A Stochastic EM type algorithm for estimation in data with ascertainment on continuous outcomes
2008 (English)Report (Other academic)
Outcome dependent sampling probabilities can be used to increase efficiency in observational studies. For continuous outcomes appropriate consideration of sampling design in estimating parameters of interest is often computationally cumbersome. In this article we suggest a Stochastic EM type algorithm for estimation. The computational complexity of the likelihood is avoided by filling in missing data so that the full data likelihood can be used. The method is not restricted to any specific distribution of the data and can be used for a broad range of statistical models.
Place, publisher, year, edition, pages
2008. , 26 p.
, ISSN 1650-0377 ; 2008:5
Ascertainment, Stochastic EM algorithm, Missing data, Sequential design, Choice-based sampling, Outcome dependent sampling, Genetic epidemiology
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:su:diva-16251OAI: oai:DiVA.org:su-16251DiVA: diva2:182771