Bayesian estimation of transition probabilities from repeated cross sections
Publication year
2002Source
Statistica Neerlandica, 56, 1, (2002), pp. 23-33ISSN
Publication type
Article / Letter to editor
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Organization
SW OZ NISCO MT
Journal title
Statistica Neerlandica
Volume
vol. 56
Issue
iss. 1
Page start
p. 23
Page end
p. 33
Subject
Inequality, cohesion and modernization; Ongelijkheid, cohesie en moderniseringAbstract
This paper discusses some simple practical advantages of Markov chain Monte Carlo (MCMC) methods in estimating entry and exit transition probabilities from repeated independent surveys. Simulated data are used to illustrate the usefulness of MCMC methods when the likelihood function has multiple local maxima. Actual data on the evaluation of an HIV prevention intervention program among drug
users are used to demonstrate the advantage of using prior information to enhance parameter identification. The latter example also demonstrates an important strength of the MCMC approach, namely the ability to make inferences on arbitrary functions of model parameters.
This item appears in the following Collection(s)
- Academic publications [238441]
- Electronic publications [122508]
- Faculty of Social Sciences [29483]
- Open Access publications [97504]
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