Properties of the Spearman correction for attenuation were investigated using Monte Carlo methods, under conditions where correlations between error scores exist as a population parameter and also where correlated errors arise by chance in random sampling. Equations allowing for all possible dependence among true and error scores on two tests at both the sample and population levels were derived and compared to simulation results. The additional influence of biased estimates of reliability at both levels was examined. Research settings under which the correction for attenuation can be useful in data analysis and those under which it is inaccurate and extremely variable were distinguished. (Contains 3 figures and 6 tables.)