Correcting for bias in GEE models with small cluster size

Question

In GEE, several methods have been proposed for correcting for bias when the cluster size is small to moderate (<40). Some have proposed alternative variance estimators, e.g. Morel, Bokossa, and Neerchal (2003), while others have described methods for obtaining bias-corrected estimates of regression coefficients, e.g. Lunardon and Scharfstein (2017).

Would it be advisable to employ both these methods simultaneously?

Lunardon & Scharfstein (2017) https://onlinelibrary.wiley.com/doi/full/10.1002/sim.7366

Morel et al. (2003) https://onlinelibrary.wiley.com/doi/abs/10.1002/bimj.200390021

Answer 1

Answering my own question here. Since the bias-correction methods target different sources of bias, I don't see why not use both. First get the bias-corrected estimates of regression coefficients, then apply the alternative variance estimator.