Kohlmann Mareike, Held Leonhard, Grunert Veit Peter
Institute of Statistics, Ludwig-Maximilians University, 80539 Munich, Germany.
Biom J. 2009 Aug;51(4):610-26. doi: 10.1002/bimj.200800157.
To classify patients either as resistant or non-resistant to HIV therapy based on longitudinal viral load profiles, we applied longitudinal quadratic discriminant analysis and examined various measures, mainly derived from the Brier Score, to assess the biomarker performance in terms of discrimination and calibration. The analysis of the application data revealed an increase in performance by using longer profiles instead of single biomarker measurements. Simulations showed that the selection of mixed models for the estimation of the group-specific discriminant rule parameters should be based on BIC, rather than on the best performance measure. An incorrect model selection can lead to spuriously better or worse performance as misclassification and classification certainty regards, especially with increasing length of the profiles and for more complex models with random slopes.
为了根据纵向病毒载量曲线将患者分类为对HIV治疗耐药或不耐药，我们应用了纵向二次判别分析，并研究了各种主要源自布里尔评分的指标，以评估生物标志物在判别和校准方面的性能。对应用数据的分析表明，使用更长的曲线而非单一生物标志物测量可提高性能。模拟结果表明，用于估计组特异性判别规则参数的混合模型选择应基于贝叶斯信息准则（BIC），而非最佳性能指标。错误的模型选择可能导致在误分类和分类确定性方面出现看似更好或更差的性能，尤其是随着曲线长度增加以及对于具有随机斜率的更复杂模型。
