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To consider several potential modifiers such as subject and dietary characteristics, a multivariate regression analysis was performed.
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If PS matching had achieved an exact or near exact match between case and comparison practices, differences in observed practice characteristics between the physicians in the treatment and comparison groups might have been negligible, making covariate adjustment for practice characteristics in a multivariate regression unnecessary.
The objective of this study was therefore to examine the association between multiple demographic and disease characteristics with sleep problems using a multivariate regression approach.
Because of multiple associations between maternal and neonatal characteristics with neonatal APAO, we performed a multivariate regression (Table 6).
Associations with baseline characteristics and clinical factors were evaluated using a multivariate regression model.
In a multivariate regression model, no baseline characteristic showed a predictive value for the occurrence of a dermatological event in RA patients on TNF-α-blocking therapy.
We also used a multivariate regression model to control individual characteristics of employees (gender, education, and working years).
By using a multivariate regression model, the incremental cost of the different characteristics of the births was calculated.
To analyze associations between cervical rotation kinematics and self-rated characteristics we used orthogonal Partial Least Squares regression (O-PLS), which is a multivariate regression method.
In Wagstaff et al. [ 12] a multivariate regression approach is used for a decomposition of background characteristics.
A multivariate regression analysis was carried out in this paper.
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