Estimating Comparable Scores Using Surrogate Variables

Abstract

The possibility of using surrogate variables (e.g., school grades, other test scores, examinee background information) as replacements for common items predicting sample-selection bias between groups was investigated. The problem was specified as an incomplete data problem of comparability studies and was addressed using nonequivalent groups. A general model for estimating complete data (fitted) distributions through covariates is proposed (including common-item scores and surrogate variables as special cases). Model parameters are estimated using the EM algorithm. Standard errors of comparable scores are derived under the proposed model. Data from an empirical example examined the use of surrogate variables for establishing score comparability.

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