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Assessing human fertility using several markers of ovulation.

Authors
Dunson-DB; Weinberg-CR; Baird-DD; Kesner-JS; Wilcox-AJ
Source
Stat Med 2001 Mar; 20(6):965-978
NIOSHTIC No.
20031891
Abstract
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.
Keywords
Models; Computer-models; Statistical-analysis; Reproduction; Reproductive-system
Contact
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.
CODEN
SMEDDA
Publication Date
20010330
Document Type
Journal Article
Email Address
dunson1@niehs.nih.gov
Fiscal Year
2001
NTIS Accession No.
NTIS Price
Issue of Publication
6
ISSN
0277-6715
NIOSH Division
DBBS
Source Name
Statistics in Medicine
State
NC; OH
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