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- W22277511 abstract "The concept of an estimating function unifies the discussion of estimation in parametric and semi-parametric contexts. Both the maximum likelihood estimating equation and the least squares (normal) estimating equations are unbiased, in the sense that the corresponding estimating functions have expectation 0 under the motivating models. An estimating function can be viewed both as a vehicle for estimation and as a way of defining a parameter, the object of estimation. Certain improvements to interval estimation are available, depending on more refined approximations than normality. They can be described in an inverse testing formulation. It is well known that in cases of unit non-response, an unbiased estimator of the complete data estimating function can be obtained by inverse response probability weighting of the observed data estimating function. In particular, they have made use of systems of estimating equations for joint estimation of the response probability parameters, the regression parameters, and the imputed estimator." @default.
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- W22277511 date "2009-01-01" @default.
- W22277511 modified "2023-09-26" @default.
- W22277511 title "Estimating Functions and Survey Sampling" @default.
- W22277511 doi "https://doi.org/10.1016/s0169-7161(09)00226-0" @default.
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