diabdata {robmixglm}

Diabetes data

Description

Data from Heritier et al (2009), originally from Harrell (2001, p379). This data was from a study of the prevalence of cardiovascular risk factors such as obesity and diabetes for African Americans. (Willems et al, 19997) Data was available for 403 subjects screened for diabetes, reduced to 372 after removal of cases with missing data.

Usage

diabdata

Format

A data frame with 372 observations on the following 8 variables.

glyhb

Glycosated haemoglobin (values above 7.0 are usually taken as a positive diagnosis of diabetes)

age

age in years

gender

male or female

bmi

body mass index in kg/m^2

waisthip

ratio of waist to hip measurement

frame

body frame, small, medium or large

stab.glu

glucose

location

location, Buckingham or Louisa

Source

Heritier et al (2009)

References

Harrell, F.E. (2001). Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression and Survival Analysis. Springer.

Heritier, S., Cantoni, E., Copt, S. and Victoria-Feser, M-P (2009). Robust Methods in Biostatistics. Wiley.

Willems, J.P., Saunders, J.T., Hunt, D.E. and Schorling, J.B. (1997) Prevalence of coronary heart disease risk factors among rural blacks: A community-based study. Southern Medical Journal, 90:814-820.

Examples

diabdata.robustmix <- robmixglm(glyhb~age+gender+bmi+waisthip+frame+location, 
         data = diabdata, cores = 1)
summary(diabdata.robustmix)

diabdata.step <- step(diabdata.robustmix, glyhb~age+gender+bmi+waisthip+frame+location, cores = 1)
summary(diabdata.step)