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Andishe 2021, 25(1): 101-109 Back to browse issues page
Nonresponse Prediction in an Establishment Survey Using Combination of Machine Learning Methods
Alireza Rezaee, Mojtaba Ganjali *, Ehsan Bahrami
Abstract:   (550 Views)
Nonrespose is a source of error in the survey results and National statistical organizations are always looking for ways to
control and reduce it. Predicting nonrespons sampling units in the survey before conducting the survey is one of the solutions
that can help a lot in reducing and treating the survey nonresponse. Recent advances in technology and the facilitation of
complex calculations have made it possible to apply machine learning methods, such as regression and classification trees
or support vector machines, to many issues, including predicting the nonresponse of sampling units in statistics. . In this
article, while reviewing the above methods, we will predict the nonresponse sampling units in a establishment survey using
them and we will show that the combination of the above methods is more accurate in predicting the correct nonresponse
than any of the methods.
Keywords: Classification and regression trees, logistic regression, nonresponse, Support vector machine
Full-Text [PDF 253 kb]   (184 Downloads)    
Type of Study: Research | Subject: Special
Received: 2020/08/10 | Accepted: 2021/01/20 | Published: 2021/01/29
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Rezaee A, Ganjali M, Bahrami E. Nonresponse Prediction in an Establishment Survey Using Combination of Machine Learning Methods. Andishe. 2021; 25 (1) :101-109
URL: http://andisheyeamari.irstat.ir/article-1-815-en.html

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