# Estimation of a Shrinkage Factor for Logistic Regression

### Description

Estimate a shrinkage factor for shrinkage-after-estimation techniques, with application to logistic regression models.

### Usage

1 | ```
ml.shrink(b, dat)
``` |

### Arguments

`b` |
1 x |

`dat` |
a |

### Details

This function works together with `bootval`

, `splitval`

,
`kcrossval`

and `loocval`

to estimate a shrinkage factor. For further details,
see References. This function should not be used directly, and instead should
be called via one of the aforementioned shrinkage-after-estimation functions.

### Value

the function returns a single shrinkage factor

### Note

Currently, this function can only derive a single shrinkage factor for a given model, and is unable to estimate (weighted) predictor-specific shrinkage factors.

### References

Harrell, F. E. *"Regression modeling strategies: with applications
to linear models, logistic regression, and survival analysis."* *Springer*, (2001).

Steyerberg, E. W. *"Clinical Prediction Models", Springer* (2009)

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