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A linear mixed-effects (LME) model is proposed for modelling and forecastingsingle and multi-population age-specific death rates (ASDRs). The innovativeapproach that we take in this study treats age, the interaction between genderand age, their interactions with predictors, and cohort as fixed effects.Furthermore, we incorporate additional random effects to account for variationsin the intercept, predictor coefficients, and cohort effects among differentage groups of females and males across various countries. In thesingle-population case, we will see how the random effects of intercept andslope change over different age groups. We will show that the LME model isidentifiable. Using simulating parameter uncertainty in the LME model, we willcalculate 95% uncertainty intervals for death rate forecasts. We will use datafrom the Human Mortality Database (HMD) to illustrate the procedure. We assessthe predictive performance of the LME model in comparison to the Lee-Carter(LC) models fitted to individual populations. Additionally, we evaluate thepredictive accuracy of the LME model relative to the Li-Lee (LL) model. Ourresults indicate that the LME model provides a more precise representation ofobserved mortality rates within the HMD, demonstrates robustness in calibrationrate selection, and exhibits superior performance when contrasted with the LCand LL models.

Age-Gender-Country-Specific Death Rates Modelling and Forecasting: A Linear Mixed-Effects Model