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A functional method for the conditional logistic regression with errors-in-covariates

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  • Samiran Sinha

Abstract

In this article, we develop a functional approach for handling errors-in-covariates in matched case–control studies which are commonly analysed through the conditional logistic regression. We propose to estimate the parameters from a set of unbiased estimating equations. We require that the moment-generating function of the measurement errors exists. We investigate the asymptotic properties of the estimators. The finite sample performance of the method is judged via simulation studies. The proposed methodology is illustrated by analysing the data from the NIH-AARP Diet and Health study.

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  • Samiran Sinha, 2012. "A functional method for the conditional logistic regression with errors-in-covariates," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 577-595.
    • Handle: RePEc:taf:gnstxx:v:24:y:2012:i:3:p:577-595
    DOI: 10.1080/10485252.2012.687735
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    Cited by:

    1. Yih-Huei Huang & Chi-Chung Wen & Yu-Hua Hsu, 2015. "The Extensively Corrected Score for Measurement Error Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(4), pages 911-924, December.

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