bolus {cold} | R Documentation |

## Bolus data

### Description

The dataset has the number of requests per interval in 12 successive four-hourly intervals following abdominal surgery for 65 patients in a clinical trial to compare two groups (bolus/lock-out combinations).

### Usage

`data("bolus")`

### Format

A data frame with 780 observations on the following 4 variables.

`id`

identifies de number of the individual profile. This vector contains observations of 65 individual profiles.

`group`

a factor with levels

`1mg`

and`2mg`

.`time`

a numeric vector that identifies the number of the time points observed.

`y`

a numeric vector with the number of analgesic doses taken by hospital patients in 12 successive four-hourly intervals.

### Details

The group `2mg`

has 30 patients and the group `1mg`

has 35 patients.

### Source

Weiss, Robert E. (2005). Modeling Longitudinal Data. Springer

https://robweiss.faculty.biostat.ucla.edu/book-data-sets

### References

Henderson, R. and Shimakura, S. (2003).
A Serially Correlated Gamma Frailty Model for Longitudinal Count Data.
*Biometrika*, vol. 90, No. 2, 355–366

### Examples

```
data(bolus)
## change the reference class
contrasts(bolus$group)
bolus$group<-relevel(factor(bolus$group), ref = "2mg")
contrasts(bolus$group)
## Weiss, Robert E. (2005) pp 353-356, compare with Table 11.2
bol0R <- cold(y ~ time + group, random = ~ 1, data = bolus,
dependence = "indR")
summary (bol0R)
## reparametrization of time
bolus$time1 <- bolus$time - 6
bol0R1 <- cold(y ~ time1 + group, random = ~ 1,data = bolus,
dependence = "indR")
summary (bol0R1)
bol1R1 <- cold(y ~ time1 + group, random = ~ 1, data = bolus,
time = "time1", dependence = "AR1R")
summary (bol1R1)
anova(bol0R1, bol1R1)
plot(bol1R1, which = 1, factor = group, ylab = "Bolus count")
```

*cold*version 2.0-3 Index]