Sentence examples for measures may capture from inspiring English sources

HRQoL measures may capture the effect of an intervention on both morbidity and mortality, and provide a common denominator for comparison of economic evaluations across diseases; however, they also are subject to a number of limitations.

On the other hand, disease-specific measures may capture disease severity well but may not capture comorbidities that are strongly correlated with economic outcomes.

Studies using more than one measure of household SEC are more likely to identify associations with childhood disability than those using single measures as different measures may capture different pathways and mechanisms associated with the outcomes.

For these reasons, generic and disease-specific measures may capture complementary information and it may be desirable to incorporate both types of measures in a study, depending on the goal of the study.

Disease-specific measures may capture variation in disease severity more effectively, include data sources not captured in comorbidity or risk adjustment measures (e.g., lab data), and avoid ceiling or floor effects of generic measures (16).

Generic measures are considered less precise than disease-specific in their ability to assess the different aspects of a disease, but these measures may capture unanticipated side effects of therapies.

Although there are advantages to using generic measures, such as the ability to compare scores to the normative sample [ 29], a more condition-specific measure may capture the impact of obesity in children and adolescents more accurately, and be more responsive to any intervention-related changes in HRQoL [ 30].

As a result, we have searched for different measures that may capture the critical dimension.

More advanced psychometric techniques, such as Item Response Theory [ 93- 95] and Confirmatory Factor Analysis [ 75], are now being used to create more sensitive instruments from our current standardized tests as well as composite measures that may capture the individual variance of change in clinically normal individuals [ 11].

Because we were interested in a global conceptualization of MFR, and different measures of MFR may capture slightly different constructs [ 29], we used three scales from two different MFR measures to represent a global latent variable.

Past research suggests disease-specific measures may better capture the dimensions of HRQL most affected by diabetes, but these measures are not designed to capture the deficits associated with comorbidities, i.e. they are specific to diabetes.