Capture‐Recapture, Epidemiology, and List Mismatches: Two Lists

Seber, G. A. F.; Huakau, John; Simmons, David

doi:10.1111/j.0006-341x.2000.01227.x

Cited by 34 publications

(33 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…RBSUME Lorsqu'on applique les mkthodes de capture-recapture pour populations fermBes en Bpidkmiologie, par exemple pour estimer l'effectif d'une population de diabktiques, on rencontre le problhme d'erreurs d'identification dans les listes, dues B des erreurs de saisie ou B des informations erronkes. Ce problhme a ktk ktudik dans le cas de seulement deux listes, par Seber, Huakau et Simmons (2000), en utilisant le concept de perte de marque empruntB aux Btudes de populations animales. Dans ce nouvel article, nous discutons d'une mkthode similaire qui peut Btre Btendue B un nombre quelconque de listes.…”

Section: Discussionunclassified

See 1 more Smart Citation

Capture-Recapture, Epidemiology, and List Mismatches: Several Lists

et al. 2001

Self Cite

View full text Add to dashboard Cite

In applying capture-recapture methods for closed populations to epidemiology, e.g., in the estimation of the size of a diabetes population, one comes up against the problem of list errors due to mistyping or misinformation. This problem has been studied for just two lists by Seber, Huakau, and Simmons (2000, Biometrics 56, 1227 1232) using the concept of tag loss borrowed from animal population studies. In this article, we discuss a similar method that can be extended to an arbitrary number of lists. The methods are applied to an example.

show abstract

Section: Discussionunclassified

“…In this article, we modify the approach of Seber et al (2000) to permit generalization of the methods t o the case where we have more than two lists and the lists are not necessarily independent. In Section 2, we demonstrate that errors in the records (i.e., tag loss) can have a very serious effect on the estimation of population size.…”

Section: Introductionmentioning

confidence: 99%

Capture-Recapture, Epidemiology, and List Mismatches: Several Lists

et al. 2001

Self Cite

View full text Add to dashboard Cite

show abstract

“…Capture-recapture techniques have been used for a number of diseases to estimate the level of ' missing ' data in routine sources [8][9][10][11]. There are four main assumptions underlying this technique : that the underlying population from which the individuals are drawn remains unchanged during the study period, that the lists of individuals being compared are independent, that each member of the population has the same probability of being on a given list, and that individuals are matched correctly [12,13]. It is also important that the case definition for each list has a high specificity (i.e.…”

Section: Discussionmentioning

confidence: 99%

Diagnoses of, and deaths from, severe liver disease due to hepatitis C in England between 2000 and 2005 estimated using multiple data sources

et al. 2008

View full text Add to dashboard Cite

SUMMARYMatching individuals reported to a sentinel surveillance scheme for hepatitis C between 2000 and 2005 to individuals with a hospital episode for hepatitis C-related liver disease in the same hospitals, we estimated that the number of cases of hepatitis C-related end-stage liver disease in these English hospitals was 42% (597/419) higher than Hospital Episode Statistics (HES) would indicate. Further, matching records of hepatitis C-related deaths in HES to death certificates, we estimated that, between 2000 and 2005, the true number of deaths from hepatitis C-related end-stage liver disease was between 185 % (353/124) and 257 % (378/106) higher than the number recorded in routine mortality statistics. We provide estimates of under-recording that can be used to modify existing models of disease burden due to hepatitis C and provide a simple approach to improve the monitoring of trends in severe hepatitis C-related morbidity over time.

show abstract

“…by Seber and Felton [25]. Their technique has recently been generalized to apply to problems in human epidemiology by Seber et al [26], Lee et al [27] and Lee [28]. While our methods are probabilistic, we assume complete and accurate information in the x vector.…”

Section: Discussionmentioning

confidence: 99%

Estimating population size and duplication rates when records cannot be linked

Laska¹,

Meisner²,

Wanderling³

et al. 2003

Statistics in Medicine

View full text Add to dashboard Cite

The capture-recapture approach to estimating the size of a population is a well-studied area of statistics. The number of distinct individuals, N(A) and N(B), on each of two lists, A and B, and the number common to both lists, N(AB), are used to form an estimate of the binomial probability of being on one of the lists, which then allows an estimate to be made of the size of the population. Critical to the method is an accurate count of N(AB). We consider situations in which this count is not available. Such problems arise in a variety of behavioural health contexts in which the need for protection of privacy may prevent sharing identifying information, so it is not possible to specifically match an individual who appears on one list with an individual on the other. Suppose that the birth dates and/or other demographics of individuals on each list are known. We introduce two methods for estimating the duplication rates and the size of the population. Conditioning on the set beta of birth dates of those on list B, N(A) and N(B), the maximum likelihood estimators (MLEs) and their variance are derived. The MLEs are based on the proportion of individuals on list A whose birth dates fall in beta. This approach is particularly useful if list B itself contains duplicates. The second model utilizes the full sample distribution of the birth dates. We generalize this approach to accommodate multiple demographic characteristics. The approaches are applied to the problem of estimating duplication rates and the population size of veterans who have mental illness in Kings County, NY. The data are lists of those receiving service from the Veterans Administration system and from providers funded or certified by the New York State Office of Mental Health.

show abstract

Capture‐Recapture, Epidemiology, and List Mismatches: Two Lists

Cited by 34 publications

References 12 publications

Capture-Recapture, Epidemiology, and List Mismatches: Several Lists

Capture-Recapture, Epidemiology, and List Mismatches: Several Lists

Diagnoses of, and deaths from, severe liver disease due to hepatitis C in England between 2000 and 2005 estimated using multiple data sources

Estimating population size and duplication rates when records cannot be linked

Contact Info

Product

Resources

About