ROBUSTNESS OF STANDARD CONFIDENCE-INTERVALS FOR LOCATION PARAMETERS UNDER DEPARTURE FROM NORMALITY
成果类型:
Article
署名作者:
BASU, S; DASGUPTA, A
署名单位:
Purdue University System; Purdue University
刊物名称:
ANNALS OF STATISTICS
ISSN/ISSBN:
0090-5364
DOI:
10.1214/aos/1176324716
发表日期:
1995
页码:
1433-1442
关键词:
t-test
摘要:
Let X(i) = theta + sigma Z(i) where Z(i) are i.i.d. from a distribution F, and -infinity < theta < infinity and sigma > 0 are unknown parameters. If F is N(0, 1), a standard confidence interval for the unknown mean theta is the t-interval (X) over bar +/- t(alpha/2)s/root n. The question of conservatism of this interval under nonnormality is considered by evaluating the infimum of its coverage probability when F belongs to a suitably chosen class of distributions F. Some rather surprising phenomena show up. For F = {all symmetric unimodal distributions} it is found that, for high nominal coverage intervals, the minimum coverage is attained at U[-1, 1] distribution, and the t-interval is quite conservative. However, for intervals with low or moderate nominal coverages (t(alpha/2) < 1), it is proved that the infimum coverage is zero, thus indicating drastic sensitivity to nonnormality. This phenomenon carries over to more general families of distributions. Our results also relate to robustness of the P-value corresponding to the t-statistic when the underlying distribution is nonnormal.
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