頁籤選單縮合
題名 | Binary Regressors in Dimension Reduction Models: A New Look at Treatment Comparisons |
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作 者 | Carroll,R. J.; Li,Ker-chau; | 書刊名 | Statistica Sinica |
卷期 | 5:2 1995.07[民84.07] |
頁次 | 頁667-688 |
分類號 | 319.51 |
關鍵詞 | 二元迴歸量; Conditioning; Dimension reduction; Linear design condition; Nonparametric curve fitting; Randomization; SIR; Treatment effect; |
語文 | 英文(English) |
英文摘要 | In this paper, new aspects of treatment comparison are brought out via the dimension reduction model of Li (1991) for general regression settings. Denoting the treatment indicator by Z and the covariate by X, the model Y = g(ν'X + θZ, ε) is discussed in detail. Estimates of ν and θ are obtained without assuming a functional form for g. Our method is based on the use of SIR (sliced inverse regression) for reducing the dimensionality of the covariate, followed by a partial-inverse mean matching method for estimating the treatment effectθ. Asymptotic theory and a simulation study are presented. |
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