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https://doi.org/10.18148/srm/2019.v1i1.7395
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Tree-based Machine Learning Methods for Survey Research
[journal article]
Abstract Predictive modeling methods from the field of machine learning have become a popular tool across various disciplines for exploring and analyzing diverse data. These methods often do not require specific prior knowledge about the functional form of the relationship under study and are able to adapt t... view more
Predictive modeling methods from the field of machine learning have become a popular tool across various disciplines for exploring and analyzing diverse data. These methods often do not require specific prior knowledge about the functional form of the relationship under study and are able to adapt to complex non-linear and non-additive interrelations between the outcome and its predictors while focusing specifically on prediction performance. This modeling perspective is beginning to be adopted by survey researchers in order to adjust or improve various aspects of data collection and/or survey management. To facilitate this strand of research, this paper (1) provides an introduction to prominent tree-based machine learning methods, (2) reviews and discusses previous and (potential) prospective applications of tree-based supervised learning in survey research, and (3) exemplifies the usage of these techniques in the context of modeling and predicting nonresponse in panel surveys.... view less
Keywords
survey research; method; model; data capture; data quality; panel; response behavior
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
machine learning; predictive models; panel attrition; nonresponse; adaptive design
Document language
English
Publication Year
2019
Page/Pages
p. 73-93
Journal
Survey Research Methods, 13 (2019) 1
ISSN
1864-3361
Status
Published Version; peer reviewed
Licence
Deposit Licence - No Redistribution, No Modifications