Key points are not available for this paper at this time.
SUMMARY This paper discusses the use of improved approximations for the estimation of generalized linear multilevel models where the response is a proportion. Simulation studies by Rodriguez and Goldman have shown that in extreme situations large biases can occur, most notably when the response is binary, the number of level 1 units per level 2 unit is small and the underlying random parameter values are large. An improved approximation is introduced which largely eliminates the biases in the situation described by Rodriguez and Goldman. Keywortis: �BINARY RESPONSE; GENERALIZED LINEAR MODEL; HIERARCHICAL DATA; MARGINAL MODEL; MULTILEVEL MODEL; QUASI-LIKELIHOOD; UNIT-SPECIFIC MODEL
Goldstein et al. (Mon,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: