Exploring the Influence of Judge Proficiency on Standard‐Setting Judgments

Setting performance standards is a judgmental process involving human opinions and values as well as technical and empirical considerations. Although all cut score decisions are by nature somewhat arbitrary, they should not be capricious. Judges selected for standard‐setting panels should have the proper qualifications to make the judgments asked of them; however, even qualified judges vary in expertise and in some cases, such as highly specialized areas or when members of the public are involved, it may be difficult to ensure that each member of a standard‐setting panel has the requisite expertise to make qualified judgments. Given the subjective nature of these types of judgments, and that a large part of the validity argument for an exam lies in the robustness of its passing standard, an examination of the influence of judge proficiency on the judgments is warranted. This study explores the use of the many‐facet Rasch model as a method for adjusting modified Angoff standard‐setting ratings based on judges’ proficiency levels. The results suggest differences in the severity and quality of standard‐setting judgments across levels of judge proficiency, such that judges who answered easy items incorrectly tended to perceive them as easier, but those who answered correctly tended to provide ratings within normal stochastic limits.     

Increasing the Validity of Angoff Standards Through Analysis of Judge-Level Internal Consistency

The purpose of the present study was to extend past work with the Angoff method for setting standards by examining judgments at the judge level rather than the panel level. The focus was on investigating the relationship between observed Angoff standard setting judgments and empirical conditional probabilities. This relationship has been used as a measure of internal consistency by previous researchers. Results indicated that judges varied in the degree to which they were able to produce internally consistent ratings; some judges produced ratings that were highly correlated with empirical conditional probabilities and other judges’ ratings had essentially no correlation with the conditional probabilities. The results also showed that weighting procedures applied to individual judgments both increased panel-level internal consistency and produced convergence across panels.     

Non‐numeric Intrajudge Consistency Feedback in an Angoff Procedure

The credibility of standard‐setting cut scores depends in part on two sources of consistency evidence: intrajudge and interjudge consistency. Although intrajudge consistency feedback has often been provided to Angoff judges in practice, more evidence is needed to determine whether it achieves its intended effect. In this randomized experiment with 36 judges, non‐numeric item‐level intrajudge consistency feedback was provided to treatment‐group judges after the first and second rounds of Angoff ratings. Compared to the judges in the control condition, those receiving the feedback significantly improved their intrajudge consistency, with the effect being stronger after the first round than after the second round. To examine whether this feedback has deleterious effects on between‐judge consistency, I also examined interjudge consistency at the cut score level and the item level using generalizability theory. The results showed that without the feedback, cut score variability worsened; with the feedback, idiosyncratic item‐level variability improved. These results suggest that non‐numeric intrajudge consistency feedback achieves its intended effect and potentially improves interjudge consistency. The findings contribute to standard‐setting feedback research and provide empirical evidence for practitioners planning Angoff procedures.     

Examining the Precision of Cut Scores Within a Generalizability Theory Framework: A Closer Look at the Item Effect

An Angoff standard setting study generally yields judgments on a number of items by a number of judges (who may or may not be nested in panels). Variability associated with judges (and possibly panels) contributes error to the resulting cut score. The variability associated with items plays a more complicated role. To the extent that the mean item judgments directly reflect empirical item difficulties, the variability in Angoff judgments over items would not add error to the cut score, but to the extent that the mean item judgments do not correspond to the empirical item difficulties, variability in mean judgments over items would add error to the cut score. In this article, we present two generalizability-theory–based analyses of the proportion of the item variance that contributes to error in the cut score. For one approach, variance components are estimated on the probability (or proportion-correct) scale of the Angoff judgments, and for the other, the judgments are transferred to the theta scale of an item response theory model before estimating the variance components. The two analyses yield somewhat different results but both indicate that it is not appropriate to simply ignore the item variance component in estimating the error variance.     

Standard Setting: An Alternative Approach

Since 1971 there have been a number of studies in which a cut score has been set using a method proposed by Angoff (1971). In this method, each member of a panel of judges estimates for each test question the proportion correct for a specific target group of examinees. Prior and contemporary research suggests that this is a difficult task for judges. Angoff also proposed that judges simply indicate whether or not an examinee from the target group will be able to answer each question correctly (the yes/no method). We report on the results of two studies that compare a yes/no estimation with a proportion correct estimation. The two studies demonstrate that both methods produce essentially equal cut scores and that judges find the yes/no method more comfortable to use than the estimated proportion correct method.     

Consistency of Angoff-Based Predictions of Item Performance: Evidence of Technical Quality of Results From the Angoff Standard Setting Method

Judgmental standard-setting methods, such as the Angoff(1971) method, use item performance estimates as the basis for determining the minimum passing score (MPS). Therefore, the accuracy, of these item peformance estimates is crucial to the validity of the resulting MPS. Recent researchers (Shepard, 1995; Impara & Plake, 1998; National Research Council. 1999) have called into question the ability of judges to make accurate item performance estimates for target subgroups of candidates, such as minimally competent candidates. The propose of this study was to examine the intra- and inter-rater consistency of item performance estimates from an Angoff standard setting. Results provide evidence that item pelformance estimates were consistent within and across panels within and across years. Factors that might have influenced this high degree of reliability, in the item performance estimates in a standard setting study are discussed.     

Differential Use of Item Information by Judges Using Angoff and Nedeisky Procedures

Competency examinations in a variety of domains require setting a minimum standard of performance. This study examines the issue of whether judges using the two most popular methods for setting cut scores (Angoff and Nedelsky methods) use different sources of information when making their judgments. Thirty-one judges were assigned randomly to the two methods to set cut scores for a high school graduation test in reading comprehension. These ratings were then related to characteristics of the items as well as to empirically obtained p values. Results indicate that judges using the Angoff method use a wider variety of information and yield estimates closer to the actual p values. The characteristics of items used in the study were effective predictors of judges' ratings, but were far less effective in predicting p values     

The Impact of Process Instructions on Judges’ Use of Examinee Performance Data in Angoff Standard Setting Exercises

Despite being widely used and frequently studied, the Angoff standard setting procedure has received little attention with respect to an integral part of the process: how judges incorporate examinee performance data in the decision‐making process. Without performance data, subject matter experts have considerable difficulty accurately making the required judgments. Providing data introduces the very real possibility that judges will turn their content‐based judgments into norm‐referenced judgments. This article reports on three Angoff standard setting panels for which some items were randomly assigned to have incorrect performance data. Judges were informed that some of the items were accompanied by inaccurate data, but were not told which items they were. The purpose of the manipulation was to assess the extent to which changing the instructions given to the judges would impact the extent to which they relied on the performance data. The modified instructions resulted in the judges making less use of the performance data than judges participating in recent parallel studies. The relative extent of the change judges made did not appear to be substantially influenced by the accuracy of the data.     

Diagnostic Profiles: A Standard Setting Method for Use With a Cognitive Diagnostic Model

This article introduces the Diagnostic Profiles (DP) standard setting method for setting a performance standard on a test developed from a cognitive diagnostic model (CDM), the outcome of which is a profile of mastered and not‐mastered skills or attributes rather than a single test score. In the DP method, the key judgment task for panelists is a decision on whether or not individual cognitive skill profiles meet the performance standard. A randomized experiment was carried out in which secondary mathematics teachers were randomly assigned to either the DP method or the modified Angoff method. The standard setting methods were applied to a test of student readiness to enter high school algebra (Algebra I). While the DP profile judgments were perceived to be more difficult than the Angoff item judgments, there was a high degree of agreement among the panelists for most of the profiles. In order to compare the methods, cut scores were generated from the DP method. The results of the DP group were comparable to the Angoff group, with less cut score variability in the DP group. The DP method shows promise for testing situations in which diagnostic information is needed about examinees and where that information needs to be linked to a performance standard.     

Teachers' Ability to Estimate Item Difficulty: A Test of the Assumptions in the Angoff Standard Setting Method

The Angoff (1971) standard setting method requires expert panelists to (a) conceptualize candidates who possess the qualifications of interest (e.g., the minimally qualified) and (b) estimate actual item performance for these candidates. Past and current research (Bejar, 1983; Shepard, 1994) suggests that estimating item performance is difficult for panelists. If panelists cannot perform this task, the validity of the standard based on these estimates is in question. This study tested the ability of 26 classroom teachers to estimate item performance for two groups of their students on a locally developed district-wide science test. Teachers were more accurate in estimating the performance of the total group than of the "borderline group," but in neither case was their accuracy level high. Implications of this finding for the validity of item performance estimates by panelists using the Angoff standard setting method are discussed.     

A Method for Detecting Regression of Hard and Easy Item Angoff Ratings

One common phenomenon in Angoff standard setting is that panelists regress their ratings in toward the middle of the probability scale. This study describes two indices based on taking ratios of standard deviations that can be utilized with a scatterplot of item ratings versus expected probabilities of success to identify whether ratings are regressed in toward the middle of the probability scale. Results from a simulation study show that the standard deviation ratio indices can successfully detect ratings for hard and easy items that are regressed in toward the middle of the probability scale in Angoff standard‐setting data, where previously proposed indices often do not work as well to detect these effects. Results from a real data set show that, while virtually all raters improve from Round 1 to Round 2 as measured by previously developed indices, the standard deviation ratios in conjunction with a scatterplot of item ratings versus expected probabilities of success can identify individuals who may still be regressing their ratings in toward the middle of the probability scale even after receiving feedback. The authors suggest using the scatterplot along with the standard deviation ratio indices and other statistics for measuring the quality of Angoff standard‐setting data.     

Examining How Professional Roles and Test Development Experiences Impact Angoff Ratings

An important consideration in standard setting is recruiting a group of panelists with different experiences and backgrounds to serve on the standard-setting panel. This study uses data from 14 different Angoff standard settings from a variety of medical imaging credentialing programs to examine whether people with different professional roles and test development experiences tended to recommend higher or lower cut scores or were more or less accurate in their standard-setting judgments. Results suggested that there were not any statistically significant differences for different types of panelists in terms of the cut scores they recommended or the accuracy of their judgments. Discussion of what these results may mean for panelist selection and recruitment is provided.     

Innovations in Measuring Rater Accuracy in Standard Setting: Assessing “Fit” to Item Characteristic Curves

Standard setting methods such as the Angoff method rely on judgments of item characteristics; item response theory empirically estimates item characteristics and displays them in item characteristic curves (ICCs). This study evaluated several indexes of rater fit to ICCs as a method for judging rater accuracy in their estimates of expected item performance for target groups of test-takers. Simulated data were used to compare adequately fitting ratings to poorly fitting ratings at various target competence levels in a simulated two stage standard setting study. The indexes were then applied to a set of real ratings on 66 items evaluated at 4 competence thresholds to demonstrate their relative usefulness for gaining insight into rater “fit.” Based on analysis of both the simulated and real data, it is recommended that fit indexes based on the absolute deviations of ratings from the ICCs be used, and those based on the standard errors of ratings should be avoided. Suggestions are provided for using these indexes in future research and practice.     

Modeling Judgments in the Angoff and Contrasting-Groups Method of Standard Setting

Essential for the validity of the judgments in a standard-setting study is that they follow the implicit task assumptions. In the Angoff method, judgments are assumed to be inversely related to the difficulty of the items; contrasting-groups judgments are assumed to be positively related to the ability of the students. In the present study, judgments from both procedures were modeled with a random-effects probit regression model. The Angoff judgments showed a weaker link with the position of the items on the latent scale than the contrasting-groups judgments with the position of the students. Hence, in the specific context of the study, the contrasting-groups judgments were more aligned with the underlying assumptions of the method than the Angoff judgments .     

The Impact of Examinee Performance Information on Judges’ Cut Scores in Modified Angoff Standard‐Setting Exercises

This research evaluated the impact of a common modification to Angoff standard‐setting exercises: the provision of examinee performance data. Data from 18 independent standard‐setting panels across three different medical licensing examinations were examined to investigate whether and how the provision of performance information impacted judgments and the resulting cut scores. Results varied by panel but in general indicated that both the variability among the panelists and the resulting cut scores were affected by the data. After the review of performance data, panelist variability generally decreased. In addition, for all panels and examinations pre‐ and post‐data cut scores were significantly different. Investigation of the practical significance of the findings indicated that nontrivial fail rate changes were associated with the cut score changes for a majority of standard‐setting exercises. This study is the first to provide a large‐scale, systematic evaluation of the impact of a common standard setting practice, and the results can provide practitioners with insight into how the practice influences panelist variability and resulting cut scores.     

Multivariate Generalizability Analysis of the Impact of Training and Examinee Performance Information on Judgments Made in an Angoff-Style Standard-Setting Procedure

Cut scores, estimated using the Angoff procedure, are routinely used to make high-stakes classification decisions based on examinee scores. Precision is necessary in estimation of cut scores because of the importance of these decisions. Although much has been written about how these procedures should be implemented, there is relatively little literature providing empirical support for specific approaches to providing training and feedback to standard-setting judges. This article presents a multivariate generalizability analysis designed to examine the impact of training and feedback on various sources of error in estimation of cut scores for a standard-setting procedure in which multiple independent groups completed the judgments. The results indicate that after training, there was little improvement in the ability of judges to rank order items by difficulty but there was a substantial improvement in inter-judge consistency in centering ratings. The results also show a substantial group effect. Consistent with this result, the direction of change for the estimated cut score was shown to be group dependent.     

Evaluating the Consistency of Angoff-Based Cut Scores Using Subsets of Items Within a Generalizability Theory Framework

The Angoff method requires experts to view every item on the test and make a probability judgment. This can be time consuming when there are large numbers of items on the test. In this study, a G-theory framework was used to determine if a subset of items can be used to make generalizable cut-score recommendations. Angoff ratings (i.e., probability judgments) from previously conducted standard setting studies were used first in a re-sampling study, followed by D-studies. For the re-sampling study, proportionally stratified subsets of items were extracted under various sampling and test-length conditions. The mean cut score, variance components, expected standard error (SE) around the mean cut score, and root-mean-squared deviation (RMSD) across 1,000 replications were estimated at each study condition. The SE and the RMSD decreased as the number of items increased, but this reduction tapered off after approximately 45 items. Subsequently, D-studies were performed on the same datasets. The expected SE was computed at various test lengths. Results from both studies are consistent with previous research indicating that between 40–50 items are sufficient to make generalizable cut score recommendations.     

An Examination of the Replicability of Angoff Standard Setting Results Within a Generalizability Theory Framework

Evidence of stable standard setting results over panels or occasions is an important part of the validity argument for an established cut score. Unfortunately, due to the high cost of convening multiple panels of content experts, standards often are based on the recommendation from a single panel of judges. This approach implicitly assumes that the variability across panels will be modest, but little evidence is available to support this assertion. This article examines the stability of Angoff standard setting results across panels. Data were collected for six independent standard setting exercises, with three panels participating in each exercise. The results show that although in some cases the panel effect is negligible, for four of the six data sets the panel facet represented a large portion of the overall error variance. Ignoring the often hidden panel/occasion facet can result in artificially optimistic estimates of the cut score stability. Results based on a single panel should not be viewed as a reasonable estimate of the results that would be found over multiple panels. Instead, the variability seen in a single panel can best be viewed as a lower bound of the expected variability when the exercise is replicated.     

A Comparison of Three Variations on a Standard-Setting Method

The purpose of this study was to determine whether two variations on the typical Angoff group standard-setting process would produce sufficiently consistent results to recommend their use. Judgments obtained from a group of experts during a meeting were compared with judgments gathered from the same group before and after the meeting. The results indicate that differences between passing scores obtained with the three variations are relatively small, but those gathered before the meeting were less consistent than ratings gathered during and after the meeting. These results imply that judgments gathered after an initial traditional group-process session can provide an efficient alternative mechanism for setting cutting scores using the Angoff method.
This research was supported by The American Board of Internal Medicine, but does not necessarily reflect its opinions or policies.