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The association between urbanicity and risk of schizophrenia is well established. The incidence of schizophrenia has been observed to increase in line with rising levels of urbanicity, as measured in terms of population size or density. This association is expressed as Incidence Rate Ratio (IRR), and the results are usually presented by comparing the most urban with the most rural environment. In this study, we undertook to express the effect of urbanicity on the risk of schizophrenia in a linear form and to perform a meta-analysis of all available evidence. We first employed a simple regression analysis of log (IRR) as given in each study on the urbanicity category, assuming a uniform distribution and a linear association. In order to obtain more accurate estimates, we developed a more sophisticated method that generates individual data points with simulation from the summary data presented in the original studies, and then fits a logistic regression model. The estimates from each study were combined with meta-analysis. Despite the challenges that arise from differences between studies as regards to the number and relative size of urbanicity levels, a linear association was observed between the logarithm of the odds of risk for schizophrenia and urbanicity. The risk for schizophrenia at the most urban environment was estimated to be 2.37 times higher than in the most rural environment. The same effect was found when studies measuring the risk for nonaffective psychosis were included.