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Unit conversion as a source of misclassification in US birthweight data.

D M Umbach1

  • 1Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, USA. umbach@niehs.nih.gov

American Journal of Public Health
|January 12, 2000
PubMed
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US birthweight data shows spiky frequency polygons due to unit conversion misclassification. Rounding to ounces and converting to grams causes these statistical artifacts in grouped birthweight data.

Area of Science:

  • Biostatistics
  • Public Health

Background:

  • Frequency polygons of US birthweights exhibit unusual spikiness compared to European data.
  • This spikiness has been observed in grouped birthweight datasets.

Purpose of the Study:

  • To explain the cause of spikiness in US birthweight frequency polygons.
  • To investigate the role of unit conversion in data misclassification.

Main Methods:

  • Utilized a probability model to simulate unit conversion effects.
  • Analyzed US and Norwegian birthweight data to demonstrate misclassification.

Main Results:

  • Spikiness in US birthweight data results from rounding to the nearest ounce, conversion to grams, and subsequent grouping.
  • Using 200-g weight classes reduces, but does not eliminate, this misclassification.

Related Experiment Videos

Conclusions:

  • Misclassification due to unit conversion can introduce bias into statistical models of grouped US birthweights.
  • Careful evaluation of potential biases is crucial when analyzing such data.