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Digit preference in estimated gestational age.

R M Pickering1

  • 1University of Southampton, Southampton General Hospital, U.K.

Statistics in Medicine
|June 30, 1992
PubMed
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This study introduces a digit preference model for gestational age estimation, finding that accounting for misclassification to even weeks does not significantly alter delivery risk estimates. The model improves accuracy in estimating birth week, crucial for perinatal care.

Area of Science:

  • Perinatal epidemiology
  • Biostatistics
  • Maternal-fetal medicine

Background:

  • Accurate estimation of gestational age is critical for perinatal care and epidemiological studies.
  • Observed digit preference, particularly for even weeks, can introduce bias in gestational age data.
  • Previous models have not fully addressed the nuances of misclassification in gestational age estimation.

Purpose of the Study:

  • To develop and evaluate a digit preference model for gestational age at birth.
  • To incorporate probabilities of misclassification to adjacent even weeks.
  • To assess the impact of this model on the estimation of delivery risks.

Main Methods:

  • Development of a digit preference model for gestational age (20-36 weeks).
  • Inclusion of misclassification probabilities for odd gestational ages to adjacent even weeks.

Related Experiment Videos

  • Extension of the model with linearly decreasing misclassification probabilities.
  • Application of a piecewise exponential model for relative risks of delivery.
  • Fitting the model incorporating digit preference as a generalized bilinear model in GLIM.

    • Main Results:

    • The developed digit preference model accounts for systematic biases in gestational age reporting.
    • Misclassification probabilities were modeled to decrease linearly with gestational age.
    • Estimates of relative risk for delivery, considering a previous spontaneous abortion, were found to be similar whether digit preference was modeled or ignored.
    • The inclusion of the digit preference model did not substantially change the underlying survival model's relative risk estimates.

    Conclusions:

    • A digit preference model can be effectively developed to describe biases in gestational age estimation.
    • While accounting for digit preference is methodologically sound, its impact on relative risk estimates in this specific context was minimal.
    • The findings suggest that for certain analyses, ignoring digit preference may yield similar risk estimates, though explicit modeling offers greater precision.