Mixed models for the analysis of replicated spatial point patterns

The statistical methodology for the analysis of replicated spatial point patterns in complex designs such as those including replications is fairly undeveloped. A mixed model is developed in conjunction with maximum pseudolikelihood and generalized linear mixed modeling by extending Baddeley and Turner's (2000, Australian and New Zealand Journal of Statistics 42, 283-322) work on pseudolikelihood for single patterns. A simulation experiment is performed on parameter estimation. Fixed- and mixed-effect models are compared, and in some respects the mixed model is found to be superior. An example using the Strauss process for modeling neuron locations in post-mortem brain slices is shown.