Abstract
SUMMARY A basic model of factor analysis is employed in the estimation of multiple correlation coefficients and partial regression weights. Estimators are derived for situations in which some or all of the independent variates are subject to errors in measurement. The effect of the errors is indicated and the problem of bias in the estimators is considered. In one special case it is shown how a best subset of the independent variates of any size can readily be found for data under analysis.
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