Two-parameter Item Response Theory Model Research Articles

Race/ethnicity and the measurement of cognition in NSHAP: Recommendations for robustness.

In this study, we examine the measurement of cognition in different racial/ethnic groups to move towards a less biased and more inclusive set of measures for capturing cognitive change and decline in older adulthood. We use data from Round 2 (N=3377) and Round 3 (N=4777) of the National Social Life, Health, and Aging Project (NSHAP) and examine the study's Survey Adjusted version of the Montreal Cognitive Assessment (MoCA-SA). We employ exploratory factor analyses to explore configural invariance by racial/ethnic group. Using modification indexes, two-parameter item response theory models, and split-sample testing, we identify items that seem robust to bias by race. We test the predictive validity of the full (18-item) and short (4-item) MoCA-SAs using self-reported dementia diagnosis, instrumental activities of daily living (IADLs), proxy reports of dementia, proxy reports of dementia-related death, and National Death Index reports of dementia-related death. We found that four measures out of the 18 used in NSHAP's MoCA-SA formed a scale that was more robust to racial bias. The shortened form predicted consequential outcomes as well as NSHAP's full MoCA-SA. The short form was also moderately correlated with the full form. Although sophisticated structural equation modeling techniques would be preferrable for assuaging measurement invariance by race in NSHAP, the shortened form of the MoCA-SA provides a quick way for researchers to carry out robustness checks and to see if the disparities and associations by race they document are "real" or the product of artifactual bias.

Addressing Cognitive Assessment Disparities Among Hispanic Adults: Adapting the MoCA-SA for Improved Accuracy and Accessibility Among Spanish-speakers.

Hispanic adults display a higher likelihood of early-stage cognitive decline than their White counterparts yet receive fewer clinical diagnoses. This troubling trend highlights the significance of longitudinal surveys like the National Social Life, Health, and Aging Project (NSHAP) in monitoring cognitive changes in aging Hispanics. Using NSHAP's Rounds 2 and 3, we observed notable cognitive score differences between English and Spanish speakers, as assessed by the survey-adapted version of the Montreal Cognitive Assessment (MoCA-SA). Our study aims to discern if statistical adjustments can reduce measurement variance in global cognition scores between these language groups. We applied modification indexes, two-parameter item response theory models, and split-sample testing to pinpoint items that exhibit resilience to language-related bias among our Hispanic sample. From this analysis, an abbreviated version of the MoCA-SA, termed MoCA-SAA, was introduced. Subsequently, we juxtaposed the performance and predictive validity of both MoCA versions against four consequential outcomes indicative of cognitive decline. Our refined methodologies enabled the identification of consistent items across both language cohorts. The MoCA-SAA demonstrated a performance and predictive validity in line with the original MoCA-SA concerning outcomes linked to cognitive deterioration. The translated measures ensure the inclusion of Hispanic Spanish speakers in NSHAP, who might otherwise be overlooked. The statistical adjustment outlined in this study offers a means to mitigate potential measurement disparities when assessing overall cognition. Despite these advancements, we acknowledge persistent issues related to the translation of the MoCA-SA into Spanish that warrant further attention.

Development of a rapid tool for screening financial toxicity based on the comprehensive score for financial toxicity

ObjectiveThis study aimed to use item response theory (IRT) to develop and validate a short version of the Chinese COmprehensive Score for financial Toxicity (COST-S-C) in patients with cancer. MethodsA total of 500 patients with cancer participated in the survey. Confirmatory factor analysis (CFA) was used to assess the factor structure of the COST-S-C. A two-parameter IRT model was used to examine the item fit of the COST-S-C. Item discrimination, item characteristic curves (ICCs), item information curves (IICs), and item fit were estimated. Differential item functioning (DIF) was assessed for participants’ gender and age. Reliability, convergent and discriminant validity was examined as well as estimating the optimal cut-off points of the COST-S-C. ResultsThe CFA results supported the bi-factor structure of the COST-S-C. The IRT analysis findings revealed that several items showed problems with the ICCs, providing little information in terms of IICs as well as poor discrimination. Item 5 showed a negligible DIF problem with age. A valid 3-item COST-S-C scale and its optimal cut-off point was developed. ConclusionsThe COST-S-C is a valid and quick screening tool used to distinguish patients with cancer who report significant financial toxicity in various medical settings.

Comparison of statistical models for individual’s ability index and ranking

ABSTRACT Economic efficiency demands accurate assessment of individual ability for selection purposes. This study investigates Classical Test Theory (CTT) and Item Response Theory (IRT) for estimating true ability and ranking individuals. Two Monte Carlo simulations and real data analyses were conducted. Results suggest a slight advantage for IRT, but ability estimates from both methods were highly correlated (r=0.95), indicating similar outcomes. The Logistic two-parameter IRT model emerged as the most reliable and rigorous approach.

30 Item response theory and differential item functioning of the AD8: The High School & Beyond Study

Objective:The AD8 is a validated screening instrument for functional changes that may be caused by cognitive decline and dementia. It is frequently used in clinics and research studies because it is short and easy to administer, with a cut off score of 2 out of 8 items recommended to maximize sensitivity and specificity. This cutoff assumes that all 8 items provide equivalent “information” about everyday functioning. In this study, we used item response theory (IRT) to test this assumption. To determine the relevance of this measure of everyday functioning in men and women, and across race, ethnicity, and education, we conducted differential item functioning (DIF) analysis to test for item bias.Participants and Methods:Data came from the 2021 follow up of the High School & Beyond cohort (N=8,690; mean age 57.5 ± 1.2; 55% women), a nationally representative, longitudinal study of Americans who were first surveyed in 1980 when they were in the 10th or 12th grade. Participants were asked AD8 questions about their own functioning via phone or internet survey. First, we estimated a one-parameter (i.e., differing difficulty, equal discrimination across items) and two-parameter IRT model (i.e., differing difficulty and differing discrimination across items). We compared model fit using a likelihood-ratio test. Second, we tested for uniform and non-uniform DIF on AD8 items by sex, race and ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic), education level (high school or less, some college, BA degree or more), and survey mode (phone or internet). We examined DIF salience by comparing the difference between original and DIF-adjusted AD8 scores to the standard error of measurement of the original score.Results:The two-parameter IRT model fit the data significantly better than the one-parameter model, indicating that some items were more strongly related to underlying everyday functional ability than others. For example, the “problems with judgment” item had higher discrimination (more information) than the “less interest in hobbies/activities” item. There were significant differences in item endorsement by race/ethnicity, education, and survey mode. We found significant uniform and non-uniform DIF on several items across each of these groups. For example, for a given level of functional decline (theta) White participants were more likely to endorse “Daily problems with thinking/memory” than Black and Hispanic participants. The DIF was salient (i.e., caused AD8 scores to change by greater than the standard error of measurement for a large portion of respondents) for those with a college degree and phone respondents.Conclusions:In a population representative sample of Americans ∼age 57, the items on the AD8 contributed differing levels of discrimination along the range of everyday functioning that is impacted by later life cognitive impairment. This suggests that a simple cut-off or summed score may not be appropriate since some items yield more information about the underlying construct than others. Furthermore, we observed significant and salient DIF on several items by education and survey mode, AD8 scores should not be compared across education groups and assessment modes without adjustment for this measurement bias.

Item response theory analysis of the University Personality Inventory in medical students.

Young adulthood has been recognized as an important period for the transition from adolescence to adulthood. The University Personality Inventory (UPI), a mental health questionnaire for young adulthood, is widely used to screen university students in East Asia. However, dichotomous systems do not allow respondent choose responses other than two options on each symptom. This study employed item response theory (IRT) to examine the properties and performance of UPI items for mental health problems. Japanese medical students (n = 1185) participated in this study, and the UPI was completed at the time of university admission. The two-parameter IRT model was used to assess the measurement characteristics of the UPI items. Among all participants, 35.4% (420/1185) had total UPI score of 21 or more, and 10.6% (126/1185) indicated that they had the idea of wanting to die (item 25). For further IRT analysis, unidimensionality was confirmed by exploratory factor analysis, in which the primary factor accounted for 39.6% of the variance. The scale has sufficient discrimination power. In the test characteristic curves, the rising slopes of the lines were between θ 0 and 2. The UPI is useful to assess mild or moderate mental health problems, while precision may decline among individuals experiencing both little and extremely high levels of stress. Our findings provide a basis for identifying people who have mental health concerns.

Development and validation of the clinical information literacy questionnaire.

Clinical Information Literacy (CIL) seems to be a prerequisite for physicians to implement Evidence-Based Medicine (EBM) effectively. This study endeavors to develop and validate a CIL questionnaire for medical residents of Isfahan University of Medical Sciences. This study employs sequential-exploratory mixed methods in 2019. The participants were 200 medical residents in different specialties; they are selected through the convenience sampling method. In the first (qualitative) phase, an early CIL questionnaire was designed by reviewing literature and performing complementary interviews with health professionals. In the second (validation) phase, the questionnaire's face validity and content validity were confirmed. In the third (quantitative) phase, the construct validity was examined via Item-Response Theory (IRT) model, and the factor loading was computed. The gathered data were analyzed using descriptive statistics, t-test, two-way ANOVA, as well as two-parameter IRT model in R software. In the qualitative phase, the concept of CIL is initially described in seven main categories and 22 subcategories, and the items were formulated. An initial 125-item questionnaire was analyzed by the research team, leading to a 43-item. Through the content validity and face validity examination, we removed 11 and 4 items in the Content Validity Ratio (CVR) and Content Validity Index (CVI), respectively. Throughout the face validity analysis, none of the items were removed. According to the construct validity results, difficulty coefficient, discriminant coefficient, and factor loading were confirmed, most of the other questions achieved a proper factor loading value that is higher than 0.30, and a value of 0.66 was achieved for the reliability via the Kuder-Richardson method. Ultimately, the real-assessment 28-item CIL questionnaire was developed with four components. The CIL questionnaire could be employed to examine the actual CIL basic knowledge. Because of using the real-assessment approach rather than self-assessment in the design, it can be claimed that this instrument can provide a more accurate assessment of the information literacy status of medical residents. This valid questionnaire is used to measure and train the skills needed by healthcare professionals in the effective implementation of EBM.

Self-regulated learner profiles in MOOCs: A cluster analysis based on the item response theory

ABSTRACT Self-regulated learning is a crucial skill that may enable massive numbers of learners to thrive in MOOCs, but MOOC learners differ in their self-regulated learning skills, as low self-regulated learners need support to regulate their learning process in MOOCs. Designing self-regulated learning scaffoldings builds upon an accurate appraisal of learners’ self-regulated learning and also a person-centered understanding of self-regulated learner profiles in MOOCs. Therefore, this study applied a two-parameter item response theory model to accurately evaluate online learners’ self-regulated learning in MOOCs and then performed a cluster analysis to identify learner profiles in terms of their traits in each phase of self-regulated learning. The findings of this study identified five clusters of self-regulated learner profiles, upon which a further statistical analysis result indicated that the learners with lower forethought skills might be less committed to completing course assignments. Implications for self-regulated learning in MOOCs are discussed at the end.

Bayesian Model Assessment for Jointly Modeling Multidimensional Response Data with Application to Computerized Testing.

Computerized assessment provides rich multidimensional data including trial-by-trial accuracy and response time (RT) measures. A key question in modeling this type of data is how to incorporate RT data, for example, in aid of ability estimation in item response theory (IRT) models. To address this, we propose a joint model consisting of a two-parameter IRT model for the dichotomous item response data, a log-normal model for the continuous RT data, and a normal model for corresponding paper-and-pencil scores. Then, we reformulate and reparameterize the model to capture the relationship between the model parameters, to facilitate the prior specification, and to make the Bayesian computation more efficient. Further, we propose several new model assessment criteria based on the decomposition of deviance information criterion (DIC) the logarithm of the pseudo-marginal likelihood (LPML). The proposed criteria can quantify the improvement in the fit of one part of the multidimensional data given the other parts. Finally, we have conducted several simulation studies to examine the empirical performance of the proposed model assessment criteria and have illustrated the application of these criteria using a real dataset from a computerized educational assessment program.

Dual Indicators to Analyze AI Benchmarks: Difficulty, Discrimination, Ability, and Generality

Item response theory (IRT) can be applied to the analysis of the evaluation of results from AI benchmarks. The two-parameter IRT model provides two indicators (difficulty and discrimination) on the side of the item (or AI problem) while only one indicator (ability) on the side of the respondent (or AI agent). In this paper we analyse how to make this set of indicators dual, by adding a fourth indicator, generality, on the side of the respondent. Generality is meant to be dual to discrimination, and it is based on difficulty. Namely, generality is defined as a new metric that evaluates whether an agent is consistently good at easy problems and bad at difficult ones. With the addition of generality, we see that this set of four key indicators can give us more insight on the results of AI benchmarks. In particular, we explore two popular benchmarks in AI, the Arcade Learning Environment (Atari 2600 games) and the General Video Game AI competition. We provide some guidelines to estimate and interpret these indicators for other AI benchmarks and competitions.

Psychometric evaluation of the disabilities of the arm, shoulder and hand (DASH) in patients with orthopedic shoulder impairments seeking outpatient rehabilitation

Study DesignThis is a cross-sectional, observational study. IntroductionThe disability of the arm, shoulder and hand (DASH) questionnaire is an upper-extremity specific outcome measure commonly used in routine clinical care and clinical trials. Purpose of the StudyOur purposes were to: (1) examine the psychometric properties of the DASH questionnaire using factor analysis, one- and two-parameter item response theory models, and (2) develop a functional staging map illustrating the relationships between the item difficulty hierarchy of the DASH items and the patient's DASH total score. MethodsData from 2724 patients with orthopedic shoulder impairments seeking outpatient physical therapy in 79 clinics in the US were analyzed. ResultsFactor analysis supported a general factor, explaining 62.2% of the total variance. The coverage of DASH items was suitable for patients with shoulder impairments with no ceiling or floor effect. Endorsed items representing the most difficult items were related to feeling less capable, executing recreational activities with force or impact, and performing recreational activities in which you move your arm freely. Items with higher discriminating abilities were those related to do heavy household chores, garden/yard work, and change a light bulb overhead. With a separation index equaled to 4.94, the DASH can differentiate persons into at least 6 statistically distinct person strata. None of the DASH items exhibited differential item functioning by gender or symptom acuity, except two items by age group. DiscussionBesides a total (summed) final score obtained from a specific measure, the keyform and functional staging plots/maps can be used to assist clinicians in clinical interpretation of the scores. ConclusionsResults supported the clinical usage of the DASH questionnaire in patients with orthopedic shoulder impairments seeking outpatient rehabilitation.

Psychometric Validation of the Danish Version of the Oswestry Disability Index in Patients With Chronic Low Back Pain.

Registry-based repeated-measures psychometric validation of the Danish Oswestry Disability Index (ODI). The goal was to use classical and modern psychometric validation methods to assess the measurement properties and the minimally clinical important difference (MCID) of the ODI in a Danish cohort of patients with chronic low back pain being treated with spinal surgery. Scores for the ODI, EQ-5D, SF-36, leg pain, back pain, and a general rating of pain item from 800 patients with chronic low back pain were extracted from the National Danish Spine Registry (DaneSpine) at baseline and 1-year postspine surgery. Confirmatory factor analysis and item response theory (IRT) models were used to assess the psychometric properties of the ODI. MCID was also calculated based on generic legacy PROMs (EQ-5D and SF-36) and follow-up pain scores. While ODI did not fit a Rasch model, adequate fit to a confirmatory factor analysis and a two-parameter item response theory model was found when accounting for differential item functioning across diagnostic subgroups (degenerative spondylolisthesis, spondylosis, spinal stenosis, and herniated intervertebral disc). In addition, each group exhibited substantially different MCID values. The Danish version of the ODI is valid and responsive, but only within each of the four major diagnosis subgroups: degenerative spondylolisthesis, spondylosis, spinal stenosis, and herniated intervertebral disc. 4.

Derivation and assessment of the opioid use disorder severity scale: prediction of health, psychological and social adjustment problems

ABSTRACT Background: Severity of substance use disorder (SUD) is typically evaluated by tabulating the number of symptoms. The resulting estimate of disorder severity is, however, biased due to intercorrelations among symptoms and their unequal salience. Objective. Employing item response theory (IRT) methodology, opioid use disorder symptoms were calibrated to derive the Opioid Use Disorder Severity Scale (OUDSS) and assess its predictive ability in men and women separately. Methods: A two-parameter IRT model was utilized to derive the OUDSS from DSM-IV symptoms recorded on the Structured Clinical Interview for DSM-IV (SCID) in 438 men and 429 women who reported at least one lifetime opioid consumption event. The predictive ability of the OUDSS was evaluated using the 10 health, psychological, and social adjustment domains of the revised Drug Use Screening Inventory (DUSI-R) assessed 2 years later. Results: The OUDSS score predicted the severity of problems in all 10 DUSI-R domains in men and women. The OUDSS also predicted the DUSI-R diagnostic cutoff score of overall problem density score in men and women (OR = 2.21 and OR = 4.83, respectively). Withdrawal was the most frequently endorsed symptom in this sample of opioid users. The other symptoms’ frequencies, while somewhat lower than withdrawal’s, did not differ from it substantially, indicating a similar severity threshold. Conclusions: OUDSS enables dimensional measurement of opioid use severity on an interval scale. The OUDSS and DUSI-R together can identify problem areas requiring prevention or treatment.

PROMIS Physical Function Short Forms Display Item- and Scale-Level Characteristics at Least as Good as the Roland Morris Disability Questionnaire in Patients With Chronic Low Back Pain

ObjectiveTo compare dimensionality, item-level characteristics, scale-level reliability, and construct validity of PROMIS Physical Function short forms (PROMIS-PF) and 24-item Roland Morris Disability Questionnaire (RMDQ-24) in patients with chronic low back pain (LBP). DesignCross-sectional study. SettingSecondary care center for rehabilitation and rheumatology. ParticipantsPatients with nonspecific LBP ≥3 months (N=768). Mean age was 49±13 years, 77% were female, and 54% displayed pain for more than 5 years. InterventionsNot applicable. Main Outcome MeasuresDutch versions of the 4-, 6-, 8-, 10-, and 20-item PROMIS-PF and of the RMDQ-24. ResultsPROMIS-PF-6, PROMIS-PF-8, and RMDQ-24 exhibited sufficient unidimensionality (confirmatory factor analysis: comparative fit index>0.950, Tucker-Lewis index>0.950, root means square error of approximation<0.060), whereas the other instruments did not. All instruments were free of local dependence except PROMIS-PF-20 with 4 item pairs with clear residual correlations. Mokken scale analysis found 1 nonmonotone item for PROMIS-PF-20 and 8 for RMDQ-24 (ie, the probability of endorsing these items was not increasing with increasing level on the underlying construct). PROMIS-PF-20 displayed 2 misfitting items (S-χ2P value>.001). Two-parameter item response theory models found 2 items with low discrimination for RMDQ-24. All other instruments had adequate fit statistics and item parameters. PROMIS-PF-20 displayed the best scale-level reliability. Construct validity was sufficient for all instruments as all hypotheses on expected correlations with other instruments and differences between relevant subgroups were met. ConclusionsPROMIS-PF-6, PROMIS-PF-8, and RMDQ-24 exhibited better unidimensionality, whereas PROMIS-PF-4, PROMIS-PF-6, PROMIS-PF-8, and PROMIS-PF-10 showed superior item-level characteristics. PROMIS-PF-20 was the instrument with the best scale-level reliability. This study warrants assessment of other measurement properties of PROMIS-PF short forms in comparison with disease-specific physical functioning instruments in LBP.

An Item Response Theory Analysis of the Korean Version of the CRAFFT Scale for Alcohol Use Among Adolescents in Korea

PurposeThis study aimed to validate the psychometric properties of the CRAFFT (Car, Relax, Alone, Forget, Family/Friends, Trouble) by using item response theory (IRT) and further examine gender differences in item-level responses. MethodsThis study used the 13th (2017) Korea Youth Risk Behavior Survey data conducted by the Korean Centers for Disease and Prevention and analyzed data of 8,568 students who reported drinking alcohol in the previous 30 days. IRT assumptions including unidimensionality, local independence, and monotonicity were tested. A one-factor two-parameter IRT model was fitted for item parameterization (M2 = 76.92, 20 df, p < .001, root mean square error of approximation = 0.02). Graphics for item characteristic curves and item and test information curves were provided. Differential item functioning (DIF) analysis was evaluated to measure item equivalence between boys and girls. ResultsUnidimensionality and local independence were satisfied, and the dominant factor eigenvalue and variance were 2.48 and 41.3% in boys and 2.08 and 34.7% in girls, respectively, and residual correlations in paired items were less than .2. The discrimination parameters were estimated as 1.32–3.59 for boys and 1.30–3.64 for girls. The severity parameters estimated verity as −0.23 to 1.67 for boys and −0.32 to 2.17 for girls. DIF was detected for four of six items, “Car,” “Relax,” “Forget,” and “Family/friends.” However, its impact on the total score was negligible. ConclusionThe CRAFFT is a valid and reliable screening tool to identify alcohol use problems for both boys and girls, exhibiting good discrimination, good coverage of severity, and negligible DIF.

Improving measurement of injection drug risk behavior using item response theory

Background: Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored. Objectives: To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning. Methods: Data is used from three studies in the National Institute on Drug Abuse’s Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning. Results: Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data. Conclusion: Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.

Complex Versus Simple Modeling for DIF Detection

Previous research has demonstrated that differential item functioning (DIF) methods that do not account for multilevel data structure could result in too frequent rejection of the null hypothesis (i.e., no DIF) when the intraclass correlation coefficient (ρ) of the studied item was the same as the ρ of the total score. The current study extended previous research by comparing the performance of DIF methods when ρ of the studied item was less than ρ of the total score, a condition that may be observed with considerable frequency in practice. The performance of two simple and frequently used DIF methods that do not account for multilevel data structure, the Mantel–Haenszel test (MH) and logistic regression (LR), was compared with the performance of a complex and less frequently used DIF method that does account for multilevel data structure, hierarchical logistic regression (HLR). Simulation indicated that HLR and LR performed equivalently in terms of significance tests under most conditions, and MH was conservative across most of the conditions. Effect size estimate of HLR was equally accurate and consistent as effect size estimates of LR and MH under the Rasch model and was more accurate and consistent than LR and MH effect size estimates under the two-parameter item response theory model. The results of the current study provide evidence to help researchers further understand the comparative performance between complex and simple modeling for DIF detection under multilevel data structure.

Development and evaluation of a crosswalk between the SF-36 physical functioning scale and Health Assessment Questionnaire disability index in rheumatoid arthritis

BackgroundThe SF-36 physical functioning scale (PF-10) and the Health Assessment Questionnaire disability index (HAQ-DI) are the most frequently used instruments for measuring self-reported physical function in rheumatoid arthritis (RA). The objective of this study was to develop a crosswalk between scores on the PF-10 and HAQ-DI in RA.MethodsItem response theory (IRT) methods were used to co-calibrate both scales using data from 1791 RA patients. The appropriateness of a Rasch-based crosswalk was evaluated by comparing it with crosswalks based on a two-parameter and a multi-dimensional IRT model. The accuracy of the final crosswalk was cross-validated using baseline (n = 532) and 6-month follow-up (n = 276) data from an independent cohort of early RA patients.ResultsThe PF-10 and HAQ-DI adequately fit a unidimensional Rasch model. Both scales measured a wide range of functioning, although the HAQ-DI tended to better target lower levels of functioning. The Rasch-based crosswalk performed similarly to crosswalks based on the two-parameter and multidimensional IRT models. Agreement between predicted and observed scale scores in the cross-validation sample was acceptable for group-level comparisons. The longitudinal validity in discriminating between disease response states was similar between observed and predicted scores.ConclusionThe crosswalk developed in this study allows for converting scores from one scale to the other and can be used for group-level analyses in patients with RA.

Mini-Cog and Mini-Mental State Examination: Agreement in a Cross-Sectional Study with an Elderly Sample

Background/Aims: We aimed to compare the Mini-Mental State Examination (MMSE) with the Mini-Cog, measuring agreement in participants’ classification, using a general population sample. Methods: Cross-sectional evaluation of 609 community dwellers aged ≥60 years was performed by trained interviewers. Cohen’s kappa and 95% confidence intervals (CI) were calculated to assess overall agreement, and Cronbach alphas computed to assess reliability. Two-parameter Item Response Theory models (difficulty and discrimination parameters) were used to assess discrimination. Results: Considering MMSE cut-point for scores <24, 3.1% of the participants would be ‘cognitive impaired’ and 6.2% considering cut-point scores <25. Following Mini-Cog’s cut-point score <3, 11.3% would be impaired. For MMSE cut-point <24 and Mini-Cog <3, we observed a Cohen’s kappa of 0.116 (95% CI: –0.073 to 0.305), and of 0.258 (95% CI: 0.101–0.415) for cut-point <25. The highest kappa was obtained for cut-point <26 on the MMSE and Mini-Cog <3 (kappa = 0.413). MMSE Cronbach alpha was 0.6108 and Mini-Cog’s alpha was 0.2776. Cocalibration according to inherent ability is graphically presented. Conclusions: Agreement between scales seems fragile in our sample. The discriminative and reliability analysis suggests a better performance for subsets of the MMSE compared with the Mini-Cog. Usefulness of calibrated scores is discussed.

Item response theory and the measurement of deprivation: evidence from Luxembourg data

Item response theory (IRT) has recently been proposed as a framework to measure deprivation. It allows a latent measure of deprivation to be derived from a set of dichotomous items indicating deprivation, and the determinants of deprivation to be analysed. We investigate further the use of IRT models in the field of deprivation measurement. First, the paper emphasises the importance of item selection and the Mokken Scale Procedure is applied to select the items to be included in the scale of deprivation. Second, we apply the one- and the two-parameter probit IRT models for dichotomous items to two different sets of items, in order to highlight different empirical results. Finally, we introduce a graphical tool, the Item Characteristic Curve (ICC), and analyse the determinants of deprivation in Luxembourg. The empirical illustration is based on the fourth wave of the “Liewen zu Letzebuerg” Luxembourg socioeconomic panel (PSELL-3).