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NAEP Assessment Weighting Procedures → Weighting Procedures and Variance Estimation for the 2004 Assessment

NAEP Technical DocumentationWeighting Procedures and Variance Estimation for the 2004 Assessment

          

Computation of Full-Sample Weights

Computation of Replicate Weights

Quality Control on 2004 Weighting Procedures

In 2004, long-term trend weights were developed for students sampled by age category (9, 13, and 17) for operational assessments in mathematics and reading, and for bridge assessments in mathematics and reading. Each student was assigned a weight to be used for making inferences about students in the target population. This weight is known as the final full-sample student weight. The final full-sample weight contains five components:

  • the base weight,
  • school nonresponse adjustments,
  • student nonresponse adjustments,
  • school weight-trimming adjustments,
  • student weight-trimming adjustments.

The base weight is the inverse of the overall probability of selecting and assigning a student to a specified assessment. The weight is adjusted for two sources of nonparticipation: school level and student level. These weighting adjustments seek to reduce the potential for bias from such nonparticipation by increasing the weights of students from schools similar to those schools not participating, and by increasing the weights of participating students similar to those students within participating schools who did not participate as scheduled. Furthermore, the weights reflect the trimming of extremely large weights at both the school and student level, if needed.

In addition to the final full-sample weight, a set of replicate weights was provided for each student. These replicate weights are used in calculating the sampling errors of estimates obtained from the data, using the jackknife repeated replication method. The methods of deriving these weights were aimed at reflecting the features of the sample design, so that when the jackknife variance estimation procedure is implemented, approximately unbiased estimates of sampling variance are obtained.


Last updated 26 June 2009 (GF)

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