Table 4.
Results on predictive validity – comparison of model-fit criteria for four different models
Adjusted R-square | Percentage of deviance explained | AIC | |
---|---|---|---|
Model 1 including only covariates | 15.2 | 23.6 | 3362 |
Model 2 including covariates and the health metric | 17.5 | 26.2 | 3251 |
Model 3 including covariates and the general health question | 16.7 | 25.5 | 3285 |
Model 4 including covariates, the general health question and the health metric | 17.9 | 26.6 | 3240 |
For wave-4 data, four different additive logit-models predicting mortality in 2008 to 2012 are compared based on three model-fit criteria: adjusted R-square, percentage of deviance explained, and Akaike Information Criterion (AIC). Covariates considered in all four models include sex, age, education, income, and health conditions. To permit a fair comparison of criteria, the same subset of data with complete responses in all the variables considered over the four models was used. Where included, age and the health metric are modeled in a flexible, non-parametric way using P-splines