Modifications of the EM algorithm for survival influenced by an unobserved stochastic process


Journal Article

Let Y=(Yt)t≥0) be an unobserved random process which influences the distribution of a random variable T which can be interpreted as the time to failure. When a conditional hazard rate corresponding to T is a quadratic function of covariates, Y, the marginal survival function may be represented by the first two moments of the conditional distribution of Y among survivors. Such a representation may not have an explicit parametric form. This makes it difficult to use standard maximum likelihood procedures to estimate parameters - especially for censored survival data. In this paper a generalization of the EM algorithm for survival problems with unobserved, stochastically changing covariates is suggested. It is shown that, for a general model of the stochastic failure model, the smoothing estimates of the first two moments of Y are of a specific form which facilitates the EM type calculations. Properties of the algorithm are discussed. © 1994.

Full Text

Duke Authors

Cited Authors

  • Yashin, AI; Manton, KG

Published Date

  • January 1, 1994

Published In

Volume / Issue

  • 54 / 2

Start / End Page

  • 257 - 274

International Standard Serial Number (ISSN)

  • 0304-4149

Digital Object Identifier (DOI)

  • 10.1016/0304-4149(94)00012-3

Citation Source

  • Scopus