). 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 The 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).
