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No-Show Analysis. Final Report.
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Kalsbeek, William D.; And Others – 1975
The National Assessment of Educational Progress; Second Science Assessment No-Show Study assessed the magnitude and causation of nonresponse biases. A No-Show is defined as an individual who was selected as a sample respondent but failed to be present for regular assessment of the 17-year-old group. The procedure whereby a sample of eligible…
Descriptors: Educational Assessment, High Schools, Mathematical Models, Performance Factors
Population Inferences and Variance Estimation for NAEP Data.
Peer reviewed Peer reviewed
Johnson, Eugene G.; Rust, Keith F. – Journal of Educational Statistics, 1992
The use of sampling weights in deriving population estimates for the National Assessment of Educational Progress (NAEP) and the effects of nonresponse and undercoverage on those estimates are described. The estimation of sampling variability from complex sample surveys is also reviewed, concentrating on the jackknife repeated replication…
Descriptors: Educational Assessment, Elementary Secondary Education, Estimation (Mathematics), Mathematical Models
Considerations and Techniques for the Analysis of NAEP Data.
Peer reviewed Peer reviewed
Johnson, Eugene G. – Journal of Educational Statistics, 1989
The effects of certain characteristics (e.g., sample design) of National Assessment of Educational Progress (NAEP) data on statistical analysis techniques are considered. Ignoring special features of NAEP data and proceeding with a standard analysis can produce inferences that underestimate the true variability and overestimate the true degrees of…
Descriptors: Data Collection, Educational Assessment, Elementary Secondary Education, Estimation (Mathematics)
Estimating Population Characteristics from Sparse Matrix Samples of Item Responses.
Peer reviewed Peer reviewed
Mislevy, Robert J.; And Others – Journal of Educational Measurement, 1992
Concepts behind plausible values in estimating population characteristics from sparse matrix samples of item responses are discussed. The use of marginal analyses is described in the context of the National Assessment of Educational Progress, and the approach is illustrated with Scholastic Aptitude Test data for 9,075 high school seniors. (SLD)
Descriptors: College Entrance Examinations, Educational Assessment, Equations (Mathematics), Estimation (Mathematics)
Sampling and Weighting in the National Assessment.
Peer reviewed Peer reviewed
Rust, Keith F.; Johnson, Eugene G. – Journal of Educational Statistics, 1992
Procedures for obtaining student samples for the National Assessment of Educational Progress (NAEP) and deriving survey weights for analysis of survey data are described. Sample designs are economically and operationally feasible, and weighting procedures result in increased precision of estimates as they account for the probabilities of student…
Descriptors: Data Analysis, Educational Assessment, Elementary Secondary Education, Estimation (Mathematics)