Setting Cutoff Scores Research Articles

Variability of joint hypermobility in children: a meta-analytic approach to set cut-off scores

Current international consensus of the appropriate Beighton score cut-off to define if a child has generalised joint hypermobile or not is based upon expert opinion. Our aim was to determine the prevalence of Beighton scores of children worldwide to provide a recommendation for establishing the Beighton score cut-off to identify generalised joint hypermobility in children. We used AMED, OVID Medline, Embase and CINAHL to find published articles from inception to April 2024 describing Beighton scores of children up to and including 18 years from the general population. We extracted study demographics including country of publication, total number of participants, summary data about the age and sex of participant, Beighton scores and any cut-off used where authors deemed children hypermobile and how many children were rated at the corresponding Beighton scores. There were 37 articles reporting on the prevalence or incidence of hypermobility at cut-off scores from 28,868 participants. Using the cut-off of ≥ 6 resulted in a prevalence of 6% for studies reporting male data and 13% for studies reporting female data. Limited data reporting availability precluded further sub-analysis at a Beighton score of ≥ 7, age, pubertal status and ethnicity. Conclusion: The working threshold for identifying generalised joint hypermobility in children should be a Beighton score of 6 or more. Our analysis also suggests a Beighton score of 7 or greater may be appropriate in childhood, particularly for females.What is Known:• The working threshold for identifying generalised joint hypermobility in children previously was set based on expert opinion.What is New:• The threshold to identify hypermobility in children should be at a minimum of ≥ 6 on the Beighton score.

An Age–Period–Cohort Framework for Profit and Profit Volatility Modeling

The greatest source of failure in portfolio analytics is not individual models that perform poorly, but rather an inability to integrate models quantitatively across management functions. The separable components of age–period–cohort models provide a framework for integrated credit risk modeling across an organization. Using a panel data structure, credit risk scores can be integrated with an APC framework using either logistic regression or machine learning. Such APC scores for default, payoff, and other key rates fit naturally into forward-looking cash flow estimates. Given an economic scenario, every applicant at the time of origination can be assigned profit and profit volatility estimates so that underwriting can truly be account-level. This process optimizes the most fallible part of underwriting, which is setting cutoff scores and assigning loan pricing and terms. This article provides a summary of applications of APC models across portfolio management roles, with a description of how to create the models to be directly integrated. As a consequence, cash flow calculations are available for each account, and cutoff scores can be set directly from portfolio financial targets.

The Importance of Thinking Multivariately When Setting Subscale Cutoff Scores.

Setting cutoff scores is one of the most common practices when using scales to aid in classification purposes. This process is usually done univariately where each optimal cutoff value is decided sequentially, subscale by subscale. While it is widely known that this process necessarily reduces the probability of “passing” such a test, what is not properly recognized is that such a test loses power to meaningfully discriminate between target groups with each new subscale that is introduced. We quantify and describe this property via an analytical exposition highlighting the counterintuitive geometry implied by marginal threshold-setting in multiple dimensions. Recommendations are presented that encourage applied researchers to think jointly, rather than marginally, when setting cutoff scores to ensure an informative test.

Development of a Predictive Score for Discharge Disposition After Lumbar Fusion Using the Quality Outcomes Database.

Lumbar fusion remains the treatment of choice for many degenerative pathologies. Healthcare costs related to the procedure are a concern, and postdischarge needs often contribute to greater expenditure. The Quality Outcomes Database (QOD) is a prospective, multicenter clinical registry designed to analyze outcomes after neurosurgical procedures. To create a simple scoring system to predict discharge needs after lumbar fusion. Institutional QOD data from 2 high-volume neurosurgical centers were collected retrospectively. Univariate and multivariable logistic regression analyses were used to identify factors for our model. A receiver operating characteristic curve was used to set cutoff scores for patients likely to discharge home without ongoing services and those likely to require additional services/alternative placement after discharge. Two hundred seventeen patients were included. Five variables-osteoporosis, predominant preoperative symptom, need for assistive ambulation device, American Society of Anesthesiologist grade, and age-were included in our final scoring system. Patients with higher scores are less likely to need additional services. In patients with high scores (8-10), our scale correctly predicted discharge needs in 88.7% of cases. In patients with low scores (0-5), our scale predicted discharge needs (additional home services/alternative placement) in 75% of cases. For our final instrument, the area under the receiver operating characteristic curve was 0.809 (95% confidence interval 0.720-0.897). We present a simple scoring system to assist in predicting postdischarge needs for patients undergoing lumbar fusion for degenerative disease. Further validation studies are needed to assess the generalizability of our scale.

Application of the Angoff Method for Assessing Item Appropriateness and Setting Cut-off Scores during the Pre-Clinical Instrument Development Phase

Application of the Angoff Method for Assessing Item Appropriateness and Setting Cut-off Scores during the Pre-Clinical Instrument Development Phase

Civil Service Mandated Cutoff Scores: Challenges and Practice Recommendations

Los Angeles County's civil service rule specifies a 70% cutoff score regardless of the situation (type of job, type of assessment, or outcome of interest). This civil service rule would be difficult to defend if it were challenged in court, and the rule places the county at increased risk in the event of employment litigation, particularly with public safety jobs (police, fire, sheriff, etc.). Additionally, it is unlikely that this cutoff would optimally balance the county's interests in fair employment practices and expected job performance (SIOP, 2003). Given the propensity for public safety candidates and employees to file lawsuits related to hiring and promotions, and given the fact that public safety agencies in this county have been subjected to a number of employment-related lawsuits in the past, the current rule is problematic. Prior to this rule's development, as well as after its implementation in 1988, there has been substantial litigation related to cutoff scores, and courts have identified what they consider to be more and less appropriate methods for setting cutoff scores.

Analysis of Clustering Evaluation Considering Features of Item Response Data Using Data Mining Technique for Setting Cut-Off Scores

The setting of standards is a critical process in educational evaluation, but it is time-consuming and expensive because it is generally conducted by an education experts group. The purpose of this paper is to find a suitable cluster validity index that considers the futures of item response data for setting cut-off scores. In this study, nine representative cluster validity indexes were used to evaluate the clustering results. Cohen’s kappa coefficient is used to check the conformity between a set cut-off score using four clustering techniques and a cut-off score set by experts. We compared the cut-off scores by each cluster validity index and by a group of experts. The experimental results show that the entropy-based method considers the features of item response data, so it has a realistic possibility of applying a clustering evaluation method to the setting of standards in criterion referenced evaluation.

TNI-93: A New Memory Test for Dementia Detection in Illiterate and Low-Educated Patients.

To validate the TNI-93 test in illiterate and low-educated subjects bysetting cutoff scores to discriminate non-demented and demented subjects in a clinical setting (CESILL) and verifying the adequacy of these cutoff scores in a population-based study (AMI cohort). We used two study samples. First, a clinical setting (CESILL) comprising normal elderly participants and demented patients, mostly multicultural, low educated, or illiterate, was used to compute the cutoff scores of TNI-93 for the detection of dementia. Second, the AMI cohort, a population-based cohort of retired farmers living in a rural setting, was used as a replication study, to assess the detection properties of the cutoff scores in a different population composed mostly of low-educated older people. When combining the two scores, that is, free recall <6 or total recall <9, TNI-93 can detect dementia with a high sensitivity (87%) and specificity (96%), in the CESILL setting. These cutoff scores were roughly similar in the AMI cohort with high sensitivity (80% sensitivity) and specificity (81% specificity). In both study samples, the level of education had no effect on performance. The TNI-93 appears to be a good test to detect dementia. The absence of a significant effect of education level on the performances makes the TNI-93 a tool of choice in the screening of dementia in illiterate/low-educated subjects.

Science and Art of Setting Performance Standards and Cutoff Scores in Kinesiology

Setting standards and cutoff scores is essential to any measurement and evaluation practice. Two evaluation frameworks, norm-referenced (NR) and criterion-referenced (CR), have often been used for setting standards. Although setting fitness standards based on the NR evaluation is relatively easy as long as a nationally representative sample can be obtained and regularly updated, it has several limitations—namely, time dependency, population dependence, discouraging low-level performers, and favoring advantaged or punishing disadvantaged individuals. Fortunately, these limitations can be significantly eliminated by employing the CR evaluation, which was introduced to kinesiology by Safrit and colleagues in the 1980s and has been successfully applied to some practical problems (e.g., set health-related fitness standards for FITNESSGRAM®). Yet, the CR evaluation has its own challenges, e.g., selecting an appropriate measure for a criterion behavior, when the expected relationship between the criterion behavior and a predictive measure is not clear, and when standards are not consistent among multiple field measures. Some of these challenges can be addressed by employing the latest statistical methods (e.g., test equating). This article provides a comprehensive review of the science and art of setting standards and cutoff scores in kinesiology. After a brief historical overview of the standard-setting practice in kinesiology is presented, a case analysis of a successful CR evaluation, along with related challenges, is described. Lessons learned from past and current practice as well as how to develop a defendable standard are described. Finally, future research needs and directions are outlined.

An argument against using standardized test scores for placement of international undergraduate students in English as a Second Language (ESL) courses

Development and administration of institutional ESL placement tests require a great deal of financial and human resources. Due to a steady increase in the number of international students studying in the United States, some US universities have started to consider using standardized test scores for ESL placement. The English Placement Test (EPT) is a locally administered ESL placement test at the University of Illinois at Urbana-Champaign (UIUC). This study examines the appropriateness of using pre-arrival SAT, ACT, and TOEFL iBT test scores as an alternative to the EPT for placement of international undergraduate students into one of the two levels of ESL writing courses at UIUC. Exploratory analysis shows that only the lowest SAT Reading and ACT English scores, and the highest TOEFL iBT total and Writing section scores can separate the students between the two placement courses. However, the number of undergraduate ESL students, who scored at the lowest and highest ends of each of these test scales, has been very low over the last six years (less than 5%). Thus, setting cutoff scores for such a small fraction of the ESL population may not be very practical. As far as the majority of the undergraduate ESL population is concerned, there is about a 40% chance that they may be misplaced if the placement decision is made solely on the standardized test scores.

Eligibility Determination Using a Curriculum-Based Assessment

This study examined the accuracy of a curriculum-based assessment for use during the eligibility process for Individuals with Disabilities Education Improvement Act (IDEA) services. The study extended a previous investigation in which performance scores of children without disabilities on the Assessment, Evaluation, and Programming System (AEPS) were used to set cutoff scores at 6-month age intervals. These cutoff scores were then tested for service eligibility classification accuracy. The present study specifies and examines cutoff scores at more specific age intervals and performance domains. Present study findings largely replicated results of the original study. The AEPS cutoff scores were found to accurately classify most eligible children but did overidentify some ineligible children. The data from these two studies suggest that, to the extent allowed by state criteria, early intervention/early childhood special education personnel may be able to use the AEPS test as a valid assessment tool while qualifying children for IDEA services.

A Review of Court Decisions on Cognitive Ability Testing, 1992-2004

General cognitive ability is likely the single best predictor of job performance, although it typically results in race-based adverse impact. The majority of the 22 cognitive ability testing cases in appellate and district courts from 1992 to 2004 involved class action plaintiffs and civil service jobs. Organizations that used professionally developed tests that were validated and that set cutoff scores supported by the validity study fared well in court. The validation study must be conducted according to professional standards, and the results should be used properly when setting cutoff scores. Plaintiffs in cognitive ability test-related lawsuits were likely to be members of minority groups; the majority of cases were race-based claims. Utilizing a consultant to develop and validate selection tests may ensure the appropriate expertise and a professionally developed and validated test; however, it does not alleviate the responsibility of the employer for adverse impact.

A Meta-Analysis of the Effects of Modifications to the Angoff Method on Cutoff Scores and Judgment Consensus

The Angoff method for setting cutoff scores on examinations has been researched extensively over the past 30 years, including investigations of several procedural modifications to the method. In the current study, the authors meta-analytically synthesized this research and evaluated the systematic effects of the most common modifications on the level of the resulting cutoff scores and the degree of consensus among judges. The authors found the following: (a) when judges use a common definition of minimally competent test-takers, this tends to increase judgment consensus; (b) when judges discuss their estimates, this tends to result in higher cutoff scores with increased consensus; and (c) when judges view normative data, this tends to systematically lower cutoff scores. In addition, the authors found an interaction effect which revealed that when judges use a common definition and later discuss their estimates, this tends to produce the highest standards on average, with the highest degree of consensus among judges. Theoretical and practical implications of these effects are discussed.

A validity study of expert judgment procedures for setting cutoff scores on high-stakes credentialing examinations using cluster analysis.

This study compares an expert judgment process--minimal performance levels (MPL) using the Nedelsky and Ebel procedures--for setting cutoff scores for pass/fail on licensure examinations with an empirical approach--cluster analysis. Data from all three components of the Canadian Standard Assessment in Optometry (CSAO) examinations (knowledge, clinical judgment, and clinical skills) from 243 candidates were obtained. Results indicate that for the written components of the exams employing the Nedelsky method of MPL setting, there was a mean agreement of pass/fail of 81% with the cluster analysis approach on pass/fail categorization. For the performance exams using the Ebel method, the mean agreement of pass/fail with the cluster analysis was 93%. Thus the subjective approaches to setting cutoff scores (i.e., expert judgment methods) converge with the objective method (i.e., cluster analysis) of classifying test takers in the same categories.

High Percentages are Not the Same as High Standards

Mr. Guskey reminds us that, even when complex statistical formulas are used in setting cutoff scores, their mathematical precision is not a substitute for sound professional judgment. HOW TO set appropriate cutoff scores for student performance on state assessments and other high-stakes examinations is a widely debated issue in education today. Typically these debates focus on what percentage of items students should be expected to correctly in order to have their performance judged proficient or competent. On the Texas Assessment of Academic Skills (TAAS), for example, students must 70% correct in order to attain a passing score. This debate often extends to the classroom level, where teachers set cutoff scores for different grades. What percentage correct should students be expected to attain, for instance, to receive a grade of A or a grade of B, and so on? Both policy makers and teachers generally assume that higher cutoff percentages mean more rigorous standards and higher expectations for student performance. A cutoff of 80% correct for proficiency in mathematics, for instance, is considered more rigorous than a 70% correct cutoff for proficiency in language arts. Similarly, the teacher who sets 95% correct as the cutoff for a grade of A is considered to be more demanding and to have higher standards than the teacher who uses a cutoff of only 90% or 92% correct for an A. This reasoning leads to the belief that raising the percentage for a cutoff is one way to raise both the standards and the expectations we set for student performance. Unfortunately, it isn't quite that simple. Setting cutoff percentages for assessments and for grades is an arbitrary decision that says little about the standards or the expectations set for students' learning. A much more important consideration is the difficulty of the tasks students are asked to perform or the cognitive complexity of the questions they are required to answer. The cutoff percentage representing an excellent level of performance on an extremely challenging task or a very difficult set of questions might be quite different from the cutoff percentage considered excellent on a relatively simple task. This does not imply that the challenge is determined strictly by how well other students perform (i.e., norm-referenced). Rather, it means that tasks or items designed to assess a given learning goal (i.e., criterion-referenced) can vary widely in their intricacy and cognitive complexity. Suppose, for example, we were interested in assessing students' basic knowledge about the Presidents of the United States. We could ask an open-ended, constructed-response question (also known as a short- answer or completion item): Who was the 17th President of the United States?1 Fewer than 10% of students are able to this question correctly. Its high level of difficulty is actually rather odd because most people know that Abraham Lincoln was the 16th President, and they know that the name of the President who succeeded him was Johnson. Putting these two pieces of information together, however, proves quite difficult for the vast majority. We might then consider framing the same question as a multiple-choice, selected-response item. For example: Who was the 17th President of the United States? A. Abraham Lincoln B. Andrew Johnson C. Ulysses S. Grant D. Millard Fillmore This remains a fairly difficult item for most students. Because of the multiple-choice format, however, about 30% are now able to correctly. Of course, if all students simply chose an at random, the limited-response, multiple-choice format would allow 25% to select the correct response. Suppose we next adjust the possible responses, making the distinctions a bit more obvious: Who was the 17th President of the United States? A. …

Setting Cutoff Scores for Personnel Selection Tests: issues. Illustrations, and Recommendations

Cutoff scores are necessary in many public sector selection contexts. In this article, reasons for using cutoff scores, legal and professional guidelines, and methods for setting cutoff scores are examined. Recent literature on the Angoff method is reviewed, and 2 applications of this approach are explored in public sector contexts. In Study 1, 3 variations on the Angoff method applied to a multiple-choice test for fire chief were compared. In Study 2, standards were set for a physical ability test for firefighter using an Angoff-based method. Data and methods from both studies are discussed in terms of reliability, practicality, and the organizational issues involved in implementation. Finally, we review areas for future research that could improve the standard setting process, and we give recommendations for standard setters based on the current literature.

Hindsight bias in an application of the Angoff method for setting cutoff scores.

Hindsight bias in an application of the Angoff method for setting cutoff scores.

Hindsight bias in an application of the Angoff method for setting cutoff scores.

This study used the hindsight bias literature to examine the effects of providing test item answers on the level and predictive accuracy of Angoff cutoff score judgments. Subjects, randomly assigned to either an answers or a no-answers group, made Angoff judgments on items testing knowledge of driving law and vehicle operation. Items were catagorized into subtests based on empirical difficulty. Results indicated that providing answers interacted with subtest difficulty to influence the level of Angoff judgments. On the easiest subtest, those in the answer group made higher judgments than did those in the no-answers groups; the reverse effect was observed on the most difficult subtest.

How to Set Cutoff Scores for Knowledge Tests Used in Promotion, Training, Certification, and Licensing

Why not set the cutoff score at 70 percent? That score has been used as passing throughout elementary school, junior high school, high school, and college. Most people are familiar with a 70 percent cutoff because of our experiences in the school system. If a score has been used for so long as a standard, why change it? Why challenge it? I have heard judges ask these questions, administrators, attorneys, and analysts. The specific score that is used as the cutoff is what separates those who pass a test from those who do not. It is this score that determines the consequences of taking the test. Those who take a test and do not reach the cutoff score are not considered further for promotion. Or if the test is the conclusion to a training course, by missing the cutoff score, the person may have to take the training again. If the test is for certification, scoring below the cutoff means having to try again for certification. Failing the licensing test means having to wait another six months or a year to take the test again, and, perhaps, not getting a substantial pay increase. The time that an unsuccessful test taker has to wait before taking a test again will vary. Two years is a common time period between test administrations when litigation is not involved. However, when litigation has been involved, hundreds of employees working for one employer waited 11 years between promotional tests. Hundreds of others employees have had to wait 6 years between promotional tests due to delays resulting from litigation. A line must be drawn somewhere to distinguish between those who possess enough knowledge to pass a training course, to be considered further for promotion, to be certified, or to be licensed. It is the specific score called the cutoff score that creates the two classes of people: those who pass and those who fail. The group who passes rarely sues. Litigation comes from the group failing a test. But not for the litigants, 70 percent might still be a universally acceptable cutoff score for promotional tests, training tests, certification tests, and tests used for licensing. Litigation, however, requires responses to penetrating questions directed to the person in charge of the test. These questions come in the form of interrogatories (written questions from the opposing party's attorney that must be answered under penalty of perjury), at depositions (a sit down session in a private office after receiving a subpoena where the opposing party's attorney verbally asks questions and a court reporter carefully takes down the reply), and court testimony where the opposing party's attorney cross examines the person testifying (asks questions of a party under oath in a court room after direct testimony has been given by that party). Questions asked will deal with the job analysis, test construction, validation procedures, and how the cutoff was determined. If a minimum cutoff score is to be set, it makes sense to gather data needed to set the score in a defensible way and to consider the factors that incite litigation. See Cascio (1988) for a discussion of the factors. For a discussion of how the burdens are followed in court cases after the United States Supreme Court decision of Wards Cove Packing v. Atonio see Biddle (1989). The purpose of this paper is to suggest a process for setting a cutoff on knowledge tests used for promotion, training, certification, and licensing. The suggested cutoff setting process incorporates the advantages of the job related process reviewed by the United States Supreme Court, adds some job related features to it, then combines the modified job related process with a distribution-wide adverse impact analysis. The process described in this paper starts immediately after the job analysis, test specification, and test development work have been completed. Job Related Cutoff Setting Process Uniform Guidelines Requirement The Uniform Guidelines on Employee Selection Procedures (1978) give us only vague guidance stating that when setting cutoff scores they should normally be set so as to be reasonable and consistent with normal expectations of acceptable proficiency within the work force. …

Setting Cutoff Scores on Credentialing Examinations

Standard setting is one of the critical components of any test development program; in credentialing examinations it is of particular concern because the cutoff score is the ultimate criterion for determining cognitive competency. This study presents a new and refined version of the Nedelsky standard-settingprocedure that is designed to eliminate several methodological problems, and to be easily applied by subject matter experts. The validity of this new procedure is analyzed based on item and test data from the actual administration of the 3-part national credentialing examination developed by the National Board of Examiners in Optometry.