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Exact(9)
There was a positive association with adjusted education minutes in our multivariable model by institution.
Variables that were statistically significant at a 0.05 p-value level in bivariate analyses were selected for the final multivariable model by use of backwards elimination if they did not remain significant.
All variables (clinical and genetic) were taken for multivariable model by backward selection.
All studied variables were used to identify the best final multivariable model by means of forward stepwise procedures based on the Akaike information criterion.
In addition, we tested interactions between variables included in the final multivariable model by creating an interaction term and using a likelihood ratio test.
We investigated a potentially effect modifying role of age at diagnosis (index) date by calculating stratum specific odds ratios for each variable in the multivariable model by age groups (>50 years, 50-59 years, 60-69 years, and ≥70 years).
Similar(51)
We created multivariable models by using the same conditional logistic regression analyses.
Factors that altered the coefficient for Pb in multivariable models by > 10% were retained in the final multivariable models.
Some of these could be partially addressed in multivariable models by controlling for differences in the age structure and median parasite density of study participants.
To discard the fourth, fifth and sixth explanations, we have adjusted our multivariable models by a variable measuring will to live, a positive aspect of psychological attitude [ 29].
12 Previous clinical diagnosis studies from Chicago and northern California identified 109 and 115 abdominal aortic aneurysm events in women, respectively, 10 11 though only the northern California study provided multivariable models by sex.
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