This inquiry is an investigation of item response theory (IRT) proficiency estimators' accuracy under multistage testing (MST). We chose a two-stage MST design that includes four modules (one at Stage 1, three at Stage 2) and three difficulty paths (low, middle, high). We assembled various two-stage MST panels (i.e., forms) by manipulating two…

In this study, a ranking strategy was evaluated for comparing subgroups' change using identical, equated, and nonidentical measures. Four empirical data sets were evaluated, each of which contained examinees' scores on two occasions, where the two occasions' scores were obtained on a single identical measure, on two equated tests, and on two…

In this paper, the "standard error of equating difference" (SEED) is described in terms of originally proposed kernel equating functions (von Davier, Holland, & Thayer, 2004) and extended to incorporate traditional linear and equipercentile functions. These derivations expand on prior developments of SEEDs and standard errors of equating and…

Polynomial loglinear models for one-, two-, and higher-way contingency tables have important applications to measurement and assessment. They are essentially regarded as a smoothing technique, which is commonly referred to as loglinear smoothing. A SAS IML (SAS Institute, 2002a) macro was created to implement loglinear smoothing according to…

The purpose of this article was to extend the use of standard errors for equated score differences (SEEDs) to traditional equating functions. The SEEDs are described in terms of their original proposal for kernel equating functions and extended so that SEEDs for traditional linear and traditional equipercentile equating functions can be computed.…

In this study, the accuracies of four strategies were compared for estimating conditional differential item functioning (DIF), including raw data, logistic regression, log-linear models, and kernel smoothing. Real data simulations were used to evaluate the estimation strategies across six items, DIF and No DIF situations, and four sample size…

This study investigated differences between two approaches to chained equipercentile (CE) equating (one- and bi-direction CE equating) in nearly equal groups and relatively unequal groups. In one-direction CE equating, the new form is linked to the anchor in one sample of examinees and the anchor is linked to the reference form in the other…

In the equating literature, a recurring concern is that equating functions that utilize a single anchor to account for examinee groups' nonequivalence are biased when the groups are extremely different and/or when the anchor only weakly measures what the tests measure. Several proposals have been made to address this equating bias by incorporating…

In this study, eight statistical strategies were evaluated for selecting the parameterizations of loglinear models for smoothing the bivariate test score distributions used in nonequivalent groups with anchor test (NEAT) equating. Four of the strategies were based on significance tests of chi-square statistics (Likelihood Ratio, Pearson,…

In this study, differential item functioning (DIF) methods utilizing 14 different matching variables were applied to assess DIF in the constructed-response (CR) items from 6 forms of 3 mixed-format tests. Results suggested that the methods might produce distinct patterns of DIF results for different tests and testing programs, in that the DIF…

This simulation study evaluated the potential of alternative loglinear smoothing strategies for improving equipercentile equating function accuracy. These alternative strategies use cues from the sample data to make automatable and efficient improvements to model fit, either through the use of indicator functions for fitting large residuals or by…

In this study, we compared 12 statistical strategies proposed for selecting loglinear models for smoothing univariate test score distributions and for enhancing the stability of equipercentile equating functions. The major focus was on evaluating the effects of the selection strategies on equating function accuracy. Selection strategies' influence…

This study compared the accuracies of four differential item functioning (DIF) estimation methods, where each method makes use of only one of the following: raw data, logistic regression, loglinear models, or kernel smoothing. The major focus was on the estimation strategies' potential for estimating score-level, conditional DIF. A secondary focus…

The purpose of this paper is to extend von Davier, Holland, and Thayer's (2004b) framework of kernel equating so that it can incorporate raw data and traditional equipercentile equating methods. One result of this more general framework is that previous equating methodology research can be viewed more comprehensively. Another result is that the…

This study addressed 2 issues of using loglinear models for smoothing univariate test score distributions and for enhancing the stability of equipercentile equating functions. One issue was a comparative assessment of several statistical strategies that have been proposed for selecting 1 from several competing model parameterizations. Another…