Estimation of Parameters in Linear Structural Relationships: Sensitivity to the Choice of the Ratio of Error Variances
研究了在正态假设下，线性结构关系模型中最大似然估计对误差方差比已知值的敏感性，通过渐近公式分析样本量和假设值对估计方差和均方误差的影响。
Maximum likelihood estimation of parameters in linear structural relationships under normality assumptions requires knowledge of one or more of the model parameters if no replication is available. The most common assumption added to the model definition is that the ratio of the error variances of the response and predictor variates is known. This paper investigates the use of asymptotic formulae for variances and mean squared errors as a function of sample size and the assumed value for the error variance ratio.