Stepping back from the immediate question of whether the CCES in fact shows a low rate of voting among non-citizens, our analysis carries a much broader lesson and caution about the analysis of big databases to study low frequency characteristics and behaviors. Very low levels of measurement error are easily tolerated in samples of 1,000 to 2,000 persons. But in very large sample surveys, classification errors in a high-frequency category can readily contaminate a low-frequency category, such as non-citizens. As a result, researchers may draw incorrect inferences concerning the behavior of relatively rare individuals in a population when there is even a very low level of misclassification.
Blogs I Follow
- Great story on gender equality (er, lack thereof) in professional labor markets in Japan
- More annals of correlations wrongly attributed as causation: The more equal women and men are, the less they want the same things
- In happened sooner than I thought: Baobab beer in microbrewery in New Jersey
- Building housing in San Jose
- Readings on immigration issues in the United States
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