Sensitivity analysis provides a mean-square-error measure of how the maximum-likelihood (ML) estimates of parameters of interest would change with changes in parameters not being estimated (i.e., nuisance parameters). This type of sensitivity analysis alone does not provide confidence intervals that include the uncertainty in nuisance parameters, whereas nuisance parameter analysis does provide such confidence intervals. The connection between these two analyses is discussed.
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