Comparison of Validation Likelihood Estimator for Randomized Response Data with Missing Covariates in Logistic Regression / 隨機作答模式於確認概似估計法伴隨共變數缺失之邏輯斯迴歸有效性探討

碩士 / 逢甲大學 / 統計與精算所 / 97 / Randomized response technique (RRT) is commonly used to guaranty privacy and reduce the number of dishonest responses to sensitive questions in a survey research. The procedure yields a more accurate estimate of the proportion of the prevalent population. This article deals with logistic regression of data obtained from the unrelated question RRT (Greenberg et al. 1969) design when the covariate data are missing at random (MAR) or completely at random (MCAR). In particular, we compare the efficiency of the validation likelihood estimator using different estimates of the selection probabilities, which may be treated as nuisance parameters. Furthermore, we develop the large sample theory, and show that, they are more efficient than the estimator using the true selection probability. The proposed method is illustrated using data from a cable TV study in Taiwan.

Identiferoai:union.ndltd.org:TW/097FCU05336013
Date January 2009
CreatorsShu-Ching Chang, 張舒晴
ContributorsShen-Ming Lee, 李燊銘
Source SetsNational Digital Library of Theses and Dissertations in Taiwan
Languagezh-TW
Detected LanguageEnglish
Type學位論文 ; thesis
Format58

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