AlzheimerDisease: Alzheimer's Disease CSF Data

In AppliedPredictiveModeling: Functions and Data Sets for 'Applied Predictive Modeling'

Description

Washington University conducted a clinical study to determine if biological measurements made from cerebrospinal fluid (CSF) can be used to diagnose or predict Alzheimer's disease (Craig-Schapiro et al. 2011). These data are a modified version of the values used for the publication.

The R factor vector diagnosis contains the outcome data for 333 of the subjects. The demographic and laboratory results are collected in the data frame predictors.

One important indicator of Alzheimer's disease is the genetic background of a subject. In particular, what versions of the Apolipoprotein E gene inherited from one's parents has an association with the disease. There are three variants of the gene: E2, E3 and E4. Since a child inherits a version of the gene from each parent, there are six possible combinations (e.g. E2/E2, E2/E3, and so on). This data is contained in the predictor column named Genotype.

Usage

data(AlzheimerDisease)

Value

diagnosis	labels for the patients, either "Impaired" or "Control".
predictors	predictors for demographic data (eg. age, gender), genotype and assay results.

Source

Craig-Schapiro, R., Kuhn, M., Xiong, C., Pickering, E. H., Liu, J., Misko, T. P., Perrin, R. J., et al. (2011). Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis. PLoS ONE, 6(4), e18850.

Examples

data(AlzheimerDisease)

Example output

AppliedPredictiveModeling documentation built on May 2, 2019, 9:22 a.m.