Literature DB >> 25332076

Estimation and assessment of markov multistate models with intermittent observations on individuals.

J F Lawless1, N Nazeri Rad.   

Abstract

Multistate models provide important methods of analysis for many life history processes, and this is an area where John Klein made numerous contributions. When individuals in a study group are observed continuously so that all transitions between states, and their times, are known, estimation and model checking is fairly straightforward. However, individuals in many studies are observed intermittently, and only the states occupied at the observation times are known. We review methods of estimation and assessment for Markov models in this situation. Numerical studies that show the effects of inter-observation times are provided, and new methods for assessing fit are given. An illustration involving viral load dynamics for HIV-positive persons is presented.

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Year:  2014        PMID: 25332076     DOI: 10.1007/s10985-014-9310-z

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  16 in total

1.  Fitting semi-Markov models to interval-censored data with unknown initiation times.

Authors:  G A Satten; M R Sternberg
Journal:  Biometrics       Date:  1999-06       Impact factor: 2.571

2.  Design of panel studies for disease progression with multiple stages.

Authors:  Wei-Ting Hwang; Ron Brookmeyer
Journal:  Lifetime Data Anal       Date:  2003-09       Impact factor: 1.588

3.  Estimation of integrated transition hazards and stage occupation probabilities for non-Markov systems under dependent censoring.

Authors:  Somnath Datta; Glen A Satten
Journal:  Biometrics       Date:  2002-12       Impact factor: 2.571

4.  Optimal designs for epidemiologic longitudinal studies with binary outcomes.

Authors:  Juha Mehtälä; Kari Auranen; Sangita Kulathinal
Journal:  Stat Methods Med Res       Date:  2011-12-13       Impact factor: 3.021

5.  Semi-Markov models with phase-type sojourn distributions.

Authors:  Andrew C Titman; Linda D Sharples
Journal:  Biometrics       Date:  2010-09       Impact factor: 2.571

6.  Computation of the asymptotic null distribution of goodness-of-fit tests for multi-state models.

Authors:  Andrew C Titman
Journal:  Lifetime Data Anal       Date:  2009-11-01       Impact factor: 1.588

7.  Magnitude of virologic blips is associated with a higher risk for virologic rebound in HIV-infected individuals: a recurrent events analysis.

Authors:  J Troy Grennan; Mona R Loutfy; DeSheng Su; P Richard Harrigan; Curtis Cooper; Marina Klein; Nima Machouf; Julio S G Montaner; Sean Rourke; Christos Tsoukas; Bob Hogg; Janet Raboud
Journal:  J Infect Dis       Date:  2012-04-15       Impact factor: 5.226

8.  Covariate adjustment of event histories estimated from Markov chains: the additive approach.

Authors:  O O Aalen; O Borgan; H Fekjaer
Journal:  Biometrics       Date:  2001-12       Impact factor: 2.571

9.  Regional differences in rates of HIV-1 viral load monitoring in Canada: Insights and implications for antiretroviral care in high income countries.

Authors:  Janet M Raboud; Mona R Loutfy; DeSheng Su; Ahmed M Bayoumi; Marina B Klein; Curtis Cooper; Nima Machouf; Sean Rourke; Sharon Walmsley; Anita Rachlis; P Richard Harrigan; Marek Smieja; Christos Tsoukas; Julio S G Montaner; Robert S Hogg
Journal:  BMC Infect Dis       Date:  2010-02-25       Impact factor: 3.090

Review 10.  Model diagnostics for multi-state models.

Authors:  Andrew C Titman; Linda D Sharples
Journal:  Stat Methods Med Res       Date:  2009-08-04       Impact factor: 3.021

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  1 in total

1.  Poverty dynamics, poverty thresholds and mortality: An age-stage Markovian model.

Authors:  Shayna Fae Bernstein; David Rehkopf; Shripad Tuljapurkar; Carol C Horvitz
Journal:  PLoS One       Date:  2018-05-16       Impact factor: 3.240

  1 in total

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