Quasi-likelihood is a statistical concept that extends the notion of likelihood by allowing for the estimation of parameters in models where the distribution of the data is not fully specified. It provides a way to analyze data that may exhibit correlations or other complexities, particularly in the context of generalized estimating equations, which focus on estimating population-averaged effects in clustered or correlated data. This approach leverages robust variance estimates to make inferences without needing a full likelihood specification.
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