Question about the shrinkage correction when building a scoring system

data analysis
1

I’m trying to build a score system as a predictive model for survival. I’ve read many articles that applied the shrinkage correction to allow for small amount of overfitting when building a score system.

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I want to know how to calculate the ‘shrinkage factor’.

Thank you,
Lin

Reference

  1. Dowsett M, Sestak I, Regan MM, Dodson A, Viale G, Thurlimann B, et al. Integration of Clinical Variables for the Prediction of Late Distant Recurrence in Patients With Estrogen Receptor-Positive Breast Cancer Treated With 5 Years of Endocrine Therapy: CTS5. J Clin Oncol. 2018;36:1941-8.
  2. Cuzick J, Dowsett M, Pineda S, Wale C, Salter J, Quinn E, et al. Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the Genomic Health recurrence score in early breast cancer. J Clin Oncol. 2011;29:4273-8.
2

There is another paper indicating that ‘we used the likelihood ratio chi-square and degrees of freedom from a model with all 27 potential predictor variables to compute the shrinkage factors’.

3

The clinical score is unlikely to fit the age effect correctly, so I would not spend time on more minor issues at present.