There are 4 basic steps to creating a table in WebCASPAR. Begin on the Home page.

• Step 1: Select the data source(s) of your choice. You may choose one or more from the NCSES surveys in the left column or the NCES IPEDS surveys in the right column. Once you have selected your sources, click the "Select Data Source(s)" button.
• Step 2: Select the analysis variable(s) of your choice from the drop down box. You may select multiple analysis variables (see instructions). Click the "Select" button.
  • The selected variables are shown under "Table Summary". You may remove these or add new analysis variables to the list.
  • Once you are satisfied with the analysis variables, click the "Modify Classification Variables" button or use the tab at the top of the page.
• Step 3: Select the classification variables of your choice. Note that Year is a required classification variable and can't be removed. You may select multiple classification variables (see instructions). Click the "Select" button.
  • The selected variables are shown in the middle of the page following "Year". You may edit, remove, or add new classification variables to the list.
  • Once you are satisfied with the classification variables, click the "View Table" button or use the tab at the top of the page.
• Step 4: Your table is dynamically generated. Please wait while the table is generated. Complicated tables with a large number (six or more of each) of analysis and classification variables are too large to be generated and shown on the screen. Please contact WebCASPAR using the "E-mail WebCASPAR" link at the bottom of the screen with questions.

There are two main resources to help determine which data source is appropriate.

• Find a Variable link at the top of the page
  • Use Data Sources Available by Subject if searching by broad subject area. Areas covered include data on people, such as degrees, completions, enrollment, and salaries; financial data on R&D investments and tuition; and data on research facilities.
  • Use Data Sources Available by Classification Variable if searching for classification variables that are qualitative or categorical, such as Carnegie classification, citizenship, discipline, or state.
• "Info" links
  • On the Home page, "Info" links are provided after each data source. Click to get a more detailed description of the data source.

An analysis variable is a quantitative data element such as number of graduate students, salary, or R&D expenditures.

A classification variable is a qualitative or categorical data element such as academic institution, enrollment status, field of science and engineering, or gender.

In most cases, the two variables will give different results. Some data detail isn't available when using a standardized variable.

• Survey-specific variables correspond directly to a single survey and may only be used when creating a table from a single data source. Survey-specific variables should be used when you want the most detailed information from a single survey.
• Standardized variables must be used when creating tables across multiple data sources. For example, if you are interested in R&D expenditures and graduate students by academic institution, you will need to use the standardized Academic Institution variable since these two variables come from two different data sources.
• Standardized variables sometimes need to be used to obtain data across multiple years. For example, you will need to use a standardized Academic Discipline variable to view IPEDS Completions field data for time periods spanning 1986 and 1987 due to a change in survey design.

Tables are generated dynamically from underlying databases. Please be patient as it may take a bit of time to generate a table.

• Things to avoid that cause the system to time out:
  • Do not create large or complex tables (those with more than 6 analysis variables and more than 6 classification variables).
  • Do not create multiple tables at the same time.
  • Do not use the back button while the system is generating a table.
  • Do not click the "View Table" or the "Download Table" button again while the system is generating a table. This causes the table request to be submitted again and slows the system even more.
• Tips for avoiding time outs:
  • Reduce the number of analysis and classification variables in your table.
  • Create simple tables in a sequential manner (and merge them outside of WebCASPAR).
  • Use the "Download Table" feature instead of "View Table".
• Contact webcaspar@nsf.gov if you experience delays or time outs.

Classification variables are qualitative or categorical data elements. You may select all values or you may select specific values for your table.

• Step 1: Select the classification variable of choice. Click the "Select" button.
• Step 2: The variable will appear in the middle of the screen. Click the "Edit" button under the variable name.
• Step 3: Select the specific values of interest in the box on the left side. Click the "Add Value(s)" button. When done, click the "Continue" button.

Year is classification variable. Follow the instructions for selecting specific values for classification variables. Predefined sets of years or individual years may be selected.

Academic institution is a classification variable. Follow the instructions for selecting specific values for classification variables. Select the academic institution variable of choice. Use the "Edit" feature:

• Predefined sets of institutions, such as "Historically Black Institutions" or public or private institutions, along with individual institutions may be selected from the box on the left.
• Use the "Institutional Search" button below the left box to do an advanced search of institutions. Institutions can be searched by name, FICE Code, city, state, zip code, region, public/private, highest degree granted, Carnegie code, or Historically Black Institution.

Due to the changing nature of this group, WebCASPAR does not predefine these groups. You may find the Department of Education's list of accredited postsecondary minority institutions at: http://www2.ed.gov/about/offices/list/ocr/edlite-minorityinst-list-hisp-tab.html. Follow the instructions for selecting specific values for classification variables to create your own custom group.

You must be a registered user to save a table or a specific grouping of your own creation.

• Register: Click the "Register" link located near the top right. Provide the requested information. Click the "Save" button. You are now a registered user.
• Login: Log in using your User ID and Password by using the boxes at the top right or using the "My WebCASPAR" link.
• Save a table: Create your table. Click the "Save Table" button at the bottom of the table. Name the table and click "Save". To retrieve your saved tables, click the "Home" link. Your saved tables are displayed near the bottom of the page under "Your Saved Tables". Click the "View" button to recreate the table.
• Save a custom grouping: Select the classification variable of interest. Click the "Edit" button. Chose the specific values of interest for your custom grouping. Click "Add Value(s)" under the box on the left. To save the grouping, click the "Save Selection Group" button under the box on the right. Name the group and click the "Save" button. Your saved groups are displayed in the box on the left when you edit a classification variable.
• Manage saved items: Click the My WebCASPAR link at the top of the page. Log in if prompted. Use the links to view, modify, or delete saved items.

We have two formats for citing data from WebCASPAR.

• Short form. The short form is used for figures or text tables. In this case the citation is: "SOURCE: National Science Foundation, National Center for Science and Engineering Statistics, Integrated Science and Engineering Resources Data System (WebCASPAR), https://webcaspar.nsf.gov".
• Long form. The long form is used when the data source is not provided in full anywhere else. For example, if the original data source is the 2008 NSF Survey of Research and Development Expenditures at Universities and Colleges, the suggested citation is: "SOURCE: National Science Foundation, National Center for Science and Engineering Statistics, Survey of Research and Development at Universities and Colleges, 2008, Integrated Science and Engineering Resources Data System (WebCASPAR) (https://webcaspar.nsf.gov) [accession date]. "

As of 2007, data on race, ethnicity, gender, and citizenship status of doctorate recipients collected on the Survey of Earned Doctorates (SED) are no longer available in WebCASPAR.

• Why? In 2007, NCSES embarked on a broader program to strengthen the confidentiality protections applied to the SED and implemented a different disclosure protection strategy aimed at providing a better balance between confidentiality protection and data utility. WebCASPAR is not able to implement the new, more sophisticated confidentiality protection procedures so these variables are no longer available in WebCASPAR.
• Are the data available somewhere else? Yes. Data from the SED, including data on race, ethnicity, gender, and citizenship status are available in the NSF SED Tabulation Engine. Note that data on baccalaureate institutions are not available on the NSF SED Tabulation Engine. Those data remain available in WebCASPAR.
• Where can I learn more about NCSES's disclosure protection strategy? A more detailed description of the issues and strategy can be found online at http://www.nsf.gov/statistics/srvydoctorates/sedreporting/.