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

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. 2012 Copyright American Statistical Association and Taylor & Francis.

authors

• Sinha, Samiran

published proceedings

• JOURNAL OF NONPARAMETRIC STATISTICS

author list (cited authors)

• Sinha, S.

citation count

• 1

complete list of authors

• Sinha, Samiran

publication date

• September 2012

publisher

• Taylor & Francis  Publisher

published in

• Journal of Nonparametric Statistics  Journal

keywords

• Bootstrap Variance
• Case-control
• Conditional Likelihood
• Estimating-equation
• Moment-generating Function
• Nih-aarp Diet And Health Study

Digital Object Identifier (DOI)

• 10.1080/10485252.2012.687735

start page

• 577

end page

• 595

volume

• 24

issue

• 3

URL

• http://dx.doi.org/10.1080/10485252.2012.687735