@article{ETD,
      recid = {721},
      author = {Perkins, Jedediah},
      title = {Censored data models for longitudinal neuropsychological  score analysis},
      publisher = {Oregon Health and Science University},
      school = {M.S.},
      address = {2011},
      number = {ETD},
      abstract = {Neuropsychological tests are essential for assessing  cognitive function, but floor and ceiling effects, summary  score limitations, and longitudinal censoring reduce  accuracy. This thesis applies censored normal (Type 1  Tobit) models to longitudinal data from the Boston Naming  Test (ceiling effects) and Word List Delayed Recall (floor  effects). Simulations show that ignoring these effects  misestimates change points and population trends. Tobit  models improved classification of Mild Cognitive Impairment  and score prediction compared to standard models, with  higher ROC values and lower mean squared error. Accounting  for ceiling and floor effects enhances cognitive decline  detection and supports earlier intervention strategies.},
      url = {http://digitalcollections.ohsu.edu/record/721},
      doi = {https://doi.org/10.6083/M4FJ2DSD},
}