  The decrease in the increase in death rates at old ages is a phenomenon that
has repeatedly been discussed in demographic research. While mortality
deceleration can be explained in the gamma-Gompertz model as an effect of
selection in heterogeneous populations, this phenomenon can be difficult to
assess statistically because it relates to the tail of the distribution of the
ages at death. By using a focused information criterion (FIC) for model
selection, we can directly target model performance at those advanced ages. The
gamma-Gompertz model is reduced to the competing Gompertz model without
mortality deceleration if the variance parameter lies on the boundary of the
parameter space. We develop a new version of the FIC that is adapted to this
non-standard condition. In a simulation study, the new FIC is shown to
outperform other methods in detecting mortality deceleration. The application
of the FIC to extinct French-Canadian birth cohorts demonstrates that focused
model selection can be used to rebut previous assertions about mortality
deceleration.
