Multivariate Markov chain analysis of the probability of pregnancy in infertile couples undergoing assisted reproduction
January 2002
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BACKGROUND: Estimating the probability of pregnancy leading to delivery and the influence of clinical factors on that probability is of fundamental importance in the treatment counselling of infertile couples. A variety of statistical techniques have been used to analyse fertility data, many borrowed from survival analysis. METHODS AND RESULTS: We propose an alternative method of analysis which is based on a discrete time Markov chain approach, with states 'pregnancy (leading to a delivery)', 'not pregnant', and 'censored' and in which the transition probabilities are dependent both on the clinical characteristics of the patient and the treatment given. CONCLUSIONS: We believe that the method of analysis presented here may be preferable to standard analyses in that it better reflects the clinical situation, it is a truly discrete time analysis applied to a discrete time situation, it explicitly models the censoring process (a process which in itself provides information of interest to the physician) and can be readily extended to a variety of clinical situations.
- Male
- Female
- Humans
- Age Factors
- Regression Analysis
- Pregnancy
- Fertilization in Vitro
- *Markov Chains
- *Reproductive Techniques
- *Treatment Outcome
- Infertility/*therapy
- treatment
- couple
- probability
- model
- analysis
- pregnancy
- markov
- patient
- cycle
- likelihood
- regression
- process
- censoring
- situation
- chain
- study
- function
- delivery
- censoring process
- state
