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Podsakoff and Todor (1985) proposed partialling the first principal component from observed correlations as a procedure for controlling method variance. Using mathematical derivations and Monte Carlo simulation, we found that this procedure is biased. Partialling out the first principal component introduces a negative bias into the resulting correlations that seriously compromises subsequent analysis. Moreover, the extent of bias is not reduced by increasing sample size; however, it is inversely proportional to the number of variables. Therefore, partialling the first principal component is not recommended. Researchers are encouraged to collect data with multiple methods whenever feasible.
Kemery et al. (1986) studied this question.