). Rho is maximized when the raised density model is 1 (i.e. when the density is not elevated, or when the null hypothesis is true) atThe parameters for the raised density model are optimized through maximum likelihood estimation (MLE), a general statistical method for estimating parameters. In this case, the process involves maximizing the log-likelihood function for rho ( ). Rho is maximized when the raised density model is 1 (i.e. when the density is not elevated, or when the null hypothesis is true) at
Where n = # cases and m = # controls (Diggle and Rowlingson 1994).
