This note concerns the construction of bootstrap simultaneous confidence intervals (SCI) for m parameters. Given B bootstrap samples, we suggest an algorithm with complexity of O (mB log (B)). We apply our algorithm to construct a confidence region for time dependent probabilities of progression in multiple sclerosis and for coefficients in a logistic regression analysis. Alternative normal based simultaneous confidence intervals are presented and compared to the bootstrap intervals.
Bibliographical noteFunding Information:
This research was supported in part by NIH CA075971, the Harvard Center for Neurodegeneration and Repair (HCNR), and the Partners MS Center. We thank Howard Weiner for the permission to use the MS data.
- Confidence region
- Discrete survival curve
- Multiple sclerosis
- Normal bound