship among the
covariates and the responses.
General
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