Overview
The package supports the use of the Canadian Longitudinal Study on Aging (CLSA) data. The CLSA is a population-level, longitudinal study and research platform that allows researchers to examine the biological, medical, psychological, and socioeconomic aspects of aging, disability, and disease.
The study tracks 51,338 participants who were between the ages of 45 and 85 at recruitment. They are divided into two cohorts: the Tracking cohort, which provides data through telephone interviews, and the comprehensive Cohort, which provides data through in-home interviews and Data Collection Site visits. Data collection occurs every three years. Currently, the survey data from baseline and two follow-ups are available. Studies often incorporate data from multiple time points and cohorts to examine temporal trends and increase sample size, respectively.
Public-sector researchers can apply for data access through the online application system.
Motivation
Scenario 1
When working with longitudinal survey data, variables representing the same concept may have different response options across time points. Categories may be added, removed, or relabelled from one time point to the next. For example, the distinct levels in CCC_HEART are “Yes” and “No” at Baseline and Follow-up 1 but “Yes”, “No”, and “Yes - confirmed in prior waves” at Follow-up 2. check_response_consistency() and find_matching_pairs() can be used to identify such inconsistencies before combining or comparing data across time points.
Scenario 2
In our experience, some variables that should have been derived by the data provider are missing from the supplied dataset. For this reason, we include a set of functions that derive these variables from component variables, following algorithms shared by the CLSA. Functions such as derive_adl_dcls() and derive_sls_dcls() are designed to save researchers from repeatedly writing long, complex definitions, improving reproducibility.
Installation
You can install the development version of clsatools from GitHub with:
# install.packages("pak")
pak::pak("Big-Life-Lab/clsatools")Vignette
You can also view the vignette by typing browseVignettes("clsatools") in your R session after installing the package.
Getting help or reporting an issue
To report bugs or request features, please file an issue on GitHub.
Code of conduct
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.