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Assessing goodness-of-fit of categorical regression models based on case-control data
Authors:Biao Zhang
Institution:Dept of Mathematics, The University of Toledo, Toledo, USA
Abstract:Demonstrated equivalence between a categorical regression model based on case‐control data and an I‐sample semiparametric selection bias model leads to a new goodness‐of‐fit test. The proposed test statistic is an extension of an existing Kolmogorov–Smirnov‐type statistic and is the weighted average of the absolute differences between two estimated distribution functions in each response category. The paper establishes an optimal property for the maximum semiparametric likelihood estimator of the parameters in the I‐sample semiparametric selection bias model. It also presents a bootstrap procedure, some simulation results and an analysis of two real datasets.
Keywords:bootstrap  case-control data  logistic regression  mixture sampling  multivariate Gaussian process  multiplicative-intercept risk model  ordinal response  proportional odds model  pseudolikelihood  semiparametric selection bias model  weak convergence
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