Abstract
In this paper, we investigate four existing and three new confidence interval estimators for the negative binomial proportion (i.e., proportion under inverse/negative binomial sampling). An extensive and systematic comparative study among these confidence interval estimators through Monte Carlo simulations is presented. The performance of these confidence intervals are evaluated in terms of their coverage probabilities and expected interval widths. Our simulation studies suggest that the confidence interval estimator based on saddlepoint approximation is more appealing for large coverage levels (e.g., nominal level1% ) whereas the score confidence interval estimator is more desirable for those commonly used coverage levels (e.g., nominal level1% ). We illustrate these confidence interval construction methods with a real data set from a maternal congenital heart disease study.
| Original language | English |
|---|---|
| Pages (from-to) | 241-249 |
| Number of pages | 9 |
| Journal | Journal of Statistical Computation and Simulation |
| Volume | 79 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Mar 2009 |
Scopus Subject Areas
- Statistics and Probability
- Modelling and Simulation
- Statistics, Probability and Uncertainty
- Applied Mathematics
User-Defined Keywords
- Average length
- Coverage probability
- Inverse sampling
- Likelihood ratio test
- Monte Carlo method
- Saddlepoint approximations
- Score test
- Wald test