The unseen sample in cohort studies: Estimation of its size and effect

D. R. Hoover, A. Muñoz, V. Carey, N. Odaka, J. M.G. Taylor, J. S. Chmiel, J. Armstrong, S. H. Vermund

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

Recruitment of disease‐free subjects into cohort studies and measurement of their time from exposure/infection to disease selectively excludes individuals (the unseen sample) who had earlier exposure and who have shorter times to disease. The unseen and observed samples may differ in other characteristics in addition to incubation period and exposure/infection time. For data with known truncation times, we develop non‐parametric maximum likelihood estimates of the size, exposure/infection dates and distribution of incubation time in the unseen sample. We provide procedures to estimate and compensate for the biasing effects due to exclusion of the unseen sample in descriptive and survival analysis. We give consistency properties of these estimates and assess variability using bootstrap methods. One can use imputation to derive the above estimates from data with unknown truncation times that have been estimated parametrically. Application is made to an AIDS cohort study of over 5000 homosexual men. Important estimates obtained from this application are the annual seroconversion rates from 1978 to 1983, not otherwise obtainable in this study population.

Original languageEnglish (US)
Pages (from-to)1993-2003
Number of pages11
JournalStatistics in Medicine
Volume10
Issue number12
DOIs
StatePublished - Jan 1 1991
Externally publishedYes

Fingerprint

Cohort Study
Cohort Studies
Infection
Truncation
Estimate
Nonparametric Maximum Likelihood
Likelihood Functions
Survival Analysis
Imputation
Bootstrap Method
Maximum Likelihood Estimate
Date
Annual
Acquired Immunodeficiency Syndrome
Unknown
Population

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Statistics and Probability

Cite this

Hoover, D. R., Muñoz, A., Carey, V., Odaka, N., Taylor, J. M. G., Chmiel, J. S., ... Vermund, S. H. (1991). The unseen sample in cohort studies: Estimation of its size and effect. Statistics in Medicine, 10(12), 1993-2003. https://doi.org/10.1002/sim.4780101212
Hoover, D. R. ; Muñoz, A. ; Carey, V. ; Odaka, N. ; Taylor, J. M.G. ; Chmiel, J. S. ; Armstrong, J. ; Vermund, S. H. / The unseen sample in cohort studies : Estimation of its size and effect. In: Statistics in Medicine. 1991 ; Vol. 10, No. 12. pp. 1993-2003.
@article{cb4d8d1cdf6d4a26995946bf595f6f8d,
title = "The unseen sample in cohort studies: Estimation of its size and effect",
abstract = "Recruitment of disease‐free subjects into cohort studies and measurement of their time from exposure/infection to disease selectively excludes individuals (the unseen sample) who had earlier exposure and who have shorter times to disease. The unseen and observed samples may differ in other characteristics in addition to incubation period and exposure/infection time. For data with known truncation times, we develop non‐parametric maximum likelihood estimates of the size, exposure/infection dates and distribution of incubation time in the unseen sample. We provide procedures to estimate and compensate for the biasing effects due to exclusion of the unseen sample in descriptive and survival analysis. We give consistency properties of these estimates and assess variability using bootstrap methods. One can use imputation to derive the above estimates from data with unknown truncation times that have been estimated parametrically. Application is made to an AIDS cohort study of over 5000 homosexual men. Important estimates obtained from this application are the annual seroconversion rates from 1978 to 1983, not otherwise obtainable in this study population.",
author = "Hoover, {D. R.} and A. Mu{\~n}oz and V. Carey and N. Odaka and Taylor, {J. M.G.} and Chmiel, {J. S.} and J. Armstrong and Vermund, {S. H.}",
year = "1991",
month = "1",
day = "1",
doi = "10.1002/sim.4780101212",
language = "English (US)",
volume = "10",
pages = "1993--2003",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "John Wiley and Sons Ltd",
number = "12",

}

Hoover, DR, Muñoz, A, Carey, V, Odaka, N, Taylor, JMG, Chmiel, JS, Armstrong, J & Vermund, SH 1991, 'The unseen sample in cohort studies: Estimation of its size and effect', Statistics in Medicine, vol. 10, no. 12, pp. 1993-2003. https://doi.org/10.1002/sim.4780101212

The unseen sample in cohort studies : Estimation of its size and effect. / Hoover, D. R.; Muñoz, A.; Carey, V.; Odaka, N.; Taylor, J. M.G.; Chmiel, J. S.; Armstrong, J.; Vermund, S. H.

In: Statistics in Medicine, Vol. 10, No. 12, 01.01.1991, p. 1993-2003.

Research output: Contribution to journalArticle

TY - JOUR

T1 - The unseen sample in cohort studies

T2 - Estimation of its size and effect

AU - Hoover, D. R.

AU - Muñoz, A.

AU - Carey, V.

AU - Odaka, N.

AU - Taylor, J. M.G.

AU - Chmiel, J. S.

AU - Armstrong, J.

AU - Vermund, S. H.

PY - 1991/1/1

Y1 - 1991/1/1

N2 - Recruitment of disease‐free subjects into cohort studies and measurement of their time from exposure/infection to disease selectively excludes individuals (the unseen sample) who had earlier exposure and who have shorter times to disease. The unseen and observed samples may differ in other characteristics in addition to incubation period and exposure/infection time. For data with known truncation times, we develop non‐parametric maximum likelihood estimates of the size, exposure/infection dates and distribution of incubation time in the unseen sample. We provide procedures to estimate and compensate for the biasing effects due to exclusion of the unseen sample in descriptive and survival analysis. We give consistency properties of these estimates and assess variability using bootstrap methods. One can use imputation to derive the above estimates from data with unknown truncation times that have been estimated parametrically. Application is made to an AIDS cohort study of over 5000 homosexual men. Important estimates obtained from this application are the annual seroconversion rates from 1978 to 1983, not otherwise obtainable in this study population.

AB - Recruitment of disease‐free subjects into cohort studies and measurement of their time from exposure/infection to disease selectively excludes individuals (the unseen sample) who had earlier exposure and who have shorter times to disease. The unseen and observed samples may differ in other characteristics in addition to incubation period and exposure/infection time. For data with known truncation times, we develop non‐parametric maximum likelihood estimates of the size, exposure/infection dates and distribution of incubation time in the unseen sample. We provide procedures to estimate and compensate for the biasing effects due to exclusion of the unseen sample in descriptive and survival analysis. We give consistency properties of these estimates and assess variability using bootstrap methods. One can use imputation to derive the above estimates from data with unknown truncation times that have been estimated parametrically. Application is made to an AIDS cohort study of over 5000 homosexual men. Important estimates obtained from this application are the annual seroconversion rates from 1978 to 1983, not otherwise obtainable in this study population.

UR - http://www.scopus.com/inward/record.url?scp=0026328835&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026328835&partnerID=8YFLogxK

U2 - 10.1002/sim.4780101212

DO - 10.1002/sim.4780101212

M3 - Article

C2 - 1805323

AN - SCOPUS:0026328835

VL - 10

SP - 1993

EP - 2003

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 12

ER -