Examining the Robustness of the Graded Response and 2-Parameter Logistic Models to Violations of Construct Normality

When fitting unidimensional item response theory (IRT) models, the population distribution of the latent trait (θ) is often assumed to be normally distributed. However, some psychological theories would suggest a nonnormal θ. For example, some clinical traits (e.g., alcoholism, depression) are believed to follow a positively skewed distribution where the construct is low for most people, medium for some, and high for few. Failure to account for nonnormality may compromise the validity of inferences and conclusions. Although corrections have been developed to account for nonnormality, these methods can be computationally intensive and have not yet been widely adopted. Previous research has recommended implementing nonnormality corrections when θ is not “approximately normal.” This research focused on examining how far θ can deviate from normal before the normality assumption becomes untenable. Specifically, our goal was to identify the type(s) and degree(s) of nonnormality that result in unacceptable parameter recovery for the graded response model (GRM) and 2-parameter logistic model (2PLM).

Assessing medical mistrust in organ donation across countries using item response theory

Although medical mistrust (MM) may be an impediment to public health interventions, no MM scale has been validated across countries and the assessment of MM has not been explored using item response theory, which allows generalisation beyond the sampled data. We aimed to determine the dimensionality of a brief MM measure across four countries through Mokken analysis and Graded Response Modelling. Analysis of 1468 participants from UK ( n = 1179), Ireland ( n = 191), India ( n = 49) and Malaysia (n = 49) demonstrated that MM items formed a hierarchical, unidimensional measure, which is very informative about high levels of MM. Possible item reduction and scoring changes were also demonstrated. This study demonstrates that this brief MM measure is suitable for international studies as it is unidimensional across countries, cross cultural, and shows that minor adjustments will not impact on the assessment of MM when using these items.

Symptom Presence and Symptom Severity as Unique Indicators of Psychopathology: An Application of Multidimensional Zero-Inflated and Hurdle Graded Response Models

Questionnaires inquiring about psychopathology symptoms often produce data with excess zeros or the equivalent (e.g., none, never, and not at all). This type of zero inflation is especially common in nonclinical samples in which many people do not exhibit psychopathology, and if unaccounted for, can result in biased parameter estimates when fitting latent variable models. In the present research, we adopt a maximum likelihood approach in fitting multidimensional zero-inflated and hurdle graded response models to data from a psychological distress measure. These models include two latent variables: susceptibility, which relates to the probability of endorsing the symptom at all, and severity, which relates to the frequency of the symptom, given its presence. After estimating model parameters, we compute susceptibility and severity scale scores and include them as explanatory variables in modeling health-related criterion measures (e.g., suicide attempts, diagnosis of major depressive disorder). Results indicate that susceptibility and severity uniquely and differentially predict other health outcomes, which suggests that symptom presence and symptom severity are unique indicators of psychopathology and both may be clinically useful. Psychometric and clinical implications are discussed, including scale score reliability.

Item Response Theory and Differential Item Functioning Analyses With the Suicidal Behaviors Questionnaire–Revised in US and Chinese Samples

Background: Despite the widespread use of the Suicidal Behaviors Questionnaire–Revised (SBQ-R) and advances in item response theory (IRT) modeling, item-level analysis with the SBQ-R has been minimal. Aims: This study extended IRT modeling strategies to examine the response parameters and potential differential item functioning (DIF) of the individual SBQ-R items in samples of US ( N = 320) and Chinese ( N = 298) undergraduate students. Method: Responses to the items were calibrated using the unidimensional graded response IRT model. Goodness-of-fit, item parameters, and DIF were evaluated. Results: The unidimensional graded response IRT model provided a good fit to the sample data. Results showed that the SBQ-R items had various item discrimination parameters and item severity parameters. Also, each SBQ-R item functioned similarly between the US and Chinese respondents. In particular, Item 1 (history of attempts) demonstrated high discrimination and severity of suicide-related thoughts and behaviors (STBs). Limitations: The use of cross-sectional data from convenience samples of undergraduate students could be considered a major limitation. Conclusion: The findings from the IRT analysis provided empirical support that each SBQ-R item taps into STBs and that scores for Item 1 can be used for screening purposes.

Generation and timing of graded responses to morphogen gradients

ABSTRACT Morphogen gradients are known to subdivide a naive cell field into distinct zones of gene expression. Here, we examine whether morphogens can also induce a graded response within such domains. To this end, we explore the role of the Dorsal protein nuclear gradient along the dorsoventral axis in defining the graded pattern of actomyosin constriction that initiates gastrulation in early Drosophila embryos. Two complementary mechanisms for graded accumulation of mRNAs of crucial zygotic Dorsal target genes were identified. First, activation of target-gene expression expands over time from the ventral-most region of high nuclear Dorsal to lateral regions, where the levels are lower, as a result of a Dorsal-dependent activation probability of transcription sites. Thus, sites that are activated earlier will exhibit more mRNA accumulation. Second, once the sites are activated, the rate of RNA Polymerase II loading is also dependent on Dorsal levels. Morphological restrictions require that translation of the graded mRNA be delayed until completion of embryonic cell formation. Such timing is achieved by large introns, which provide a delay in production of the mature mRNAs. Spatio-temporal regulation of key zygotic genes therefore shapes the pattern of gastrulation.

COVID-19 Outbreak in India: A Review of Preventive Measures and Challenges during the First Wave

Coronavirus disease 2019 (COVID-19) cases in India, the world's second most populous country, have been increasing rapidly in recent months, challenging India's ability to deal with this viral pandemic. The Government of India (GoI) and the States/UTs have taken a number of “pre-emptive, pro-active and graded” measures to prevent, contain, and manage COVID-19 in the country. These preventive measures and decisions taken by the GoI helped to stem the first wave of COVID-19 in the nation. Such measures and decisions were reviewed and monitored on a regular basis. The GoI followed a graded response approach, and ensured that there is no shortage of supplies of critical items, including medical Personal Protective Equipment (PPE), N95 masks, test kits, medications, and ventilators, across the country. The government ensured the establishment of COVID-19 hospitals at both the Center and the State to take care of the infected patients. Nations like India are at higher risk due to their large population density, inadequate infrastructure, and healthcare systems to satisfy extremely high demands.

Efficient and precise Ultra-QuickDASH scale measuring lymphedema impact developed using computerized adaptive testing

Purpose This study aimed to evaluate and improve the accuracy and efficiency of the QuickDASH for use in assessment of limb function in patients with upper extremity lymphedema using modern psychometric techniques. Method We conducted confirmative factor analysis (CFA) and Mokken analysis to examine the assumption of unidimensionality for IRT model on data from 285 patients who completed the QuickDASH, and then fit the data to Samejima’s graded response model (GRM) and assessed the assumption of local independence of items and calibrated the item responses for CAT simulation. Results Initial CFA and Mokken analyses demonstrated good scalability of items and unidimensionality. However, the local independence of items assumption was violated between items 9 (severity of pain) and 11 (sleeping difficulty due to pain) (Yen’s Q3 = 0.46) and disordered thresholds were evident for item 5 (cutting food). After addressing these breaches of assumptions, the re-analyzed GRM with the remaining 10 items achieved an improved fit. Simulation of CAT administration demonstrated a high correlation between scores on the CAT and the QuickDash (r = 0.98). Items 2 (doing heavy chores) and 8 (limiting work or daily activities) were the most frequently used. The correlation among factor scores derived from the QuickDASH version with 11 items and the Ultra-QuickDASH version with items 2 and 8 was as high as 0.91. Conclusion By administering just these two best performing QuickDash items we can obtain estimates that are very similar to those obtained from the full-length QuickDash without the need for CAT technology.

How the Perception of Public Official on Organizational Culture Influences Procedural Justice in Environmental Policy Processes

How does the organizational culture of local governments influence the type and extent of procedural justice in environmental policy processes? Using the culture theory developed by Mary Douglas and others, this research seeks to bring a new conception and new measures of organizational culture to the study of policy making by local governments. To contribute to the development of the conceptualization and measurement of procedural justice in the environmental policy processes of those governments, item response theory (IRT) graded response model (GRM) is used to show variations in difficulties and frequencies of adopting distinctive public participation strategies for improving procedural justice across local governments. In this study, original survey data is collected from Illinois municipalities and a finding is suggestive of cultural variables explaining the two dimensions of procedural justice, equal and authentic public participation, while other variables can, at best, explain only the equal public participation. Furthermore, as hypothesized, egalitarianism increases both equal and authentic public participation, individualism increases equal public participation, and fatalism decreases both.

Modern Test Theory Techniques for Adaptive Testing in Short Scales Comprising Polytomous Items: A Monte Carlo Simulation Study Comparing Rasch Measurement Theory to Unidimensional and Multidimensional Graded Response Models. (Preprint)

BACKGROUND There are two philosophical approaches to contemporary psychometrics: Rasch measurement theory (RMT) and item response theory (IRT). Either measurement strategy can be applied to computerized adaptive testing (CAT). There are potential benefits of IRT over RMT with regards to measurement precision, but also potential risks to measurement generalizability. RMT CAT assessments have demonstrated good performance with the CLEFT-Q, a patient-reported outcome measure for use in orofacial clefting. OBJECTIVE To test whether the post-hoc application of IRT (graded response models, GRMs, and multidimensional GRMs) to RMT-validated CLEFT-Q appearance scales could improve CAT accuracy at given assessment lengths. METHODS Partial credit Rasch models, unidimensional GRMs and a multidimensional GRM were calibrated for each of the 7 CLEFT-Q appearance scales (which measure the appearance of the: face, jaw, teeth, nose, nostrils, cleft lip scar and lips) using data from the CLEFT-Q field test. A second, simulated dataset was generated with 1000 plausible response sets to each scale. Rasch and GRM scores were calculated for each simulated response set, scaled to 0-100 scores, and compared by Pearson’s correlation coefficient, root mean square error (RMSE), mean absolute error (MAE) and 95% limits of agreement. For the face, teeth and jaw scales, we repeated this in a an independent, real patient dataset. We then used the simulated data to compare the performance of a range of fixed-length CAT assessments that were generated with partial credit Rasch models, unidimensional GRMs and the multidimensional GRM. Median standard error of measurement (SEM) was recorded for each assessment. CAT scores were scaled to 0-100 and compared to linear assessment Rasch scores with RMSE, MAE and 95% limits of agreement. This was repeated in the independent, real patient dataset with the RMT and unidimensional GRM CAT assessments for the face, teeth and jaw scales to test the generalizability of our simulated data analysis. RESULTS Linear assessment scores generated by Rasch models and unidimensional GRMs showed close agreement, with RMSE ranging from 2.2 to 6.1, and MAE ranging from 1.5 to 4.9 in the simulated dataset. These findings were closely reproduced in the real patient dataset. Unidimensional GRM CAT algorithms achieved lower median SEM than Rasch counterparts, but reproduced linear assessment scores with very similar accuracy (RMSE, MAE and 95% limits of agreement). The multidimensional GRM had poorer accuracy than the unidimensional models at comparable assessment lengths. CONCLUSIONS Partial credit Rasch models and GRMs produce very similar CAT scores. GRM CAT assessments achieve a lower SEM, but this does not translate into better accuracy. Commonly used SEM heuristics for target measurement reliability should not be generalized across CAT assessments built with different psychometric models. In this study, a relatively parsimonious multidimensional GRM CAT algorithm performed more poorly than unidimensional GRM comparators.

Accounting for Item Response Process and Response Styles Using the Unfolding Item Response Tree (UIRTree) Model

Many researchers have found that unfolding models may better represent how respondents answer Liker-type items and response styles (RSs) often have moderate to strong presence in responses to such items. However, the two research lines have been growing largely in parallel. The present study proposed an unfolding item response tree (UIRTree) model that can account for unfolding response process and RSs simultaneously. An empirical illustration showed that the UIRTree model could fit a personality dataset well and produced more reasonable parameter estimates. Strong presence of the extreme response style (ERS) was also revealed by the UIRTree model. We further conducted a Monte Carlo simulation study to examine the performance of the UIRTree model compared to three other models for Likert-scale responses: the Samejima’s graded response model, the generalized graded unfolding model, and the dominance item response tree (DIRTree) model. Results showed that when data followed unfolding response process and contained the ERS, the AIC was able to select the UIRTree model, while BIC was biased towards the DIRTree model in many conditions. In addition, model parameters in the UIRTree model could be accurately recovered under realistic conditions, and wrongly assuming the item response process or ignoring RSs was detrimental to the estimation of key parameters. In general, the UIRTree model is expected to help in better understanding of responses to Liker-type items theoretically and contribute to better scale development practically. Future studies on multi-trait UIRTree models and UIRTree models accounting for different types of RSs are expected.