IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v60y2004i2p510-516.html
   My bibliography  Save this article

A Multiple-Record Systems Estimation Method that Takes Observed and Unobserved Heterogeneity into Account

Author

Listed:
  • Elena Stanghellini
  • Peter G. M. van der Heijden

Abstract

No abstract is available for this item.

Suggested Citation

  • Elena Stanghellini & Peter G. M. van der Heijden, 2004. "A Multiple-Record Systems Estimation Method that Takes Observed and Unobserved Heterogeneity into Account," Biometrics, The International Biometric Society, vol. 60(2), pages 510-516, June.
    • Handle: RePEc:bla:biomet:v:60:y:2004:i:2:p:510-516
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2004.00197.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. S. E. Fienberg & M. S. Johnson & B. W. Junker, 1999. "Classical multilevel and Bayesian approaches to population size estimation using multiple lists," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(3), pages 383-405.
    2. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    3. Brent A. Coull & Alan Agresti, 1999. "The Use of Mixed Logit Models to Reflect Heterogeneity in Capture-Recapture Studies," Biometrics, The International Biometric Society, vol. 55(1), pages 294-301, March.
    4. Francesco Bartolucci & Antonio Forcina, 2001. "Analysis of Capture-Recapture Data with a Rasch-Type Model Allowing for Conditional Dependence and Multidimensionality," Biometrics, The International Biometric Society, vol. 57(3), pages 714-719, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shira Mitchell & Al Ozonoff & Alan M. Zaslavsky & Bethany Hedt-Gauthier & Kristian Lum & Brent A. Coull, 2013. "A Comparison of Marginal and Conditional Models for Capture–Recapture Data with Application to Human Rights Violations Data," Biometrics, The International Biometric Society, vol. 69(4), pages 1022-1032, December.
    2. Baffour Bernard & Brown James J. & Smith Peter W.F., 2021. "Latent Class Analysis for Estimating an Unknown Population Size – with Application to Censuses," Journal of Official Statistics, Sciendo, vol. 37(3), pages 673-697, September.
    3. Francesco Bartolucci & Fulvia Pennoni, 2007. "A Class of Latent Markov Models for Capture–Recapture Data Allowing for Time, Heterogeneity, and Behavior Effects," Biometrics, The International Biometric Society, vol. 63(2), pages 568-578, June.
    4. R. King & S. P. Brooks, 2008. "On the Bayesian Estimation of a Closed Population Size in the Presence of Heterogeneity and Model Uncertainty," Biometrics, The International Biometric Society, vol. 64(3), pages 816-824, September.
    5. Peter G. M. van der Heijden & Maarten Cruyff & Paul A. Smith & Christine Bycroft & Patrick Graham & Nathaniel Matheson‐Dunning, 2022. "Multiple system estimation using covariates having missing values and measurement error: Estimating the size of the Māori population in New Zealand," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 156-177, January.
    6. Di Cecco Davide & Di Zio Marco & Filipponi Danila & Rocchetti Irene, 2018. "Population Size Estimation Using Multiple Incomplete Lists with Overcoverage," Journal of Official Statistics, Sciendo, vol. 34(2), pages 557-572, June.
    7. Thandrayen, Joanne & Wang, Yan, 2009. "A latent variable regression model for capture-recapture data," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2740-2746, May.
    8. Danilo Fegatelli & Luca Tardella, 2013. "Improved inference on capture recapture models with behavioural effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(1), pages 45-66, March.
    9. Na You & Chang Xuan Mao, 2008. "Population Size Estimation in a Two-List Surveillance System with a Discrete Covariate," Biometrics, The International Biometric Society, vol. 64(2), pages 371-376, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. R. King & S. P. Brooks, 2008. "On the Bayesian Estimation of a Closed Population Size in the Presence of Heterogeneity and Model Uncertainty," Biometrics, The International Biometric Society, vol. 64(3), pages 816-824, September.
    2. Chang Xuan Mao & Cuiying Yang & Yitong Yang & Wei Zhuang, 2017. "Estimating population sizes with the Rasch model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(3), pages 705-716, June.
    3. Francesco Bartolucci & Antonio Forcina, 2001. "Analysis of Capture-Recapture Data with a Rasch-Type Model Allowing for Conditional Dependence and Multidimensionality," Biometrics, The International Biometric Society, vol. 57(3), pages 714-719, September.
    4. Shira Mitchell & Al Ozonoff & Alan M. Zaslavsky & Bethany Hedt-Gauthier & Kristian Lum & Brent A. Coull, 2013. "A Comparison of Marginal and Conditional Models for Capture–Recapture Data with Application to Human Rights Violations Data," Biometrics, The International Biometric Society, vol. 69(4), pages 1022-1032, December.
    5. Richard Arnold & Yu Hayakawa & Paul Yip, 2010. "Capture–Recapture Estimation Using Finite Mixtures of Arbitrary Dimension," Biometrics, The International Biometric Society, vol. 66(2), pages 644-655, June.
    6. J. Andrew Royle, 2006. "Site Occupancy Models with Heterogeneous Detection Probabilities," Biometrics, The International Biometric Society, vol. 62(1), pages 97-102, March.
    7. Félix-Medina Martín Humberto, 2021. "Combining Cluster Sampling and Link-Tracing Sampling to Estimate Totals and Means of Hidden Populations in Presence of Heterogeneous Probabilities of Links," Journal of Official Statistics, Sciendo, vol. 37(4), pages 865-905, December.
    8. Robert M. Dorazio & J. Andrew Royle, 2005. "Rejoinder to "The Performance of Mixture Models in Heterogeneous Closed Population Capture-Recapture"," Biometrics, The International Biometric Society, vol. 61(3), pages 874-876, September.
    9. Baffour Bernard & Brown James J. & Smith Peter W.F., 2021. "Latent Class Analysis for Estimating an Unknown Population Size – with Application to Censuses," Journal of Official Statistics, Sciendo, vol. 37(3), pages 673-697, September.
    10. Robert M. Dorazio & J. Andrew Royle, 2003. "Mixture Models for Estimating the Size of a Closed Population When Capture Rates Vary among Individuals," Biometrics, The International Biometric Society, vol. 59(2), pages 351-364, June.
    11. Francesco Bartolucci & Fulvia Pennoni, 2007. "A Class of Latent Markov Models for Capture–Recapture Data Allowing for Time, Heterogeneity, and Behavior Effects," Biometrics, The International Biometric Society, vol. 63(2), pages 568-578, June.
    12. Nguimkeu, Pierre & Denteh, Augustine & Tchernis, Rusty, 2019. "On the estimation of treatment effects with endogenous misreporting," Journal of Econometrics, Elsevier, vol. 208(2), pages 487-506.
    13. Richard Dennis, 2000. "Steps toward identifying central bank policy preferences," Working Paper Series 2000-13, Federal Reserve Bank of San Francisco.
    14. Kocięcki, Andrzej & Kolasa, Marcin, 2023. "A solution to the global identification problem in DSGE models," Journal of Econometrics, Elsevier, vol. 236(2).
    15. Jean-Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 767-808, November.
    16. Browning, Martin & Carro, Jesus M., 2014. "Dynamic binary outcome models with maximal heterogeneity," Journal of Econometrics, Elsevier, vol. 178(2), pages 805-823.
    17. Carvalho Lopes, Celia Mendes & Bolfarine, Heleno, 2012. "Random effects in promotion time cure rate models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 75-87, January.
    18. Hayakawa, Kazuhiko, 2016. "Identification problem of GMM estimators for short panel data models with interactive fixed effects," Economics Letters, Elsevier, vol. 139(C), pages 22-26.
    19. Elena Stanghellini & Eduwin Pakpahan, 2015. "Identification of causal effects in linear models: beyond instrumental variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 489-509, September.
    20. Neusser, Klaus, 2016. "A topological view on the identification of structural vector autoregressions," Economics Letters, Elsevier, vol. 144(C), pages 107-111.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:biomet:v:60:y:2004:i:2:p:510-516. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.