کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
415269 681196 2016 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A covariate nonrandomized response model for multicategorical sensitive variables
ترجمه فارسی عنوان
مدل پاسخ غیرتصادفی همگام برای متغیرهای حساس چندطبقه‌ای
کلمات کلیدی
پاسخ امتناع؛ الگوریتم EM؛ امتیازدهی فیشر؛ مدل خطی؛ رگرسیون لجستیک چندمتغیره؛ پاسخ کذب
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی

The diagonal method (DM) is an innovative technique to obtain trustworthy survey data on an arbitrary categorical sensitive characteristic Y∗Y∗ (e.g., income classes, number of tax evasions). The estimation of the unconditional distribution of Y∗Y∗ from DM data has already been shown. Now, a covariate extension of the DM, that is, methods to investigate the dependence of Y∗Y∗ on nonsensitive covariates, is sought. For instance, the dependence of income on gender and profession may be under study. The covariate extensions of privacy-protecting survey designs are broadened by the covariate DM, especially because existing methods focus on binary Y∗Y∗. LR-DM estimation and stratum-wise estimation are described, where the former is based on a logistic regression model, leads to a generalized linear model, and requires computer-intensive methods. The existence of a certain regression estimate is investigated. Moreover, the connection between efficiency of the LR-DM estimation and the degree of privacy protection is studied and appropriate model parameters of the DM are searched. This problem of finding suitable model parameters is rarely addressed for privacy-protecting survey methods for multicategorical Y∗Y∗. Finally, the LR-DM estimation is compared with the stratum-wise estimation. MATLAB programs that conduct the presented estimations are provided as supplemental material (see Appendix E).

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 103, November 2016, Pages 124–138
نویسندگان
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