Assessing Human Fertility Using Several Markers of Ovulation

Details

• Personal Author:
  Baird DD ; Dunson DB ; Kesner JS ; Weinberg CR ; Wilcox AJ
• Description:
  In modelling human fertility one ideally accounts for timing of intercourse relative to ovulation. Measurement error in identifying the day of ovulation can bias estimates of fecundability parameters and attenuate estimates of covariate effects. In the absence of a single perfect marker of ovulation, several error prone markers are sometimes obtained. In this paper we propose a semi-parametric mixture model that uses multiple independent markers of ovulation to account for measurement error. The model assigns each method of assessing ovulation a distinct non-parametric error distribution, and corrects bias in estimates of day-specific fecundability. We use a Monte Carlo EM algorithm for joint estimation of (i) the error distribution for the markers, (ii) the error-corrected fertility parameters, and (iii) the couple-specific random effects. We apply the methods to data from a North Carolina fertility study to assess the magnitude of error in measures of ovulation based on urinary luteinizing hormone and metabolites of ovarian hormones, and estimate the corrected day-specific probabilities of clinical pregnancy. [Description provided by NIOSH]
• Subjects:
  Air Pollutants, Occupational Asbestos Dust Environmental Monitoring Inorganic Chemicals Microbiology Mining Occupational Health Particulate Matter Safety
• Keywords:
  Computer-models Models Reproduction Reproductive-system Statistical-analysis
• ISSN:
  0277-6715
• Document Type:
  Text
• Genre:
  Journal Article
• Place as Subject:
  North Carolina ; Ohio ; OSHA Region 4 ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DBBS - Division of Biomedical and Behavioral Sciences
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  20
• Issue:
  6
• NIOSHTIC Number:
  nn:20031891
• Citation:
  Stat Med 2001 Mar; 20(6):965-978
• Contact Point Address:
  D. B. Dunson, Biostatistics Branch, MD A3-03, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, U.S.A.
• Email:
  dunson1@niehs.nih.gov
• Federal Fiscal Year:
  2001
• Peer Reviewed:
  True
• Source Full Name:
  Statistics in Medicine
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:0b922753f642a3e29e250ec530cb40b772fc326e8cc53e7fa91b79f7eeffd9db5301a794612a136c2e0b50867fa9798f6d73224b17118ed01d660cf777baaa02
• Download URL:
  https://stacks.cdc.gov/view/cdc/186005/cdc_186005_DS1.pdf
• File Type:
  [PDF - 115.03 KB ]