MSPE;
bias;
systematic bias;
calibration equation;
reproducibility;
concordance correlation;
intraclass correlation;
type II regression;
D O I:
10.1255/jnirs.244
中图分类号:
O69 [应用化学];
学科分类号:
081704 ;
摘要:
Monitoring of calibration equation performance is essential if high quality of predicted analytical data is to be sustained. In this paper we outline and illustrate the use of some statistical methods which are well suited for postprediction data scrutiny. Mean square prediction error is partitioned into three components, viz, mean bias, systematic bias and random error. Reproducibility measures such as concordance correlation (r(c)), intraclass correlation (r(2)) and correlation between difference and sum (r((X- Y)(X + Y))) are also discussed. Other topics discussed include the maximisation of R-2, type II regression (both variables with error model) and new graphical displays.