Measurement quality has recently been highlighted as an important concern for advancing a cumulative psychological science. An implication is that researchers should move beyond mechanistically reporting coefficient alpha toward more carefully assessing the internal structure and reliability of multi-item scales. Yet a researcher may be discouraged upon discovering that a prominent alternative to alpha, namely, coefficient omega, can be calculated in a variety of ways. In this Tutorial, I alleviate this potential confusion by describing alternative forms of omega and providing guidelines for choosing an appropriate omega estimate pertaining to the measurement of a target construct represented with a confirmatory factor analysis model. Several applied examples demonstrate how to compute different forms of omega in R.