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Information on the
timing of intercourse relative to ovulation can be incorporated into time
to pregnancy models to improve the power to detect covariate effects, to
estimate the day-specific conception probabilities, and to distinguish
between biological and behavioral effects on fecundability, and therefore
the probability of conception in a menstrual cycle. In this paper, Bayesian
methods are proposed for joint modeling of intercourse behavior and biologic
fecundability. The model accommodates a sterile subpopulation of couples,
general covariate effects, and heterogeneity among fecund couples in menstrual
cycle viability and in frequency of unprotected intercourse. Methods are
described for incorporating cycles with varying amounts of intercourse
information into a single analysis. A Markov chain Monte Carlo algorithm
is outlined for estimation of the posterior distributions of the unknowns.
The methods are applied to data from a North Carolina study of couples
attempting pregnancy.
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