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Getting Your Money's Worth! Targeting Resources to Make Cognitive Interviews Most Effective
Jaki McCarthy
USDA/National Agricultural Stat. Service
Cognitive interviews are typically resource intensive and conducted on limited sets of questions and few respondents. To be most effective, questions most likely to have adverse impacts on data quality should be targeted. Respondents most likely to exhibit problems with these questions should likewise be selected. One way to target is to use available information from previous data collections to identify questions with quality problems (e.g. high edit or item imputation rates, greater numbers of requests for assistance answering these questions, etc.) Once a subset of questions has been identified as good candidates for cognitive testing, respondents must also be selected. Data mining techniques, such as classification trees, can be used to determine the type of respondents most likely to contribute to low quality responses. These criteria can be be used to select respondents for cognitive interviews. Once questions have been revised, the same indicators of quality can be used to measure the improvement in data collection using the new questions. This approach has been employed in making revisions to questions on the Census of Agriculture; a case study is presented.