The Orlin Data System allows users to create extracts of the data and metadata available in the system. Users can easily select all or a subset of records. They can also select the variables for the extract by record type. If the user selects a subset of records (such as only females), the system will automatically extract only the records linked to that subset.
The Orlin Data System supports sophisticated metadata search and cross-reference features. All the metadata loaded into the system is available for full-text searching and is linked to other references where possible. Users with system permissions can associate documents with samples and record types to directly link new variables to their references in questionnaires and code books.
The Orlin Data System has both templates and a powerful scripting language to allow users to recode and transform variables.
Our analysis tools are based on the R programming language, but the user interface was designed so that knowledge of R is unnecessary. The system guides users through analytical functions, such as cross tabs and duration analyses, using prompts and dialog boxes. Researchers can access records directly, so it’s simple to select cases or create new variables to fit a variety of analytical needs. All of the statistical functions are also available through our advanced scripting language. Users can also adjust variables within ODS and then export to standard statistical programs such as SAS, Strata, SPSS, R, or Excel.
Analysis of longitudinal surveys and panel studies comes with particular challenges, such as the need to deal
with substantial manipulation and recoding of data, inconsistent responses across survey waves, and the
reproducibility of results because of issues with constant tracking of data extraction and preparation methods.
In the past, the complexity and scope of these issues has made it difficult for researchers to operate
efficiently with limited resources.
The Orlin Data System is designed to help make the most of complicated data sources. The system prompts users through the data preparation process to restructure the data for longitudinal analysis. For example, researchers often want to create transition variable that identify changes over time (someone gets married, loses a job, etc.). Creation of these kinds of variables is often difficult in a standard statistical package. The Orlin Data System provides simple templates to easily create the new variable in a single pass.