Moore D F, Tsiatis A
Department of Statistics, Temple University, Philadelphia, Pennsylvania 19122.
Biometrics. 1991 Jun;47(2):383-401.
When faced with data in the form of overdispersed counts or proportions, moment methods allow consistent parameter estimation when only the form of the mean and variance is specified. If the variance form is misspecified, these methods still yield consistent parameter estimates, though with lower efficiency, and the variances of the estimates will be inconsistent. A variance correction is available that yields consistent variance estimates in these circumstances. The asymptotic and small-sample efficiencies of this correction are calculated, and its performance under variance misspecification is studied. A group-randomized breast self-examination prevention study that is now underway serves as a focal point for the study of these properties. The use of the variance correction in modelling is illustrated on a teratology data set.
当面对过度分散的计数或比例形式的数据时,矩方法在仅指定均值和方差形式的情况下允许进行一致的参数估计。如果方差形式指定错误,这些方法仍会产生一致的参数估计,尽管效率较低,并且估计值的方差将不一致。有一种方差校正方法可在这些情况下产生一致的方差估计。计算了这种校正的渐近效率和小样本效率,并研究了其在方差指定错误情况下的性能。一项正在进行的群组随机乳房自我检查预防研究成为了这些特性研究的焦点。在一个致畸学数据集上展示了方差校正在建模中的应用。