Access the WLS Data

The Wisconsin Longitudinal Study is committed to the privacy of its study participants and WLS staff takes great care to maintain their confidentiality. To this aim, some variables are either not included or truncated in the publicly available data. Researchers can identify these protected variables by the note "Not Available on Public Release" in the online codebooks. If your research requires access to the protected data please contact the WLS at

Researchers are reminded that WLS data are considered Human Subject Data and any research involving Human Subject Data requires IRB approval. WLS researchers are also reminded that they should not publish any tables with cell sizes less than or equal to five.

To summarize the data we suggest you cite this article in your research.

Herd, Pamela, Deborah Carr, and Carol Roan. 2014. "Cohort Profile: Wisconsin Longitudinal Study (WLS)." International Journal of Epidemiology 43:34-41 PMCID: PMC3937969

Find data
Browse and search the data documentation to find the data you want.

14 August 2015
The Technical Difficulties have been resolved, the following links are working correctly.

Download complete datasets
Download pre-packaged WLS datasets in the format of your choice.

Download a subset
Download a subset of the WLS data containing only the data of interest to you.

Download utility programs
Download programs that are useful for working with the WLS data.

Download supplemental data files
Download college or 1975 employer characteristics or 1957-1993 female grad's job history.

NEW Download harmonized roster data
Harmonized marriage roster data is available now with children's roster coming soon.

Issues with the documentation? Let us know.
Please contact us if you notice any problems with the documentation.

All of the downloadable data files are compressed in ZIP format. The order of the variables in the data files is the same as the order of the variables in the codebooks/documentation. The "complete" datasets contain the data for all waves, combining the files from 1957-77, 1992 phone and mail, 1994 phone and mail, 2004-07 phone and mail, and 2011 in person and mail into one dataset. If a variable is not available due to non-interview, it will have the system missing value. For all SPSS portable files, variable and value labels are declared, and the refused/not ascertained category is normally defined as missing. SAS permanent datasets have variable labels, and most refused/not ascertained values are declared as missing values. The Stata datasets contain variable and value labels and a missing declaration for the refused category. The variable names are in lower case in Stata; Stata is case sensitive.