Abstract
Standard errors of maximum likelihood estimators are commonly estimated from the inverse of the information matrix. When the information matrix is a function of parameters, some of which are estimated with little precision, the standard error may be estimated very poorly. This problem is discussed in the context of two-level (random-coefficient) models, and some remedies are proposed.
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Schedule a callMore From: Journal of the Royal Statistical Society: Series D (The Statistician)
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