Journal of Biometrics & Biostatistics

Susan M Gapstur

Publications

• Research Article
  Analysis of Multivariate Disease Classification Data in the Presence of Partially Missing Disease Traits
  Author(s): Jingang Miao, Samiran Sinha, Suojin Wang, W Ryan Diver and Susan M GapsturJingang Miao, Samiran Sinha, Suojin Wang, W Ryan Diver and Susan M Gapstur
  
  In modern cancer epidemiology, diseases are classified based on pathologic and molecular traits, and different combinations of these traits give rise to many disease subtypes. The effect of predictor variables can be measured by fitting a polytomous logistic model to such data. The differences (heterogeneity) among the relative risk parameters associated with subtypes are of great interest to better understand disease etiology. Due to the heterogeneity of the relative risk parameters, when a risk factor is changed, the prevalence of one subtype may change more than that of another subtype does. Estimation of the heterogeneity parameters is difficult when disease trait information is only partially observed and the number of disease subtypes is large. We consider a robust semiparametric approach based on the pseudo-conditional likelihood for estimating these heterogeneity parameters. T.. Read More»
  DOI: 10.4172/2155-6180.1000197

  Abstract PDF