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Part-Time Undergraduates in Postsecondary Education: 200304 Postsecondary Education Descriptive Analysis Report

Data Analysis System

The estimates presented in this report were produced using the NPSAS:2004 and BPS:96/01 Data Analysis System (DAS). The DAS software makes it possible for users to specify and generate their own tables. The DAS also contains a detailed description of how each variable was created and includes question wording for items coming directly from an interview. With the DAS, users can replicate or expand upon the tables presented in this report. In addition to the table estimates, the DAS calculates the proper standard errors3 and weighted sample sizes for these estimates. For example, table B-1 contains standard errors that correspond to estimates in table 1 in the report

If the number of valid cases is too small to produce a reliable estimate (fewer than 30 cases), the DAS prints the message “low-N” instead of the estimate. All standard errors for estimates presented in this report can be viewed at http://nces.ed.gov/das. In addition to tables, the DAS can also produce a correlation matrix of selected variables to be used for linear regression models (or referred to “multivariate commonality analysis” in the report; see more description below). Included in the output with the correlation matrix are the design effects (DEFTs) for each variable in the matrix. Because statistical procedures generally compute regression coefficients based on simple random sample assumptions, the standard errors must be adjusted with the design effects to take into account the stratified sampling method used in the NPSAS and BPS surveys.

The DAS can be accessed electronically at http://nces.ed.gov/das. For more information about the Data Analysis System, contact:

Aurora D’Amico
Postsecondary Studies Division
National Center for Education Statistics
1990 K Street NW
Washington, DC 20006–5652
(202) 502-7334
Aurora.D'Amico@ed.gov


3Both NPSAS and BPS samples are not simple random samples, and therefore, simple random sample techniques for estimating sampling error cannot be applied to these data. The DAS takes into account the complexity of the sampling procedures and calculates standard errors appropriate for such samples. The method for computing sampling errors used by the DAS involves approximating the estimator by balanced repeated replication of the sampled population. The procedure is typically referred to as the “balanced repeated replication technique” (BRR).

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