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Univariate and multivariate models rely upon general linear models.
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Prognostic factors were identified by univariate and multivariate logistic regression models relying on the backward elimination algorithm with a selection level of 0.05.
Multivariate models were built using backstep stepwise techniques.
Age-stratified multivariate models are presented for month of visit.
The multivariate models yielded several rather intriguing findings.
Multivariate models did not improve the performance of CRP alone.
Finally, the multivariate models were formulated.
Accordingly, their contribution in the respective multivariate models is high.
We thus relied on a mixed-effect model by including a random effect in our classical multivariate model [ 22].
Multivariate models were established.
Multivariate models were run.
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