IDEAS home Printed from https://ideas.repec.org/p/iim/iimawp/wp02008.html

Analysis of Mixed Outcomes: Misclassified Binary Responses and Measurement Error in Covariates

Author

Listed:
  • Roy Surupa
  • Banerjee, Tathagata

Abstract

The focus of this paper is on regression models for mixed binary and continuous outcomes, when the true predictor is measured with error and the binary responses are subject to classification errors. Latent variable is used to model the binary response. The joint distribution is expressed as a product of the marginal distribution of the continuous response and the conditional distribution of the binary response given the continuous response. Models are proposed to incorporate the measurement error and/or classification errors. Likelihood based analysis is performed to estimate the regression parameters of interest. Theoretical studies are made to find the bias of the likelihood estimates of the model parameters. An extensive simulation study is carried out to investigate the effect of ignoring classification errors and/or measurement error on the estimates of the model parameters. The methodology is illustrated with a data set obtained by conducting a small scale survey.

Suggested Citation

  • Roy Surupa & Banerjee, Tathagata, 2007. "Analysis of Mixed Outcomes: Misclassified Binary Responses and Measurement Error in Covariates," IIMA Working Papers WP2007-01-08, Indian Institute of Management Ahmedabad, Research and Publication Department.
    • Handle: RePEc:iim:iimawp:wp02008
    as

    Download full text from publisher

    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/2007-01-08_tbanerjee.pdf
    File Function: English Version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. D. R. Cox, 1972. "The Analysis of Multivariate Binary Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 21(2), pages 113-120, June.
    2. White, Halbert, 1983. "Corrigendum [Maximum Likelihood Estimation of Misspecified Models]," Econometrica, Econometric Society, vol. 51(2), pages 513-513, March.
    3. Christina A. Holcroft & Donna Spiegelman, 1999. "Design of Validation Studies for Estimating the Odds Ratio of Exposure–Disease Relationships When Exposure Is Misclassified," Biometrics, The International Biometric Society, vol. 55(4), pages 1193-1201, December.
    4. Mary J. Morrissey & Donna Spiegelman, 1999. "Matrix Methods for Estimating Odds Ratios with Misclassified Exposure Data: Extensions and Comparisons," Biometrics, The International Biometric Society, vol. 55(2), pages 338-344, June.
    5. Mary Dupuis Sammel & Louise M. Ryan & Julie M. Legler, 1997. "Latent Variable Models for Mixed Discrete and Continuous Outcomes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(3), pages 667-678.
    Full references (including those not matched with items on IDEAS)

    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. Hao Bai & Yuan Zhong & Xin Gao & Wei Xu, 2020. "Multivariate Mixed Response Model with Pairwise Composite-Likelihood Method," Stats, MDPI, vol. 3(3), pages 1-18, July.
    2. Bartolucci, Francesco & Nigro, Valentina, 2012. "Pseudo conditional maximum likelihood estimation of the dynamic logit model for binary panel data," Journal of Econometrics, Elsevier, vol. 170(1), pages 102-116.
    3. Helmut Küchenhoff & Samuel M. Mwalili & Emmanuel Lesaffre, 2006. "A General Method for Dealing with Misclassification in Regression: The Misclassification SIMEX," Biometrics, The International Biometric Society, vol. 62(1), pages 85-96, March.
    4. Sanjoy K. Sinha & Andrea B. Troxel & Stuart R. Lipsitz & Debajyoti Sinha & Garrett M. Fitzmaurice & Geert Molenberghs & Joseph G. Ibrahim, 2011. "A Bivariate Pseudolikelihood for Incomplete Longitudinal Binary Data with Nonignorable Nonmonotone Missingness," Biometrics, The International Biometric Society, vol. 67(3), pages 1119-1126, September.
    5. Aerts, Marc & Claeskens, Gerda, 2001. "Bootstrap tests for misspecified models, with application to clustered binary data," Computational Statistics & Data Analysis, Elsevier, vol. 36(3), pages 383-401, May.
    6. P.A.V.B. Swamy & I-Lok Chang & Jatinder S. Mehta & William H. Greene & Stephen G. Hall & George S. Tavlas, 2016. "Removing Specification Errors from the Usual Formulation of Binary Choice Models," Econometrics, MDPI, vol. 4(2), pages 1-21, June.
    7. Fernando Rios-Avila & Gustavo Canavire-Bacarreza, 2018. "Standard-error correction in two-stage optimization models: A quasi–maximum likelihood estimation approach," Stata Journal, StataCorp LLC, vol. 18(1), pages 206-222, March.
    8. Sandy Fréret & Denis Maguain, 2017. "The effects of agglomeration on tax competition: evidence from a two-regime spatial panel model on French data," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 24(6), pages 1100-1140, December.
    9. Ai, Chunrong & Chen, Xiaohong, 2007. "Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables," Journal of Econometrics, Elsevier, vol. 141(1), pages 5-43, November.
    10. Gregory, Allan W. & McCurdy, Thomas H., 1986. "The unbiasedness hypothesis in the forward foreign exchange market: A specification analysis with application to France, Italy, Japan, the United Kingdom and West Germany," European Economic Review, Elsevier, vol. 30(2), pages 365-381, April.
    11. B. Praag & T. Dijkstra & J. Velzen, 1985. "Least-squares theory based on general distributional assumptions with an application to the incomplete observations problem," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 25-36, March.
    12. Reischmann, Markus, 2016. "Creative accounting and electoral motives: Evidence from OECD countries," Journal of Comparative Economics, Elsevier, vol. 44(2), pages 243-257.
    13. Vassilios Babalos & Mehmet Balcilar & Rangan Gupta, 2014. "Revisiting Herding Behavior in REITs: A Regime-Switching Approach," Working Papers 201448, University of Pretoria, Department of Economics.
    14. Topi Miettinen & Sigrid Suetens, 2008. "Communication and Guilt in a Prisoner's Dilemma," Journal of Conflict Resolution, Peace Science Society (International), vol. 52(6), pages 945-960, December.
    15. Towfiqul Islam Khan & Mashfique Ibne Akbar, 2015. "Illicit Financial Flow in view of Financing the Post-2015 Development Agenda," Southern Voice Occasional Paper 25, Southern Voice.
    16. Corradi, Valentina & Swanson, Norman R., 2004. "A test for the distributional comparison of simulated and historical data," Economics Letters, Elsevier, vol. 85(2), pages 185-193, November.
    17. Hendrik Thiel & Stephan L. Thomsen, 2015. "Individual Poverty Paths and the Stability of Control-Perception," SOEPpapers on Multidisciplinary Panel Data Research 794, DIW Berlin, The German Socio-Economic Panel (SOEP).
    18. Arzheimer, Kai & Evans, Jocelyn, 2010. "Bread and butter à la française: Multiparty forecasts of the French legislative vote (1981-2007)," International Journal of Forecasting, Elsevier, vol. 26(1), pages 19-31, January.
    19. repec:ebl:ecbull:v:3:y:2008:i:5:p:1-7 is not listed on IDEAS
    20. Tobias Hartl & Roland Jucknewitz, 2022. "Approximate state space modelling of unobserved fractional components," Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 75-98, January.
    21. Hao Wu & Michael Browne, 2015. "Random Model Discrepancy: Interpretations and Technicalities (A Rejoinder)," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 619-624, September.

    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:iim:iimawp:wp02008. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/eciimin.html .

    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.