Sentence examples for principal dependent variable from inspiring English sources

The principal dependent variable for comparison was the mean cartilage disease score (CDS), which captured the aggregate extent of involvement of articular cartilage.

Although uptake data [ 4] were nominally available for all three doses, we felt constrained to use uptake to the second dose only as the principal dependent variable.

The probability of cutout was calculated according to Baumgaertner's curve (Baumgaertner et al. 1995), the principal dependent variable of which was tip-apex distance from the isometric center of the femoral head.

The principal dependent variable in this schedule is the value of dB, which oscillates in response to the subject's choices, eventually approaching a quasi-stable value (the 'indifference delay', dB 50)), which lies between dA short) and dA long).

Blood pressure represents the principal dependent variable for this study, as general practitioners were incentivised directly to lower blood pressure to 150/90 mm Hg or less (see web extra).

With respect to the principal dependent variable of chaperone use, we created a dichotomous "ever/never" variable in which those respondents who reported any use of chaperones in their practice (i.e., always, sometimes, or rarely) are contrasted with those who reported "never" using chaperones in their practice.

The principal dependent variables were VAS and AOFAS scores at the final follow-up as clinical outcomes; postoperative TAS, TT, and TLS angles as radiological outcomes; and ICRS grade at second-look arthroscopy.

Measures of intermediate outcomes (A1C, BP, LDL levels) of diabetes care in patients of providers extracted from the electronic medical record were the principal dependent variables.

The two principal dependent variables were physical functional ability health status and quality of life, a measure of emotional wellbeing, both derived using validated WHO instruments (WHO 2010; WHOQoL Group 1993).

Four principal dependent variables were measured in actual patients: 1) change in A1C and LDL cholesterol testing rates, 2) change in A1C and LDL cholesterol levels, 3) rates of intensification of glucose or lipid medication when patients are not achieving recommended clinical goals, and 4) change in risky prescribing events related to glycemic control.

To test these hypotheses, we compared the scores of the principal components (dependent variables: PC1 PC3) using a factorial ANOVA, with FRAGMENT (1 6) and USE of trap locations (used and unused) as factors.