Ascertaining an Individual Patient’s Symptom Dominance Hierarchy: Analysis of Raw Longitudinal Data Induces Simpson’s Paradox

Paul R. Yarnold

Optimal Data Analysis, LLC

Examples of ordered “N-of-1″ single-case series include the monthly closing price of a corporate stock, a dieter’s weight each Friday morning upon waking, or real-time heart rate of an ICU patient recorded minute-by-minute. The present study examined a single-case series for a patient with fibromyalgia, consisting of 297 sequential daily ratings of nine symptoms commonly associated with the disease. Symptoms were compared statistically by UniODA to identify their dominance hierarchy (most to least severe) for this patient. Analysis of raw data suggested that fatigue was the dominant symptom, but analysis of ipsatively standardized data indicated that finding was paradoxically confounded: the primary symptom, in fact, was stiffness. Of 36 comparisons of symptom pairs performed using raw data, 28 (78%) were found to be confounded, ten of which (28%) identified the opposite effect (what raw data analysis suggested occurred was, in fact, the opposite of what occurred). These findings reveal a crucial difference between the meaning of the numbers and labels constituting the response scale as perceived and interpreted by the investigator, and the meaning of the numbers and labels as perceived and applied by the individual to quantify internal cognitive and emotional experiences. The latter issue is the purpose of the scale (if subject perception and response scale did not interact, then valid measurements would be impossible to obtain) and motivation underlying the research. Present findings show raw score analysis addresses the investigator’s perspective, and ipsative z-score analysis addresses the patient’s.

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