Hello Readers, I am looking for guidance on calculating degrees of freedom for an external validation of a clinical prediction rule. The calculation for sample size is as follows:

We will include 4,875 patients. The recommended sample size for validation studies is a minimum of 100 events and a minimum of 100 non-events. During derivation, the study team derived an accurate model from a total sample size of 2,399 patients of whom 263 patients suffered adverse events. Thus, we have more than **adequate degrees of freedom** to validate the model and refine it if needed. Though the minimum is 100 patients with adverse events, a large sample size of 536 patients with adverse events will have adequate precision to estimate the sensitivity of the score using a two-sided 95% CI across all risk categories of interest. The margin of error will be +/- 3.1% for a sensitivity of 85% (CI 81.7% to 87.9%), or an exact binomial CI from 97.7% to 99.7% for a sensitivity of 99%.

I would appreciate it if someone could guide me on how to calculate the degrees of freedom for the above sample size. The derived tool has 7 parameters.