Getting Started with PDAS

Public-use Data Analysis System (PDAS) is a user-friendly online analysis tool for users to analyze public-use data files (PUFs). This tool allows users to review study variables, run crosstab analyses, perform logistic regressions, and download the results of any analysis to CSV format. PDAS is populated with the PUFs and may not contain all variables of interest. No files need to be downloaded.

PDAS and the PUFs do not include any geographic identifiers; they include only collapsed age categories and do not include continuous age variables (including age at first use of substances). Several other variables, like income, are recoded to courser levels as well. Other demographic variables (i.e., immigrant status) have also been removed to protect the confidentiality of respondents.

Accessing PDAS

To access PDAS, perform the following:

From the SAMHDA website, select one of the following options:
1. Hover over the Analyze tab on the toolbar and select Public Data.
2. Click the Analyze Data button on the Home page to open the Analyze Data page. Click the PDAS link.
Review the list of available surveys and click the appropriate survey to select it. You can also use the Search bar at the top of the Surveys list to search for the appropriate survey.
If necessary, click the star next to the survey name to Add to Favorites.
The Crosstab tab displays by default. Use this tab to Run a Crosstab using the variables from the selected survey. A Crosstab, or cross-tabulation, is a table that depicts the number of times each of the possible variable combinations occurred in the sample data. The results display a table and graph.
Click the Access Recent Analyses tab to select a recently-run analysis with the variables pre-populated.
Click the Logistic Regression tab to Run a Logistic Regression using the variables from the selected survey. Logistic regression measures the relationship between the dependent variable and one or more independent variables by estimating probabilities using a logistic function, which is the cumulative logistic distribution.