【摘 要】
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In this paper,we consider the estimation of the regression parameter β defined by an estimating equation E{G[Y,S,X,β]} =0in a surrogate outcome setup,in w
【机 构】
：
AcademyofMathematicsandSystems,ChineseAcademyofScienceNationalInstituteofAllergyandInfectiousDisease
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In this paper,we consider the estimation of the regression parameter β defined by an estimating equation E{G[Y,S,X,β]} =0in a surrogate outcome setup,in which the response variable Y is only partly observed while its easilymeasured surrogate S and the covariate X associated with Y are observed for all individuals.The estimation of β involves both the propensity function of Y given surrogate S and covariate X and the "working outcome regression model" φ(s,x; γ,) for E(Y | s,x).Our procedure yields consistent estimation of β as long as either the propensity score is correctly specified or φ(s,x; y) is correctly specified.More importantly,if the propensity function is correctly specified,the proposed estimator has the smallest trace of the asymptotic covariance matrix among all γ given in the "working outcome regression models" φ(s,x; γ)whether φ is correct or not,and the result is particularly meaningful when φ is misspecified.Simulations are conducted to examine the finite sample performance of the proposed procedure.A real data is analyzed for illustration.
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