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Modelling digit preference in fecundability studies.

M S Ridout1, B J Morgan

  • 1Institute of Horticultural Research, Maidstone, Kent, England.

Biometrics
|December 1, 1991
PubMed
Summary
This summary is machine-generated.

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This study introduces a probability model to address digit preference in retrospective fecundability studies. The model accurately accounts for misreporting of conception waiting times, improving data reliability.

Area of Science:

  • Reproductive Epidemiology
  • Biostatistics
  • Statistical Modeling

Background:

  • Retrospective studies assessing fecundability (time to pregnancy) are prone to digit preference, where women may round their reported conception waiting time.
  • This misreporting often favors specific numbers, such as 6 or 12 cycles, potentially biasing study results.

Purpose of the Study:

  • To propose and validate a probability model that accounts for digit preference in reporting conception waiting times.
  • To assess the impact of modeling misreporting on the estimation of fecundability parameters using the beta-geometric distribution.

Main Methods:

  • Development of a probability model incorporating digit preference, assuming misreporting favors certain cycle counts (e.g., 6, 12).
  • Application of the model to two existing datasets on fecundability, comparing model fit with and without misreporting parameters.
Keywords:
BehaviorBiasContraceptionContraceptive Usage--statisticsData AnalysisError SourcesFamily PlanningFecundabilityFecundityMeasurementMenstrual CycleMenstruationModels, TheoreticalReproductionResearch MethodologySmokingStatistical Regression

Related Experiment Videos

  • Estimation of parameters for both the underlying beta-geometric distribution and the misreporting process.

    • Main Results:

    • The proposed model significantly improves the fit of retrospective fecundability data by accounting for digit preference.
    • Inclusion of misreporting parameters caused minimal changes to the estimated parameters of the underlying beta-geometric distribution.
    • Misreporting parameters showed interpretable variations across different women categories and could be used to estimate the prevalence of misreporting.

    Conclusions:

    • The developed probability model effectively addresses digit preference in retrospective fecundability studies.
    • The model enhances the accuracy of estimating conception waiting times and provides insights into reporting biases.
    • This approach offers a valuable tool for analyzing reproductive health data and understanding couple fertility.