In particular, urbanity was a good predictor for the dimension of pain/discomfort in the Greek individuals and also for the dimension of depression/anxiety for both the Greek and Albanian individuals.
In this model X is the predictor matrix of dimension n × p, where n is the number of data objects and p is the number of variables.
The importance of patients' expectations in the context of evaluation of QOL has already been pointed out by Wan et al. [ 38] who demonstrated that the discrepancy between what patients expect and what actually occurs with treatment is a significant predictor for every dimension of health-related QL.
In the models predicting the physical dimensions of HRQoL, BMI predicted more additional variance than PA, whereas PA was the strongest predictor for mental dimensions (Table 4).
The rectangle is a two-dimension predictor space.
However, findings here reveal that depression is a predictor for all dimensions of fatigue.
A regression analysis showed that resilience was a significant predictor for all dimensions of quality of life before donation (R = 10.2 24.6 %).
However, the specific summaries described in the previous section are defined only on the single dimension of predictor (lag-specific and overall cumulative associations, bottom panels of Figure 1) or lag (predictor-specific association, top-right panel of Figure 1).
Race/ethnicity remained a significant predictor for just one dimension of underuse, in the multivariate regressions (Table 4).
Alternatively, the simplification could be applied in the other dimension of predictor, specifying DLMs for linear or linear-threshold exposure-response relationships [ 8- 11].
In this contribution we propose a method to reduce estimates from DLNMs to summaries defined in only one dimension of predictor or lags, re-expressing the fit in terms of reduced parameters for the related uni-dimensional basis functions.
