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This dataset contains simulated patient-level data for Alzheimer’s disease biomarker analysis. It includes demographic variables, clinical covariates, biomarker values, and disease status. The dataset is suitable for testing finite mixture models, cutoff derivation, and performance evaluation.

Usage

data(alzheimer_data)

Format

A data frame with 500 rows and 7 variables:

PTAU

numeric: Plasma p-tau biomarker concentration (pg/mL).

AGE

numeric: Age in years (approx. 57-96).

SEX

integer: Sex (0 = Female, 1 = Male).

BMI

numeric: Body Mass Index (kg/m\(^2\)).

HTN

integer: Hypertension status (0 = no, 1 = yes).

DM

integer: Diabetes status (0 = no, 1 = yes).

DISEASE

integer: Alzheimer’s disease status (0 = no disease, 1 = disease).

Details

The dataset mimics typical biomarker distributions observed in Alzheimer’s cohorts. Covariates (AGE, SEX, BMI, HTN, DM) act as confounders in biomarker-disease associations. Useful for demonstrating the two-cutoff approach in biomarker classification.