Data and Analysis

The Population Research Institute's (PRI) Computational and Spatial Analysis (CSA) Core provides research support services at all stages of the funded research cycle to faculty associates, postdoctoral trainees, predoctoral trainees, research assistants, and students in the dual-degree program in demography. Researchers are able to select from a wide variety of services that suit their specific needs ranging from utilizing only a single service to having a core member on the project team for the entire duration of the project. Researchers can draw upon the extensive depth and breadth of the CSA Core's talents and experiences to:

  • design and implement data collection instruments;
  • acquire and disseminate data;
  • clean and construct complex data files using primary and secondary data;
  • provide statistical and spatial analyses; and
  • manage, document, and archive project files.

Contact the CSA Core at to discuss your needs and to learn how we can support your project.

GIS and Spatial Analysis

The CSA Core can help you to incorporate geographic information into your research in creative and cutting-edge ways. The CSA Core staff specializes in spatial statistics, advanced spatial analysis, exploratory spatial data analysis, spatial econometrics, and customized programming for geographic information systems (GIS). The CSA Core also provides an online interactive WebGIS and will support innovative research using mobile technology in the collection of spatial and social media data.

Learn more about how the CSA Core can help you with your GIS and Spatial Analysis.

Data Management

The CSA Core can help you with your data management needs from pre-proposal planning through dissemination and archiving. The CSA Core staff has extensive experience:

  • working with a variety of publicly-available datasets;
  • developing primary data collection systems;
  • working with highly-sensitive, restricted data; and
  • managing restricted data contracts and usage agreements.

Learn more about how the CSA Core can help you with the data for your project.

Programming and Statistical Support

The CSA Core provides programming support, statistical expertise, and software packages for population research. From developing project websites to implementing complex statistical analyses of your research data, the CSA Core offers experienced, professional programmers to support your project. We can provide support for short-term needs or long-term, multi-year research programs.

Learn more about how the CSA Core can help you with your programming and statistical support.

Federal Statistical Research Data Center

The Federal Statistical Research Data Center (RDC) at Penn State, which opened in Spring 2014, is a valuable asset for population researchers. Nevertheless, accessing and using RDC data can be challenging. Census RDC staff already help researchers with their applications and security clearance forms to gain access to the RDC. To provide further assistance, the CSA Core is modifying its operations to help PRI-affiliated researchers use RDC data.

The CSA Core staff has access to and experience with the public versions of many of the datasets available in the RDC. CSA Core staff can provide support for preliminary analyses for RDC proposals and can reduce startup costs by developing as much of the analysis as possible for later application in the RDC. Additionally, the CSA Core staff members either have obtained or are in the process of obtaining access ("Special Sworn Status") so they can assist with restricted data in the RDC.

Learn more about the Federal Statistical Research Data Center (RDC) at Penn State.

Emerging Areas

The CSA Core also promotes innovative population research using cutting-edge technologies and methodologies. This includes:

  • the integration and analysis of large spatial, historical, individual, and contextual datasets and the use of "Big Data";
  • social networks and complex systems analysis;
  • geo-tagged social media data collection and analysis;
  • population-engineering nexus modeling; and
  • privacy-preserving methods.