Calibrated random imputation for qualitative data |
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| Institution: | 1. Universidade Lusíada—Norte, Campus de Vila Nova de Famalicão, Largo Tinoco de Sousa, 4760-108 Vila Nova de Famalicão, Portugal;2. Cranfield University, College Road, Cranfield MK43 0AL, United Kingdom;3. Rachel Newton Consulting;1. State Key Laboratory of Powder Metallurgy, Central South University, Changsha 410083, China;2. Zhuzhou Cemented Carbide Cutting Tools Co., Ltd., Zhuzhou 412007, China |
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| Abstract: | In official statistics, when a file of microdata must be delivered to external users, it is very difficult to propose them a file where missing values has been treated by multiple imputations. In order to overcome this difficulty, we propose a method of single imputation for qualitative data that respect numerous constraints. The imputation is balanced on totals previously estimated; editing rules can be respected; the imputation is random, but the totals are not affected by an imputation variance. |
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