Optimal Integrating Learning for Split Questionnaire Design Type Data

نویسندگان

چکیده

In the era of data science, it is common to encounter with different subsets variables obtained for cases. An example split questionnaire design (SQD), which adopted reduce respondent fatigue and improve response rates by assigning sampled respondents. A general question then how estimate regression function based on such block-wise observed data. Currently, this often carried out aid missing methods, may unfortunately suffer from intensive computational cost, high variability, possible large modeling biases in real applications. article, we develop a novel approach estimating SQD-type We first construct list candidate models using available data-blocks separately, combine estimates properly make an efficient use all information. show resulting averaged model asymptotically optimal sense that squared loss risk are equivalent those best but infeasible estimator. Both simulated examples application SQD dataset European Social Survey promise proposed method. Supplementary materials article online.

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ژورنال

عنوان ژورنال: Journal of Computational and Graphical Statistics

سال: 2022

ISSN: ['1061-8600', '1537-2715']

DOI: https://doi.org/10.1080/10618600.2022.2118753