Sentence examples for models of outcome from inspiring English sources
3. Multivariate analysis of predictive factors and models of outcome.
However, little work has examined the role of motivation in more complex models of outcome that include social cognition, despite our increased understanding of the critical role of social cognition in community functioning in schizophrenia, and despite new basic science findings on the association between social cognitive and reward processing in neural systems in humans.
Beyond age, other measures of underlying health can also be incorporated into predictive models of outcome after injury.
Beyond the distinction between blunt and penetrating injury, more specific classifications of injury mechanism can be incorporated into predictive models of outcome after injury.
Adjusted analyses were performed using linear regression models of outcome on randomised group, adjusting for baseline values of the respective outcome measure, AUDIT-C, age, education, self-efficacy, log (TOT-AL+1), EQ5D and gender.
Thus, serum cytokine based prediction models of outcome seem to be reasonable and of great interest.
This article examines various definitions and models of outcome-based evaluation; describes the lack of knowledge regarding children's use of technology in public libraries, despite their majority status among users; and presents an original outcome-based evaluation model (the Project CATE model) developed to assess this use.
Models of outcomes measured after time 0 were run with and without adjustment for their respective baseline level.
Significant predictors of between-study heterogeneity were identified in two of the meta-regression models of outcomes in uncontrolled before-and-after studies.
Previous models of outcomes for rheumatic conditions have a strong biomedical focus with many models of disability or quality of life having an implicit assumption that there is a linear relationship between disease processes and disability.
Multinomial regression allows modelling of outcome variables with >2 categories and relates the probability of being in category j to the probability of being in a baseline category.
