EFFECTS OF MISMODELING AND MISMEASURING EXPLANATORY VARIABLES ON TESTS OF THEIR ASSOCIATION WITH A RESPONSE VARIABLE
EFFECTS OF MISMODELING AND MISMEASURING EXPLANATORY VARIABLES ON TESTS OF THEIR ASSOCIATION WITH A RESPONSE VARIABLE
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DOI：
10.1002/sim.4780070126
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发表时间：
1988-01-01
影响因子：
2
通讯作者：
LAGAKOS, SW
中科院分区：
文献类型：
--
作者：
LAGAKOS, SW
我们考虑了三种常用的统计检验，用于评估解释变量与测量的二进制或生存时间响应变量之间的关联，并调查了错误建模或错误测量解释变量的效率损失。关于错误建模，我们研究的后果，使用不正确的剂量metalloys在测试的趋势，错误建模的连续解释变量，和离散化的连续解释变量。我们还检查了离散解释变量的分类错误和连续解释变量的测量错误的后果。对于所有三种统计检验，对应于每种类型的误设定的渐近相对效率（ARE）等于解释变量的正确形式和拟合形式之间的相关性的平方。这个结果进行了数值评估的不同类型的误指定，以提供深入了解测试的选择，结果的解释，和设计的研究中的“正确的”解释变量不能被精确测量。
We consider three commonly‐used statistical tests for assessing the association between an explanatory variable and a measured, binary, or survival‐time, response variable, and investigate the loss in efficiency from mismodelling or mismeasuring the explanatory variable. With respect to mismodelling, we examine the consequences of using an incorrect dose metameter in a test for trend, of mismodelling a continuous explanatory variable, and of discretizing a continuous explanatory variable. We also examine the consequences of classification errors for a discrete explanatory variable and of measurement errors for a continuous explanatory variable. For all three statistical tests, the asymptotic relative efficiency (ARE) corresponding to each type of mis‐specification equals the square of the correlation between the correct and fitted form of the explanatory variable. This result is evaluated numerically for the different types of misspecification to provide insight into the selection of tests, the interpretation of results, and the design of studies where the ‘correct’ explanatory variable cannot be measured exactly.