Reliability refers to how measurements can produce consistent results and are crucial for any scientific research measurement. Intraclass Correlation Coefficient (ICC) is the most widely used method to determine the reproducibility of measurements of various statistical techniques. Calculated ICC and its confidence interval that reveal the underlying sampling distribution may help detect an experimental method's ability to identify systematic differences between research participants in a test. The purpose of this study was to introduce a new SAS macro, ICC6 for the calculation of different ICC forms and their confidence intervals. A SAS macro that employs the PROC GLM procedure in SAS was created to generate the estimates of two-way random effects (ANOVA). A simulated dataset was used as an input into the macro to calculate the point estimates for different types of ICCs. The upper and lower confidence interval limits for the ICC forms were calculated using the F statistics distribution. The SAS macro provided here produces a complete set of various forms of ICC along with their confidence intervals. A cross-validation using commercial software packages STATA and SPSS produced identical results. A development of SAS methodology using publicly available statistical approaches in estimating six distinct forms of ICC and their confidence intervals has been reported in this article. This work is an extension of available methodology supported by a few other statistical software packages to SAS.