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Fig. 2 | BMC Medical Research Methodology

Fig. 2

From: An investigation of penalization and data augmentation to improve convergence of generalized estimating equations for clustered binary outcomes

Fig. 2

Nested loop plot for the proportion of non-convergence with logistic regression, generalized estimating equations (GEE), single-step augmented GEE (augGEE1), iterated augmented GEE (augGEE) and penalized GEE (pGEE) for the 36 scenarios. For scenarios with small, moderate or large cluster size, the numbers of observations per cluster were sampled from a truncated Poisson distribution with mean 5, 10 or 20, respectively. A moderate or large correlation refers to a correlation coefficient of 0.7 or 0.9 at the level of latent responses. ‘Event rate’ denotes the expected proportion of Y = 1 in a scenario

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BMC Medical Research Methodology

ISSN: 1471-2288

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