Your English writing platform
Discover LudwigExact(60)
Initially, we also estimated GEE models employing an exchangeable working correlation but this resulted in unreasonable (i.e., negative) working correlation estimates for both IRU and CRU.
For all models, we used an unstructured working correlation matrix and a robust estimator covariance matrix.
The working correlation matrix was set to exchangeable because symmetry was assumed.
A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis.
We used M-dependent as working correlation matrix structure and logit as link function * p < 0.05; ** p < 0.01; *** p < 0.001.
The GEE models were estimated using a binomial distribution, independent working correlation matrix and a logit link function.
GEE models were implemented in SPSS 16 using an unstructured working correlation matrix.
GEEs use working correlation matrices to take the correlation into account and provide unbiased estimates even if the working correlation matrix is misspecified, albeit at the potential loss of efficiency.
An exchangeable working correlation structure was selected and the results verified to be similar assuming other applicable correlation structures.
An exchangeable working correlation matrix was assumed.
Independence was used as working correlation matrix.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com