An empirical Bayes approach to smoothing in backcalculation of HIV infection rates

J. Liao, R. Brookmeyer

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Backcalculation is a methodology to reconstruct the past human immunodeficiency virus (HIV) infection rates from the AIDS incidence data and incubation distribution by deconvolution. Smoothing has proved important in backcalculation, and a key question is how to choose the amount of smoothing. This paper proposes an empirical Bayes approach in which the smoothing parameter is estimated from the data. We introduce a family of priors that reflect the notion of closeness of neighboring infection rates. The variance parameter in the prior family plays the role of the smoothing parameter and is estimated by a method similar to the residual maximum likelihood in linear random effects model through an efficient EM (expectation/maximization) algorithm. A number of penalized likelihood functions that have been used in backcalculation have an empirical Bayes formulation. A bootstrap confidence interval for the infection rates is proposed. The methodology is illustrated with United States AIDS incidence data.

Original languageEnglish (US)
Pages (from-to)579-588
Number of pages10
JournalBiometrics
Volume51
Issue number2
DOIs
StatePublished - Aug 8 1995

Fingerprint

Empirical Bayes
HIV infections
Deconvolution
Virus Diseases
Viruses
Maximum likelihood
Virus
Infection
Smoothing
Acquired Immunodeficiency Syndrome
Smoothing Parameter
HIV
Likelihood Functions
Incidence
Residual Maximum Likelihood
Bootstrap Confidence Intervals
incidence
Penalized Likelihood
Methodology
Random Effects Model

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

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An empirical Bayes approach to smoothing in backcalculation of HIV infection rates. / Liao, J.; Brookmeyer, R.

In: Biometrics, Vol. 51, No. 2, 08.08.1995, p. 579-588.

Research output: Contribution to journalArticle

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