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- W2274623894 abstract "Author(s): Donohue, Michael C; Gamst, Anthony C; Rissman, Robert A; Abramson, Ian | Abstract: We discuss semiparametric regression when only the ranks of responses are observed. The model is $Y_i = F (mathbf{x}_i'{boldsymbolbeta}_0 + varepsilon_i)$, where $Y_i$ is the unobserved response, $F$ is a monotone increasing function, $mathbf{x}_i$ is a known $p-$vector of covariates, ${boldsymbolbeta}_0$ is an unknown $p$-vector of interest, and $varepsilon_i$ is an error term independent of $mathbf{x}_i$. We observe ${(mathbf{x}_i,R_n(Y_i)) : i = 1,ldots ,n}$, where $R_n$ is the ordinal rank function. We explore a novel estimator under Gaussian assumptions. We discuss the literature, apply the method to an Alzheimer's disease biomarker, conduct simulation studies, and prove consistency and asymptotic normality." @default.
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- W2274623894 date "2016-02-24" @default.
- W2274623894 modified "2023-09-27" @default.
- W2274623894 title "Regression of ranked responses when raw responses are censored" @default.
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