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The sandwich estimator accounts for the clustering in the data and corrects standard errors, which leads to fewer biases.
Reflecting the clustering in the data, the outcomes will be compared using multilevel models, with adjustment for minimisation variables [ 19].
The clustering in the data was accounted for by a random intercept at patient level and at centre level.
An initial confirmatory factor model with the full set of 21 importance-weighted items was fitted to adjust for the clustering in the data.
This specification ignores the clustering in the data and assumes that each individual health state value is an independent observation, regardless of whether or not it was valued by the same respondent.
Accurate predictions are not necessarily achieved with a random effects model (having different regression parameters compared to a standard model), because the random effects are not readily applicable in new data with new clusters and the clustering in the data may be weak resulting in minor differences between the models.
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Network layout was carried automatically using the 'organic' layout option that visualizes the clusters in the data.
This suggests that O-HARP can identify all the clusters in the evaluation data set, but there is not a single threshold value that can produce the ideal filtering across all clusters.
An indication of the purity (precision) of the clusters in the augmented training data set can be viewed in Table 4.
The area under the ROC curve for the model was determined; although to obtain a 95% confidence interval of the area under the curve, clustering in the data was disregarded.
High values in the contour map indicate space-time clustering in the data.
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