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Multivariate logistic regression analyses, using robust errors to account for the same individual rating multiple ads, were performed to compare the eight ads on each outcome.
Significance of difference between intervention and control determined by logistic regression using standard robust errors in order to adjust for clustering by centre.
Generalized linear mixed model with robust errors was used to examine the influence of factors such as such as time of day and day of week of the call on the likelihood of talking to an individual on the phone.
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The Lorentzian norm has desirable robust error metric properties.
The developed theoretical framework includes robust estimation and filtering methods, as well as robust error metrics.
Another difficulty is due to the non-linearity of the robust error function.
A robust error analysis was undertaken to determine the optimum methodology to convert image light intensity to concentration.
We observed robust error-related activation in the dorsal ACC and activation in the ventral lateral prefrontal cortex during PES [10], [12].
In place of this, we used a generalized estimating equation modified Poisson regression approach with robust error variance to produce direct assessments of the relative risks [27].
A Poisson regression model was fitted with robust error variance.
b Education-related relative index of inequality calculated using Poisson regression with robust error variance.
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