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- W3083362879 abstract "Abstract In nonignorable missing response problems, we study a semiparametric model with unspecified missingness mechanism model and a exponential family model for response conditional density. Even though existing methods are available to estimate the parameters in exponential family, estimation or testing of the missingness mechanism model nonparametrically remains to be an open problem. By defining a “synthesis density involving the unknown missingness mechanism model and the known baseline “carrier density in the exponential family model, we treat this “synthesis density as a legitimate one with biased sampling version. We develop maximum pseudo likelihood estimation procedures and the resultant estimators are consistent and asymptotically normal. Since the “synthesis cumulative distribution is a functional of the missingness mechanism model and the known carrier density, proposed method can be used to test the correctness of the missingness mechanism model nonparametrically andindirectly. Simulation studies and real example demonstrate the proposed methods perform very well." @default.
- W3083362879 created "2020-09-11" @default.
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- W3083362879 date "2020-09-30" @default.
- W3083362879 modified "2023-10-18" @default.
- W3083362879 title "Pseudo likelihood‐based estimation and testing of missingness mechanism function in nonignorable missing data problems" @default.
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- W3083362879 doi "https://doi.org/10.1111/sjos.12493" @default.
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