10: Applications of Psychometric Models: Analyzing smell as an early predictor of Parkinson's disease

Music City Center 

As populations age, finding new reliable ways to identify Parkinson's disease is increasingly vital. In addition, identifying biomarkers for early progression of Parkinson's disease will help accelerate the clinical evaluation of the efficacy of new interventions. We investigate the University of Pennsylvania Smell Identification Test (UPSIT) as a diagnostic tool for early stages of Parkinson's disease. To do this, we utilize psychometric models, specifically the Rasch and 3 parameter logistic models, to investigate both if this test can identify Parkinson's disease in early stages of development, and also to gain insights into the psychometric properties of the specific questions on the UPSIT, such as which questions perform well and which questions perform poorly.

Parkinson's Disease

Rasch Model

3PL Model 

Section on Statistics in Epidemiology