metsynd {DATAstudio}

Metabolic Syndrome Data

Description

The metsynd data includes Gamma-Glutamyl Transferase (GGT) levels and curves of arterial oxygen saturation, for samples of women suffering from metabolic syndrome and women without metabolic syndrome; the data were gathered from a population-based survey conducted in Galicia (NW Spain), and it includes 35 women suffering from metabolic syndrome and 80 women without metabolic syndrome.

Usage

metsynd

Format

The data consist of a list with the following elements:

• y0: GGT levels for women without metabolic syndrome.

• y1: GGT levels for women suffering from metabolic syndrome.

• X0: Curves of arterial oxygen saturation (%) for women without metabolic syndrome (X0$data, X0$time).

• X1: Curves of arterial oxygen saturation (%) for women suffering from metabolic syndrome (X1$data, X1$time).

Details

The curves of arterial oxygen saturation are included in the matrices X0$data and X1$data, with each row representing a patient, and with columns representing ordered measurements over time. Here X0$time and X1$time represents the time (in hours) at which measurements were made, i.e., every 20 seconds during three hours of sleep. Further details on these data can be found in the references below.

References

Inácio de Carvalho, V., de Carvalho, M., Alonzo, T. A., González-Manteiga, W. (2016) Functional covariate-adjusted partial area under the specificity-ROC curve regression with an application to metabolic syndrome case study. Annals of Applied Statistics, 10, 1472-1495

Examples

data(metsynd)
library(scales)
attach(metsynd)

## Inacio de Carvalho et al (2016; Fig 1)
oldpar <- par(mfrow = c(1,2))
n0 <- length(y0)
n1 <- length(y1)
t <- X1$time
plot(t, X1$data[1, ], type = "l", lwd = 3, ylim = c(70, 100), 
     xlab = "Time (in hours)", ylab = "Arterial oxygen saturation (%)", 
     main = "Metabolic syndrome")
for (i in 2:n1)
  lines(t, X1$data[i, ], type = "l", lwd = 3, col = alpha("black", i / n1))
plot(t, X0$data[1, ], type = "l", lwd = 3, col = "gray", ylim = c(70, 100), 
     xlab = "Time (in hours)", ylab = "Arterial oxygen saturation (%)", 
     main = "No metabolic syndrome")
for (i in 1:n0)
  lines(t, X0$data[i, ], type = "l", lwd = 3, col = alpha("gray", i / n0))
par(oldpar)