Poststratification without population level information on the poststratifying variable, with application to political polling
Poststratification without population level information on the poststratifying variable, with application to political polling
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DOI：
10.1198/016214501750332640
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发表时间：
2001-03-01
影响因子：
3.7
通讯作者：
Katz, J
中科院分区：
文献类型：
--
作者：
Reilly, C;Gelman, A;Katz, J
在重复抽样调查的背景下，我们使用相关变量的信息来研究如何构建更精确的总体均值集合估计。文中用实例说明了该方法。关于总统支持率的民调结果(我们的相关变量是政党认同)。我们使用后分层来构建这些改进的估计，但因为我们没有关于后分层变量的总体水平信息，所以我们构建了后分层随时间发展的方式的模型。通过这种方式，我们获得了更准确的估计，而不会对我们的利益变量--总统支持率--的动态做出可能站不住脚的假设。
We investigate the construction of more precise estimates of a collection of population means using information about a related variable in the context of repeated sample surveys. The method is illustrated using. poll results concerning presidential approval rating (our related variable is political party identification). We use poststratification to construct these improved estimates, but because we do not have population level information on the poststratifying variable, we construct a model for the manner in which the poststratifier develops over time. In this manner, we obtain more precise estimates without making possibly untenable assumptions about the dynamics of our variable of interest, the presidential approval rating.