I have difficulty interpreting some results. I am doing an hierarchical related regression with
ecoreg. If I enter the code I receive output with odds ratios, confidence ratios and a 2x maximized log likelihood.
However, I do not fully understand how to interpret the 2x maximized log likelihood. As far as I know log likelihood is used as a convenient way of calculating a likelihood and it calculates the value of the parameters based on the outcomes. But I do not understand if a higher or lower value is better. I looked at several online sources e.g. https://stackoverflow.com/questions/2343093/what-is-log-likelihood, but I am still stuck.
Below the outcome I receive:
Call: eco(formula = cbind(y, N) ~ deprivation + meanIncome, binary = ~fracSmoke + soclass, data = dfAggPlus, cross = cross) Aggregate-level odds ratios: OR l95 u95 (Intercept) 0.0510475 0.03837276 0.06790878 deprivation 0.9859936 0.88421991 1.09948134 meanIncome 1.0689951 0.95574925 1.19565924 Individual-level odds ratios: OR l95 u95 fracSmoke 3.124053 2.0761956 4.700765 soclass 1.001050 0.9930815 1.009083 -2 x log-likelihood: 237.4882
So, how should I interpreted a value of 237.4882 compared to an outcome of 206 or 1083? Help is much appreciated!