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Poisson Regression with Misclassified Counts: Application to Cervical Cancer Mortality Rates

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  • A. S. Whittemore
  • G. Gong

Abstract

Errors in disease classification can give misleading inferences for covariate effects when the probability of error is itself related to the covariates. More accurate inferences are possible using supplemental data on both true and fallible disease counts at various covariate levels. We present a method for incorporating such supplemental data into disease rate regression and use it to show that, although observed intercountry differences in European cervical cancer mortality rates are exaggerated by errors in death certification, they are not completely explained by such errors.

Suggested Citation

  • A. S. Whittemore & G. Gong, 1991. "Poisson Regression with Misclassified Counts: Application to Cervical Cancer Mortality Rates," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(1), pages 81-93, March.
    • Handle: RePEc:bla:jorssc:v:40:y:1991:i:1:p:81-93
    DOI: 10.2307/2347906
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    1. repec:jss:jstsof:02:i05 is not listed on IDEAS
    2. Kahle, David J. & Young, Phil D. & Greer, Brandi A. & Young, Dean M., 2016. "Confidence intervals for the ratio of two Poisson rates under one-way differential misclassification using double sampling," Computational Statistics & Data Analysis, Elsevier, vol. 95(C), pages 122-132.
    3. Ramalho, Esmeralda A., 2002. "Regression models for choice-based samples with misclassification in the response variable," Journal of Econometrics, Elsevier, vol. 106(1), pages 171-201, January.
    4. Powers, Stephanie & Gerlach, Richard & Stamey, James, 2010. "Bayesian variable selection for Poisson regression with underreported responses," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3289-3299, December.
    5. Ozbugday, F.C., 2012. "Empirical essays on ex post evaluations of competition and regulatory authorities decisions and policy reforms," Other publications TiSEM 3ef7e12f-223a-4622-9d0c-5, Tilburg University, School of Economics and Management.
    6. Sajad Shojaee & Nastaran Hajizadeh & Hadis Najafimehr & Luca Busani & Mohamad Amin Pourhoseingholi & Ahmad Reza Baghestani & Maryam Nasserinejad & Sara Ashtari & Mohammad Reza Zali, 2018. "Bayesian adjustment for trend of colorectal cancer incidence in misclassified registering across Iranian provinces," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-10, December.
    7. Tong Li & Pravin K. Trivedi & Jiequn Guo, 2003. "Modeling Response Bias in Count: A Structural Approach With an Application to the National Crime Victimization Survey Data," Sociological Methods & Research, , vol. 31(4), pages 514-544, May.

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