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Simulation Study of Conditional, Bootstrap, and t Confidence Intervals in Linear Regression.
- Source :
-
Communications in Statistics: Simulation & Computation . Aug2003, Vol. 32 Issue 3, p697-715. 19p. - Publication Year :
- 2003
-
Abstract
- Two resampling procedures, the bootstrap (BS) and the conditional confidence interval (CCI), are compared with the standard t-interval for the slope parameter in simple linear regression with an error term that is not necessarily normal. The type of bootstrap confidence intervals computed are the widely used bias-corrected and accelerated (BC[SUBa]) intervals. The CCIs are found by an efficient method for inverting permutation tests. Normal, highly skewed, and heavy-tailed error distributions are considered. While the CCI and BC[SUBa] intervals have similar asymptotic properties, for a moderate number of cases, the confidence intervals obtained from the CCI and BC[SUBa] behave di8erently in terms of accuracy, power, length, and correctness. Across all conditions, the CCI is the most accurate interval and has very good power. The t-intervals are also very accurate across most of the conditions we studied, and have coverage closer to the nominal value than the BC[SUBa] intervals. [ABSTRACT FROM AUTHOR]
- Subjects :
- *STATISTICAL bootstrapping
*CONFIDENCE intervals
*REGRESSION analysis
*PERMUTATIONS
Subjects
Details
- Language :
- English
- ISSN :
- 03610918
- Volume :
- 32
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- Communications in Statistics: Simulation & Computation
- Publication Type :
- Academic Journal
- Accession number :
- 10405981
- Full Text :
- https://doi.org/10.1081/SAC-120017857