When repeated-measures data are collected with small or even moderate sample sizes, correlation matrices show considerable variability. If one’s primary interest is in the correlations, some means of smoothing the coefficients may be desirable. Two methods of smoothing Pearson rs were investigated in the present study. The first method was to average repeated measures in blocks and then correlate block averages. In the second method, all repeated measures were correlated and then the correlation coefficients were averaged in blocks. The latter approach proved much superior, resulting in greatly reduced sampling variability and little distortion in the population correlation estimated.