### Item Response Theory in Change from Baseline for Ordinal Data

In quality of life data, it is common to have the outcome measures as ordinal e.g., points on a Likert Scale. These outcome measures are based on attributes that cannot be assessed directly, such as pain or satisfaction level. One of the major difficulties that we come across while analyzing the ordinal outcome measures is that these data preclude any arithmetic operations, such as addition or subtraction etc. When it comes to measurement of change in ordinal outcome measures for longitudinal data, one either uses standard classical methods such as the paired t-test, repeated measures or the effect size statistics to test the statistical significance of the change. However, these approaches have some critical issues. Let’s discuss about scores as outcome measures which are ordinal in nature. Being ordinal, the…