ArticleNeuropsychology2017
"The effectiveness and unique contribution of neuropsychological tests and the δ latent phenotype in the differential diagnosis of dementia in the uniform data set": Correction to John et al. (2016).
Article in Neuropsychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Reports an error in "The effectiveness and unique contribution of neuropsychological tests and the δ latent phenotype in the differential diagnosis of dementia in the uniform data set" by Samantha E. John, Ashita S. Gurnani, Cara Bussell, Jessica L. Saurman, Jason W. Griffin and Brandon E. Gavett (
methodArchival data requested from the NACC provided clinical diagnostic groups that were paired to 1 another through a genetic matching procedure. For each diagnostic pairing, 2 separate logistic regression models predicting clinical diagnosis were performed and compared on their predictive ability. The shared variance approach was represented through the latent phenotype δ, which served as the lone predictor in 1 set of models. The unique variance approach was represented through raw score values for the 12 neuropsychological test variables comprising δ, which served as the set of predictors in the second group of models.
resultsExamining the unique patterns of neuropsychological test performance across a battery of tests was the superior method of differentiating between competing diagnoses, and it accounted for 16-30% of the variance in diagnostic decision making.
conclusionImplications for clinical practice are discussed, including test selection and interpretation. (PsycINFO Database Record
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