Spatial generalized linear mixed model is commonly used to model Non-Gaussian data and the spatial correlation of the data is modelled by latent variables. In this paper, latent variables are modeled using a stationary skew Gaussian random field and a new algorithm based on composite marginal likelihood is presented. The performance of this stationary random field in the model and the proposed algorithm is implemented in a simulation example.