diab: Diabetes Progression

In genridge: Generalized Ridge Trace Plots for Ridge Regression

Diabetes Progression

Description

These data consist of observations on 442 patients, with the response of interest being a quantitative measure of disease progression one year after baseline.

There are ten baseline variables: age, sex, body-mass index (bmi), average blood pressure (map) and six blood serum measurements.

Usage

data("diab")

Format

A data frame with 442 observations on the following 11 variables.

prog

disease progression, a numeric vector

age

age, a numeric vector

sex

integer, a numeric vector

bmi

body mass index, a numeric vector

map

mean arterial blood pressure, a numeric vector

tc

blood serum TC, a numeric vector

ldl

blood serum low-density lipoprotein ("bad cholersterol"), a numeric vector

hdl

blood serum high-density lipoprotein ("good cholersterol"), a numeric vector

tch

blood serum TCH, a numeric vector

ltg

blood serum lamotrigine, a numeric vector

glu

blood serum glucose, a numeric vector

Details

Efron & Hastie describe their analysis using the centered predictor variables standardized to unit L2 norm. ridge does not (yet) provide this scaling.

Source

The dataset was taken from the web site for Efron & Hastie (2021), Computer Age Statistical Inference, https://hastie.su.domains/CASI_files/DATA/diabetes.csv.

References

Efron, B., Hastie, T., Johnstone, I., & Tibshirani, R. (2004). Least Angle Regression. The Annals of Statistics, 32(2), 407-499. \Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.1214/009053604000000067")}

Efron, B., & Hastie, T. (2021). Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, and Data Science, Cambridge University Press. \Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.1017/9781108914062")}

Examples

data(diab)
## maybe str(diab) ; plot(diab) ...

genridge documentation built on April 3, 2025, 11:07 p.m.