Most important, correlations of AOD and PM2.5 may reflect variability in PM2.5 that could be predicted by other sources of information, such as land use or meteorology or estimation of large-scale regional variation through spatial smoothing of monitored values, so they may overstate the usefulness of AOD as a predictor in light of other readily available information.
Phase-typing as a predictor of light-treatment response was proposed by Lewy and colleagues [ 33] and has been previously employed to select light treatment timing prospectively [ 34].
We found no changes in the duration, IPI, or IPI variance in response to any predictor variables (lights, fabrics, distress calls, date, time, and passes or collisions).
In this model the main predictor was the light backscatter response from the NIR light back scatter sensor.
Genetic and clinical predictors of EXERCISE, LIGHT and MODERATE responders and nonresponders were tested using binary logistic regression models.
The study extends the evaluation of the optimum set of predictors not only in light of the attained performances but in relation to the stability of the resulted predictors as well.
Categorical predictors were: taxon, temperature, light condition and collection time for continuous regimes, and taxon, climate, light condition, collection time and starting point for annual cycles.
Our analysis not only generated mechanism based gene signature predictors, but also shed light on the role of different molecular pathways in cancer development.
For example, given the recent national evidence suggesting overall difficulties in access to EI [ 9, 10], shedding light on predictors of a specific aspect of EI services (i.e., therapy) seems critical to improving our understanding of access disparities.
Several predictors of response to light treatment in winter depressives have been identified: the ratio of atypical to classical symptoms of depression [ 15] and hypersomnia, increased eating and younger age [ 16].
