Validating Performance Standards via Latent Class Analysis

Abstract

Validity of performance standards is a key element for the defensibility of standard setting results, and validating performance standards requires collecting multiple pieces of evidence at every step during the standard setting process. This study employs a statistical procedure, latent class analysis, to set performance standards and compares latent class analysis results with previously established performance standards via the modified-Angoff method for cross-validation. The context of the study is an operational large-scale science assessment administered in one of the southern states in the United States. Results show that the number of classes that emerged in the latent class analysis concurs with the number of existing performance levels. In addition, there is a substantial level of agreement between latent class analysis results and modified-Angoff method in terms of classifying students into the same performance levels. Overall, the findings establish evidence for the validity of the performance standards identified via the modified-Angoff method. Practical implications of the study findings are discussed.