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Left-censored dementia incidences in estimating cohort effects

Author

Listed:
  • Rafael Weißbach

    (University of Rostock)

  • Yongdai Kim

    (Seoul National University)

  • Achim Dörre

    (University of Rostock)

  • Anne Fink

    (German Center for Neurodegenerative Diseases)

  • Gabriele Doblhammer

    (German Center for Neurodegenerative Diseases
    University of Rostock)

Abstract

We estimate the dementia incidence hazard in Germany for the birth cohorts 1900 until 1954 from a simple sample of Germany’s largest health insurance company. Followed from 2004 to 2012, 36,000 uncensored dementia incidences are observed and further 200,000 right-censored insurants included. From a multiplicative hazard model we find a positive and linear trend in the dementia hazard over the cohorts. The main focus of the study is on 11,000 left-censored persons who have already suffered from the disease in 2004. After including the left-censored observations, the slope of the trend declines markedly due to Simpson’s paradox, left-censored persons are imbalanced between the cohorts. When including left-censoring, the dementia hazard increases differently for different ages, we consider omitted covariates to be the reason. For the standard errors from large sample theory, left-censoring requires an adjustment to the conditional information matrix equality.

Suggested Citation

  • Rafael Weißbach & Yongdai Kim & Achim Dörre & Anne Fink & Gabriele Doblhammer, 2021. "Left-censored dementia incidences in estimating cohort effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(1), pages 38-63, January.
  • Handle: RePEc:spr:lifeda:v:27:y:2021:i:1:d:10.1007_s10985-020-09505-1
    DOI: 10.1007/s10985-020-09505-1
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    References listed on IDEAS

    as
    1. Rafael Weißbach & Lucas Radloff, 2020. "Consistency for the negative binomial regression with fixed covariate," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(5), pages 627-641, July.
    2. Ying Chen & Su-Chun Cheng, 2004. "Semiparametric Regression Analysis of Mean Residual Life with Censored Survival Data," U.C. Berkeley Division of Biostatistics Working Paper Series 1146, Berkeley Electronic Press.
    3. T. Cai, 2004. "Semiparametric regression analysis for doubly censored data," Biometrika, Biometrika Trust, vol. 91(2), pages 277-290, June.
    4. Rafael Weißbach & Wladislaw Poniatowski & Walter Krämer, 2013. "Nearest neighbor hazard estimation with left-truncated duration data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 33-47, January.
    5. Weißbach, Rafael & Walter, Ronja, 2010. "A likelihood ratio test for stationarity of rating transitions," Journal of Econometrics, Elsevier, vol. 155(2), pages 188-194, April.
    6. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    7. Kim, Yongdai & Kim, Joungyoun & Jang, Woncheol, 2013. "An EM algorithm for the proportional hazards model with doubly censored data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 41-51.
    8. Yongdai Kim & Lancelot James & Rafael Weissbach, 2012. "Bayesian analysis of multistate event history data: beta-Dirichlet process prior," Biometrika, Biometrika Trust, vol. 99(1), pages 127-140.
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