Abstract
The relative accuracies of various estimators of partial regression coefficients are investigated for the case of two Independent variables x1 and x2 with, randomly missing values on x2 only. The estimators are studied.in the context of the usual linear model yi = β0 + β1x1 i, + β2x2 i + ci. where the ci are i.i.d.with mean 0 and variance α2. The mean square errors of two estimators% the piecewise estimator and the linear prediction estimator, are derived for both β1. and β2 and compared with the nuaan square error of ihe complete-case estimator* To further compare the estimators,, a Monte Carlo study of oliser¥atio»iis generated from a trivariate normal distribution is performed. The study supports a general preference for the method of maximum likelihood in estimating both β1 and β2 under this model
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