Literature DB >> 8086603

Estimation of the infection time and latency distribution of AIDS with doubly censored data.

G Gómez1, S W Lagakos.   

Abstract

We consider the nonparametric estimation of the time to infection with HIV and the latency period between infection and the onset of AIDS in data where both the events of infection and AIDS are not directly observed. The methods use self-consistency equations that are more easily and quickly solvable than the nonparametric estimators proposed by De Gruttola and Lagakos (1989, Biometrics 45, 1-11). The techniques are illustrated with data on hemophiliacs who became infected through contamination of the blood factor they were given to control their hemophilia.

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Year:  1994        PMID: 8086603

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  9 in total

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2.  Self-consistency estimation of distributions based on truncated and doubly censored survival data with applications to AIDS cohort studies.

Authors:  J Sun
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4.  A semiparametric regression cure model for doubly censored data.

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5.  Fitting Cox Models with Doubly Censored Data Using Spline-Based Sieve Marginal Likelihood.

Authors:  Zhiguo Li; Kouros Owzar
Journal:  Scand Stat Theory Appl       Date:  2015-11-23       Impact factor: 1.396

6.  A progressive three-state model to estimate time to cancer: a likelihood-based approach.

Authors:  Eddymurphy U Akwiwu; Thomas Klausch; Henriette C Jodal; Beatriz Carvalho; Magnus Løberg; Mette Kalager; Johannes Berkhof; Veerle M H Coupé
Journal:  BMC Med Res Methodol       Date:  2022-06-27       Impact factor: 4.612

7.  Nonparametric inference and uniqueness for periodically observed progressive disease models.

Authors:  Beth Ann Griffin; Stephen W Lagakos
Journal:  Lifetime Data Anal       Date:  2009-07-23       Impact factor: 1.588

8.  Calculating stage duration statistics in multistage diseases.

Authors:  Natalia L Komarova; Craig J Thalhauser
Journal:  PLoS One       Date:  2011-12-07       Impact factor: 3.240

9.  High degree of heterogeneity in Alzheimer's disease progression patterns.

Authors:  Natalia L Komarova; Craig J Thalhauser
Journal:  PLoS Comput Biol       Date:  2011-11-03       Impact factor: 4.475

  9 in total

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