Depicting Changes in Multiple Symptoms Over Time

Abstract

Ridit analysis, an acronym for Relative to an Identified Distribution, is a method for assessing change in ordinal data and can be used to show how individual symptoms change or remain the same over time. The purposes of this article are to (a) describe how to use ridit analysis to assess change in a symptom measure using data from a longitudinal study, (b) give a step-by-step example of ridit analysis, (c) show the clinical relevance of applying ridit analysis, and (d) display results in an innovative graphic. Mean ridit effect sizes were calculated for the frequency and distress of 64 symptoms in lung transplant patients before and after transplant. Results were displayed in a bubble graph. Ridit analysis allowed us to maintain the specificity of individual symptoms and to show how each symptom changed or remained the same over time. The bubble graph provides an efficient way for clinicians to identify changes in symptom frequency and distress over time.