Literature DB >> 31270651

Prevalent cohort studies and unobserved heterogeneity.

Niels Keiding1, Katrine Lykke Albertsen2, Helene Charlotte Rytgaard2, Anne Lyngholm Sørensen2.   

Abstract

Consider lifetimes originating at a series of calendar times [Formula: see text]. At a certain time [Formula: see text] a cross-sectional sample is taken, generating a sample of current durations (backward recurrence times) of survivors until [Formula: see text] and a prevalent cohort study consisting of survival times left-truncated at the current durations. A Lexis diagram is helpful in visualizing this situation. Survival analysis based on current durations and prevalent cohort studies is now well-established as long as all covariates are observed. The general problems with unobserved covariates have been well understood for ordinary prospective follow-up studies, with the good help of hazard rate models incorporating frailties: as for ordinary regression models, the added noise generates attenuation in the regression parameter estimates. For prevalent cohort studies this attenuation remains, but in addition one needs to take account of the differential selection of the survivors from initiation [Formula: see text] to cross-sectional sampling at [Formula: see text]. This paper intends to survey the recent development of these matters and the consequences for routine use of hazard rate models or accelerated failure time models in the many cases where unobserved heterogeneity may be an issue. The study was inspired by concrete problems in the study of time-to-pregnancy, and we present various simulation results inspired by this particular application.

Keywords:  Attenuation; Current duration; Survival analysis; Survivor selection; Unobserved heterogeneity

Mesh:

Year:  2019        PMID: 31270651     DOI: 10.1007/s10985-019-09479-9

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


  23 in total

1.  Estimating time to pregnancy from current durations in a cross-sectional sample.

Authors:  Niels Keiding; Kajsa Kvist; Helle Hartvig; Mads Tvede; Svend Juul
Journal:  Biostatistics       Date:  2002-12       Impact factor: 5.899

2.  Feasibility of the current-duration approach to studying human fecundity.

Authors:  Rémy Slama; Béatrice Ducot; Lisbeth Carstensen; Christine Lorente; Elise de La Rochebrochard; Henri Leridon; Niels Keiding; Jean Bouyer
Journal:  Epidemiology       Date:  2006-07       Impact factor: 4.822

Review 3.  Design and analysis of time-to-pregnancy.

Authors:  Thomas H Scheike; Niels Keiding
Journal:  Stat Methods Med Res       Date:  2006-04       Impact factor: 3.021

4.  The role of frailty models and accelerated failure time models in describing heterogeneity due to omitted covariates.

Authors:  N Keiding; P K Andersen; J P Klein
Journal:  Stat Med       Date:  1997 Jan 15-Feb 15       Impact factor: 2.373

5.  The beta-geometric distribution applied to comparative fecundability studies.

Authors:  C R Weinberg; B C Gladen
Journal:  Biometrics       Date:  1986-09       Impact factor: 2.571

6.  Semiparametric modeling of grouped current duration data with preferential reporting.

Authors:  Alexander C McLain; Rajeshwari Sundaram; Marie Thoma; Germaine M Buck Louis
Journal:  Stat Med       Date:  2014-05-27       Impact factor: 2.373

7.  Cumulative incidence rate of medical consultation for fecundity problems--analysis of a prevalent cohort using competing risks.

Authors:  S Duron; R Slama; B Ducot; A Bohet; D N Sørensen; N Keiding; C Moreau; J Bouyer
Journal:  Hum Reprod       Date:  2013-07-09       Impact factor: 6.918

8.  Prevalence of infertility in the United States as estimated by the current duration approach and a traditional constructed approach.

Authors:  Marie E Thoma; Alexander C McLain; Jean Fredo Louis; Rosalind B King; Ann C Trumble; Rajeshwari Sundaram; Germaine M Buck Louis
Journal:  Fertil Steril       Date:  2013-01-03       Impact factor: 7.329

9.  Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication II: associations with persistence of DSM-IV disorders.

Authors:  Katie A McLaughlin; Jennifer Greif Green; Michael J Gruber; Nancy A Sampson; Alan M Zaslavsky; Ronald C Kessler
Journal:  Arch Gen Psychiatry       Date:  2010-02

10.  The hazards of hazard ratios.

Authors:  Miguel A Hernán
Journal:  Epidemiology       Date:  2010-01       Impact factor: 4.822

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  3 in total

1.  In a Stationary Population, the Average Lifespan of the Living Is a Length-Biased Life Expectancy.

Authors:  Elizabeth Wrigley-Field; Dennis Feehan
Journal:  Demography       Date:  2022-02-01

2.  Efficiency of Naive Estimators for Accelerated Failure Time Models under Length-Biased Sampling.

Authors:  Pourab Roy; Jason P Fine; Michael R Kosorok
Journal:  Scand Stat Theory Appl       Date:  2021-03-16       Impact factor: 1.040

3.  Flexible extension of the accelerated failure time model to account for nonlinear and time-dependent effects of covariates on the hazard.

Authors:  Menglan Pang; Robert W Platt; Tibor Schuster; Michal Abrahamowicz
Journal:  Stat Methods Med Res       Date:  2021-09-21       Impact factor: 3.021

  3 in total

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