Glucose | R Documentation |
The Glucose
data frame has 196 rows and 4 columns. The dataset is originally in package nlme as Glucose2.
This data frame contains the following columns:
a factor with levels
1
to 7
identifying the subject whose glucose
level is measured.
a factor with levels
1
2
indicating the occasion in which the experiment was conducted.
a numeric vector giving the time since alcohol ingestion (in min/10).
a numeric vector giving the blood glucose level (in mg/dl) adjusted for baseline.
Hand and Crowder (Table A.14, pp. 180-181, 1996) describe data on
the blood glucose levels measured at 14 time points over 5 hours for 7
volunteers who took alcohol at time 0. The same experiment was
repeated on a second date with the same subjects but with a dietary
additive used for all subjects.
Dataset was corrected for baseline using the following code:
## dataset Glucose2 of package nlme require(nlme) Glucose2 <- Glucose2[order(Glucose2$Subject, Glucose2$Date, Glucose2$Time),] ## adjust for pre-infusion levels measured at time points -1 and 0 data <- NULL for(i in unique(Glucose2$Subject)){ for(j in unique(Glucose2$Date)){ temp <- subset(Glucose2, Subject==i & Date==j) temp$Conc <- temp$glucose - mean(c(temp$glucose[1], temp$glucose[2])) temp$Conc <- ifelse(temp$Conc < 0 | temp$Time <= 0, 0, temp$Conc) ## handle intermediate values > 0 index1 <- which.max(temp$Conc) index2 <- which.min(temp$Conc[-c(1:index1)]) + index1 if(temp$Conc[index2]==0){temp$Conc[c(index2:nrow(temp))] <- 0} data <- rbind(data,temp) } } Glucose <- subset(data, Time >= 0, select=c('Subject', 'Date', 'Time', 'Conc')) names(Glucose) <- c("id","date","time","conc")
Pinheiro, J. C. and Bates, D. M. (2000), Mixed-Effects Models in S and S-PLUS, Springer, New York. (Appendix A.10)
Hand, D. and Crowder, M. (1996), Practical Longitudinal Data Analysis, Chapman and Hall, London.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.