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The final multivariable model is demonstrated in Table 3.
Second, the novel grey multivariable model is established, combined with the changing trends of driving variables.
To this end, a novel grey multivariable model is designed in this paper.
A multivariable model is identified for the experimental flexible structure by using these orthonormal basis functions.
The multivariable model is used to design an H∞ controller for the experimental structure to suppress vibrations.
2 The multivariable model is adjusted for age, body mass index, race, smoking status, history of diabetes, and height.
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The multivariable model was built using all variables significantly associated with ICU mortality in univariate analysis (p < 0.05).
The estimated coefficient for HD in the multivariable model was −20.4 (95% confidence interval: −26.3 to −14.4) (Table 2).
A single multivariable model was produced.
A main effect multivariable model was applied.
In each sample a multivariable model was built.
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