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In many demographic behaviors (e.g., those relating to marriage, contraception, migration, and health), people change among multiple statuses through time, sometimes leaving and then returning to the same status. Data on such behaviors are often collected in surveys as censored event histories. The multistate life table (MSLT) can be used to properly describe, in a single analysis, these complex transitions among multiple states measured in such data, but MSLT is rarely applied in the demographic literature because practical guidance is lacking on how to compute MSLTs with such data. We provide methods for computing MSLT quantities using censored event-history data: namely, transition intensities and probabilities, "state occupancy" probabilities and standard errors, average time spent in specified states, and average number of visits to specified states. Applying these methods to contraceptive use, we find high levels of switching back and forth, particularly between barrier methods and non-use, resulting in high rates of unintended pregnancy.
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In many demographic behaviors, people change among multiple statuses through time, sometimes leaving and then returning to the same status. Such behaviors include change in marital status among never-married, cohabiting, married, separated/divorced, and remarried states; contraceptive switching among different methods and use of no methods and pregnancy; migration to different places; and change between healthy and unhealthy states ending in death by different causes. Data on such behaviors are often collected in surveys as event histories with right-censored data. To properly describe the complex transitions back and forth among multiple states measured in such data, the multistate life table (MSLT) method is appropriate and useful. Despite its usefulness, this method has been rarely applied to event histories with censored data in the demographic literature, largely because practical guidance is lacking on how to compute MSLTs with such data (see Meira-Machado et al. 2006:5).
The purpose of this paper is to provide a step-by-step account of how to obtain from such data the transition probability matrix (the fundamental quantities on which the other life table measures depend), "state occupancy" probabilities (probabilities of being in a particular state at a particular time), average time spent in states, and average number of visits to specified states. In addition, we provide a practical formula for calculating the standard errors of...