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Hierarchical models allow examination of the effect of data clustering on outcomes.
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Careful consideration should be given to whether the covariance with the fixed effects outweighs the disadvantages of data clustering.
Multilevel logistic regression (GEE modeling) accounting for the effects of data clustering and confounding factors confirmed this finding.
Some surgical factors such as volume, grade of surgeon, and approach have been included in analyses, but analysis of the effects of data clustering (in terms of surgeon and unit) was not possible.
This approach does not account for the effect of clustered data as a result of the two-stage cluster sampling designs employed by the DHS, MICS and MIS, and thus the statistical tests used here may slightly overestimate statistical significance.
Specifying this option leads to robust standard errors in the sense that the estimates provide correct standard errors in the presence of the effects of clustered data [33].
Data were examined for the effect of clustering.
We found a positive, nonlinear association between midazolam consumption and length of MV (P = 0.022), adjusted for SAPS III score and taking account the effect of repeated and clustered data.
(a) Effect of clustering with different Distance on the number of clusters.
Multivariate two-level logistic regression analysis (GEE modeling) which can account for the effects of confounding factors and data clustering was adopted [ 29].
The SUDAAN software also took into account effects of clustering in the data, including multiple occupants in the same household.
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