Recently there has been a surge of interest in using structural priming to examine sentence production. We present an analogical model of sentence production that exhibits structural priming effects. It uses analogical generalization to acquire abstract language patterns from experience. To construct utterances, it uses analogical retrieval to find semantically similar utterances and generalizations, and constructs a new sentence by analogy to them. Using the stimulus generator of Chang et al (2006), we show that this model can exhibit structural priming effects similar to those observed in humans, but with orders of magnitude less prior experience than required by a previous simulation.