dataCog: Made-up longitudinal data on global cognition before death
In nlive: Automated Estimation of Sigmoidal and Piecewise Linear Mixed Models
dataCog R Documentation
Made-up longitudinal data on global cognition before death
Description
The dataCog contains 1200 individuals with one line per visit. Repeated measures of global cognition (cognition) were collected over a maximum period of 30 years. Information on the age at death is also provided (ageDeath, ageDeath90).
Format
A data frame with 11867 observations over 1200 subjects and 5 variables:
- ID
subject identification number
- time
the retrospective (negative) time before death (in years)
- cognition
composite score of global cognition
- ageDeath
age at death (in years)
- ageDeath90
age at death centered by the mean
Examples
summary(dataCog)
nlive documentation built on April 12, 2025, 1:33 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| dataCog | R Documentation |
Made-up longitudinal data on global cognition before death
Description
The dataCog contains 1200 individuals with one line per visit. Repeated measures of global cognition (cognition) were collected over a maximum period of 30 years. Information on the age at death is also provided (ageDeath, ageDeath90).
Format
A data frame with 11867 observations over 1200 subjects and 5 variables:
- ID
subject identification number
- time
the retrospective (negative) time before death (in years)
- cognition
composite score of global cognition
- ageDeath
age at death (in years)
- ageDeath90
age at death centered by the mean
Examples
summary(dataCog)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.