Department of Psychology, Boston College, 300 McGuinn, 140 Commonwealth Avenue, Chestnut Hil, MA 02467, USA.
Behav Genet. 2012 Nov;42(6):886-98. doi: 10.1007/s10519-012-9560-z. Epub 2012 Sep 13.
It is well known that the regular likelihood ratio test of a bounded parameter is not valid if the boundary value is being tested. This is the case for testing the null value of a scalar variance component. Although an adjusted test of variance component has been suggested to account for the effect of its lower bound of zero, no adjustment of its interval estimate has ever been proposed. If left unadjusted, the confidence interval of the variance may still contain zero when the adjusted test rejects the null hypothesis of a zero variance, leading to conflicting conclusions. In this research, we propose two ways to adjust the confidence interval of a parameter subject to a lower bound, one based on the Wald test and the other on the likelihood ratio test. Both are compatible to the adjusted test and parametrization-invariant. A simulation study and two examples are given in the framework of ACDE models in twin studies.
众所周知，如果正在测试边界值，则有界参数的常规似然比检验将无效。这就是检验标量方差分量的零假设值的情况。尽管已经提出了调整方差分量检验的方法来考虑其零下限的影响，但从未提出过其区间估计的调整方法。如果不进行调整，当调整后的检验拒绝零方差的零假设时，方差的置信区间仍可能包含零值，从而导致结论相互矛盾。在这项研究中，我们提出了两种方法来调整受下限约束的参数的置信区间，一种基于 Wald 检验，另一种基于似然比检验。这两种方法都与调整后的检验和参数不变性兼容。在双胞胎研究的 ACDE 模型框架中进行了模拟研究和两个示例。
