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首页> 外文期刊>Australian & New Zealand journal of statistics >An alternative to confidence intervals constructed after a Hausman pretest in panel data
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An alternative to confidence intervals constructed after a Hausman pretest in panel data

机译：在Hausman预先在面板数据中预测后构建的置信区间的替代方案

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摘要

Consider panel data modelled by a linear random intercept model that includes a time-varying covariate. Suppose that our aim is to construct a confidence interval for the slope parameter. Commonly, a Hausman pretest is used to decide whether this confidence interval is constructed using the random effects model or the fixed effects model. This post-model-selection confidence interval has the attractive features that it (a) is relatively short when the random effects model is correct and (b) reduces to the confidence interval based on the fixed effects model when the data and the random effects model are highly discordant. However, this confidence interval has the drawbacks that (i) its endpoints are discontinuous functions of the data and (ii) its minimum coverage can be far below its nominal coverage probability. We construct a new confidence interval that possesses these attractive features, but does not suffer from these drawbacks. This new confidence interval provides an intermediate between the post-model-selection confidence interval and the confidence interval obtained by always using the fixed effects model. The endpoints of the new confidence interval are smooth functions of the Hausman test statistic, whereas the endpoints of the post-model-selection confidence interval are discontinuous functions of this statistic.
机译：考虑由线性随机拦截模型建模的面板数据，该模型包括时变协变量。假设我们的目标是为斜率参数构造一个置信区间。通常，Hausman预测试用于确定是否使用随机效果模型或固定效果模型构建这种置信区间。这种模式选择型置信区间具有诱人的特征，当随机效果模型是正确的并且（b）在数据和随机效果模型时基于固定效果模型降低到置信区间非常不安。然而，这种置信区间具有（i）其端点是数据的不连续功能的缺点，并且（ii）其最小覆盖率远远低于其标称覆盖概率。我们构建具有这些有吸引力的特征的新置信区间，但不会遭受这些缺点。这种新的置信区间提供了模型后选择的置信区间之间的中间，并且始终使用固定效果模型获得的置信区间。新置信区间的终点是Hausman测试统计的顺利功能，而模型后选择置信区间的终点是这种统计的不连续功能。

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