Sentence examples for multivariate model compared from inspiring English sources

In contrast, in a similar but separate multivariate model, compared with SP respondents, SSP respondents met the criteria for fewer DSM-III psychiatric disorders and were less likely to report impaired instrumental support.

Occupational mercury exposure explains only approximately 10% of the total variance of the multivariate model, compared with > 60% for exposure from personal amalgams.

Also in the multivariate model, compared with respondents with acute health conditions, those with chronic communicable diseases (OR=5.91, 95% CI: 1.44, 24.32), NCDs (OR=2.85, 95% CI: 1.96, 4.14) and other health problems (OR=1.83, 95% CI: 1.27, 2.66) had significantly higher odds of use of health care.

Women with low vitamin D levels at baseline had a 46% higher risk (RR: 1.46; 95% CI: 1.09, 1.96; p = 0.01) of developing severe anemia during follow-up in multivariate models, compared to women with adequate vitamin D levels.

Ward-level deprivation provides better explanatory power than the unhealthy lifestyle index: beta coefficients for the unhealthy lifestyle index were much more attenuated in the multivariate models compared to univariate models than the coefficients for ward-level deprivation.

In the multivariate models, compared with individuals with normal glucose values, cost ratios were significantly increased in diagnosed diabetes (2.98 [95% CI 2.50 3.56]) and when antihyperglycemic drugs were excluded (2.30 [1.91–2.30]).

The results of the multivariate models comparing CE immigrant women and Canadian-born women in Table 4 are generally similar to those for men. Figure 7 plots the estimated earnings trajectories for Canada-born and CE immigrant women with a bachelor's degree based on model 2 and model 3 for the 1991 cohort.

A cutoff criteria of p-value <0.2 on bivariate analysis was used to select variables for inclusion in the multivariate models comparing MDR TB and XDR TB with DS TB (models 1 and 2 respectively).

Our hypothesis was that patients who stated a preference for surgery would have a higher predicted probability of having surgery based on the multivariate regression model, compared to those who were unsure.

In the multivariate logistic regression model, compared with the 50- to 64-year-old age group, older patients were at higher odds of prostate cancer, with an OR of 3.05 (95% CI=2.43 3.83) for the 65- 74-year-old age group, and 3.97 (95% CI=3.16 4.98) for the ⩾75-year-old age group (Table 2).

To predict renal length in MMA subjects, we first created a multivariate model and compared our data to healthy controls in the medical literature using age as the independent variable.