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Case-control down-sampling in corpus research
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AI
DOI：10.1515/cllt-2025-0074.png)
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Abstract
En 中文
When corpus researchers have to down-size their data, different techniques may be used to optimize the sub-sample. In alternation studies, one strategy is the selection of instances based on the observed realization of the outcome variable. This is referred to as a case-control design in the health sciences, which have developed a rich methodology surrounding this approach. The present paper argues that corpus linguists should be sounding out the potential for methodological transfer. It pursues three goals. The first is to overcome terminological barriers by making transparent the peculiar jargon associated with this research design. Further, I will provide an overview and illustration of some principles of study design and data analysis that form the core of this method. Finally, distinctive features of case-control down-sampling will be identified, which allows for a focused exploration of the extensive literature related to this approach and also provides guideposts for future methodological work.
Keywords:
case-control study
down-sampling
methodology
study design
thinning
Journal
C
IF:
1.7
Papers:
14
Citations:
0