The need to quantify agreement between two raters or two methods of measuring a response often arises in research. Kappa statistics (unweighted and weighted) are appropriate when the data are nominal or ordinal, whereas the concordance correlation coefficient is more appropriate when the data are measured on a continuous scale. We develop weighted product-moment and concordance correlation coefficients which are applicable for repeated measurements study designs. We consider two distinct situations in which the repeated measurements are paired or unpaired over time. We illustrate the methodology with examples comparing (1) two assays for measuring serum cholesterol, (2) two estimates of dietary intake, from a food frequency questionnaire and dietary recalls, and (3) two measurements of percentage body fat, from skinfold calipers and dual energy x-ray absorptiometry.