Using an autoregressive model to detect departures from steady states in unequally spaced tumour biomarker data.

@article{Schlain1992UsingAA,
  title={Using an autoregressive model to detect departures from steady states in unequally spaced tumour biomarker data.},
  author={B R Schlain and Philip Lavin and Col Dennis L Hayden},
  journal={Statistics in medicine},
  year={1992},
  volume={11 4},
  pages={515-32}
}
A new method, based on a continuous time autoregressive [CAR(1)] model of time series data, is provided for detecting departures of tumour markers from steady states in breast cancer patients following surgery. A Kalman filter recursive algorithm is used to calculate the likelihood function arising from the CAR(1) model and to calculate recursive residuals, which are monitored by a Shewhart-Cusum scheme. This approach can be used to monitor the serial marker data of large numbers of patients… CONTINUE READING

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