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To increase the robustness of range scaling, the range could also be determined by using robust range estimators.
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†Results of univariable and multivariable Poisson regression adjusted for household clustering by using robust variance estimates.
We tested heteroscedasticity in Stata and corrected mild heteroscedasticity by using "robust" and "hc3" procedures.
For GEO data, gene level normalization was performed by using Robust Multi-array Average (RMA) [ 22].
We solve the second problem by using robust estimators for location and scale.
We accounted for patient clustering by using robust standard errors in all analyses [ 24, 25].
All of these cases were confirmed by using robust laboratory methods.
* Adjusted by oxygen administration using robust Poisson Regression.
Adjustments for clustering by practice were made using robust variance estimates.
MT impedance tensors were then estimated in the period range 0.001 1, 000 s using robust processing codes.
This model takes dependencies into account using robust standard errors by clustering at the family level.
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