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To adjust for the clustering of patients within hospitals, a multilevel logistics regression was applied on all unplanned readmissions to examine the factors relating to the characteristics of index hospitalization that induced the avoidable readmission at 95% confidence intervals using the software Stata.
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Multilevel logistic regression models used SAS GLIMMIX.
We used multilevel logistic regression analysis to identify factors associated with hospital mortality.
A multilevel logistic regression approach was used.
Multilevel logistic regression analyses were applied.
Descriptive, bivariate, and multilevel logistic regression analyses.
Multilevel logistic regression analyses were performed.
Multilevel logistic regression analyses were performed with MLwiN, a statistical program for multilevel analyses [ 16].
Associations were determined by using sex-specific multilevel logistic regression.
We fit the marginal multilevel logistic regression model using PROC GENMOD.
Multilevel logistic regression in Stata was applied [ 48].
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