Unidimensional Item Response Theory Research Articles

Validation of the Barthel Index in Chinese nursing home residents: an item response theory analysis.

The Barthel Index (BI) is used to standardize the grading of assessments for clinical needs, insurance support, and long-term care resource allocation in China. However, its psychometric properties among nursing home residents remain unclear. Therefore, this study aims to assess and modify the psychometric properties of BI in nursing home residents. A total of 1,402 individuals undergoing evaluation in a nursing home facility in China were included in this study from November 2021 to November 2022. Correlations between items were examined to identify the potential multicollinearity concerns. The unidimensional item response theory (IRT) was used to validate and modify the single structure of BI. Furthermore, the logistic regression/IRT hybrid DIF detection method was conducted to assess differential item functioning (DIF) between the dementia group and the normal group. The pairing of items 5 ("bowl control") and 6 ("bladder control") revealed a local dependence issue, leading to their consolidation. Items 56 (bowel and bladder control) and 9 (mobility) both displayed poor fit indices and underwent category collapsing. Through the application of the generalized partial credit model, the adjusted scale displayed better fit indices, demonstrating a robust discriminative power (DC >1.5) and orderly thresholds. Furthermore, non-uniform DIF was identified in item 2 (bathing) between the dementia group and the normal group. The modified BI demonstrated favorable psychometric properties and proved to be suitable for evaluating nursing home residents experiencing moderate functional impairment, which may provide a precise evaluation for long-term care resource allocation. Future studies could explore integrating supplementary measurements, such as objective indices, to assess a broader spectrum of functional statuses to potentially enhance the limited precision width observed in BI.

Examining Differential Item Functioning from a Multidimensional IRT Perspective.

Differential item functioning (DIF) is a standard analysis for every testing company. Research has demonstrated that DIF can result when test items measure different ability composites, and the groups being examined for DIF exhibit distinct underlying ability distributions on those composite abilities. In this article, we examine DIF from a two-dimensional multidimensional item response theory (MIRT) perspective. We begin by delving into the compensatory MIRT model, illustrating and how items and the composites they measure can be graphically represented. Additionally, we discuss how estimated item parameters can vary based on the underlying latent ability distributions of the examinees. Analytical research highlighting the consequences of ignoring dimensionally and applying unidimensional IRT models, where the two-dimensional latent space is mapped onto a unidimensional, is reviewed. Next, we investigate three different approaches to understanding DIF from a MIRT standpoint: 1. Analytically Uniform and Nonuniform DIF: When two groups of interest have different two-dimensional ability distributions, a unidimensional model is estimated. 2. Accounting for complete latent ability space: We emphasize the importance of considering the entire latent ability space when using DIF conditional approaches, which leads to the mitigation of DIF effects. 3. Scenario-Based DIF: Even when underlying two-dimensional distributions are identical for two groups, differing problem-solving approaches can still lead to DIF. Modern software programs facilitate routine DIF procedures for comparing response data from two identified groups of interest. The real challenge is to identify why DIF could occur with flagged items. Thus, as a closing challenge, we present four items (Appendix A) from a standardized test and invite readers to identify which group was favored by a DIF analysis.

How Scoring Approaches Impact Estimates of Growth in the Presence of Survey Item Ceiling Effects.

Survey scores are often the basis for understanding how individuals grow psychologically and socio-emotionally. A known problem with many surveys is that the items are all "easy"-that is, individuals tend to use only the top one or two response categories on the Likert scale. Such an issue could be especially problematic, and lead to ceiling effects, when the same survey is administered repeatedly over time. In this study, we conduct simulation and empirical studies to (a) quantify the impact of these ceiling effects on growth estimates when using typical scoring approaches like sum scores and unidimensional item response theory (IRT) models and (b) examine whether approaches to survey design and scoring, including employing various longitudinal multidimensional IRT (MIRT) models, can mitigate any bias in growth estimates. We show that bias is substantial when using typical scoring approaches and that, while lengthening the survey helps somewhat, using a longitudinal MIRT model with plausible values scoring all but alleviates the issue. Results have implications for scoring surveys in growth studies going forward, as well as understanding how Likert item ceiling effects may be contributing to replication failures.

Corrigendum to “irtplay: An R Package for Online Item Calibration, Scoring, Evaluation of Model Fit, and Useful Functions for Unidimensional IRT”

Corrigendum to “irtplay: An R Package for Online Item Calibration, Scoring, Evaluation of Model Fit, and Useful Functions for Unidimensional IRT”

The ABC of happiness: Validation of the tridimensional model of subjective well-being (affect, cognition, and behavior) using Bifactor Polytomous Multidimensional Item Response Theory

BackgroundHappiness is often conceptualized as subjective well-being, which comprises people's evaluations of emotional experiences (i.e., the affective dimension: positive and negative feelings and emotions) and judgements of a self-imposed ideal (i.e., the cognitive dimension: life satisfaction). Recent research has established these two dimensions as primary parts of a higher order factor. However, theoretical, conceptual, and empirical work suggest that people's evaluations of harmony in their life (i.e., the sense of balance and capacity to behave and adapt with both acceptance and flexibility to inter- and intrapersonal circumstances) constitutes a third dimension (i.e., the behavioral dimension). This tridemensional conceptualization of subjective well-being has recently been verified using Unidimensional Item Response Theory (UIRT) and Classical Test Theory (CTT). Here, we use a recently developed and more robust approach that combines these two methods (i.e., Multidimensional Item Response Theory, MIRT) to simultaneously address the complex interactions and multidimensionality behind how people feel, think, and behave in relation to happiness in their life. MethodA total of 435 participants (197 males and 238 females) with an age mean of 44.84 (sd = 13.36) responded to the Positive Affect Negative Affect Schedule (10 positive affect items, 10 negative affect items), the Satisfaction with Life Scale (five items), and the Harmony in life Scale (five items). We used Bifactor-Graded Response MIRT for the main analyses. ResultAt the general level, each of the 30 items had a strong capacity to discriminate between respondents across all three dimensions of subjective well-being. The investigation of different parameters (e.g., marginal slopes, ECV, IECV) strongly reflected the multidimensionality of subjective well-being at the item, the scale, and the model level. Indeed, subjective well-being could explain 64 % of the common variance in the whole model. Moreover, most of the items measuring positive affect (8/10) and life satisfaction (4/5) and all the items measuring harmony in life (5/5) accounted for a larger amount of variance of subjective well-being compared to that of their respective individual dimensions. The negative affect items, however, measured its own individual concept to a lager extent rather than subjective well-being. Thus, suggesting that the experience of negative affect is a more independent dimension within the whole subjective well-being model. We also found that specific items (e.g., “Alert”, “Distressed”, “Irritable”, “I am satisfied with my life”) were the recurrent exceptions in our results. Last but not the least, experiencing high levels in one dimension seems to compensate for low levels in the others and vice versa. ConclusionAs expected, the three subjective well-being dimensions do not work separately. Interestingly, the order and magnitude of the effect by each dimension on subjective well-being mirror how people define happiness in their life: first as harmony, second as satisfaction, third as positive emotions, and fourth, albeit to a much lesser degree, as negative emotions. Ergo, we argue that subjective well-being functions as a complex biopsychosocial adaptive system mirroring our attitude towards life in these three dimensions (A: affective dimension; B: behavioral dimension; C: cognitive dimension). Ergo, researchers and practitioners need to take in to account all three to fully understand, measure, and promote people's experience of the happy life. Moreover, our results also suggest that negative affect, especially regarding high activation unpleasant emotions, need considerable changes and further analyses if it is going to be included as a construct within the affective dimension of a general subjective well-being factor.

Cross-Country Variation in (Binary) Gender Differences in Secondary School Students’ CS Attitudes: Re-Validating and Generalizing a CS Attitudes Scale

The current study compared American, Korean, and Indonesian middle and high school students’ CS attitudes. Concurrently, this study also examined whether the items in the CS attitudes scale exhibit country and gender measurement biases. We gathered data on CS attitudes from middle and high school students in the US, Korea, and Indonesia. The participating students took the same (translated) previously validated CS attitudes scale. We ran a unidimensional IRT, differential item functioning (DIF), a two-way ANOVA, and the Kruskal-Wallis H test. Despite the valid instrument, we found it inappropriate as is for international comparison studies because students from different countries interpreted some items differently. We then compared gender-based differences in CS attitudes across countries. The results revealed no significant differences between males and females in the Indonesian middle school data, whereas male students had significantly higher CS attitudes than female students in both American and Korean student data. Furthermore, we found the same pattern in gender differences in Korean and Indonesian high school students’ CS attitudes scores as in the middle school study. These findings underscore the importance of a country’s sociocultural context in influencing gap and diversity in secondary school students’ CS attitudes.

The validity and IRT psychometric analysis of Chinese version of Difficult Doctor-Patient Relationship Questionnaire (DDPRQ-10)

ObjectiveThe doctor-patient relationship (DPR) plays a crucial role in the Chinese healthcare system, functioning to improve medical quality and reduce medical costs. This study examined the psychometric properties of the Chinese version of the Difficult Doctor-Patient Relationship Questionnaire (DDPRQ-10) among general hospital inpatients in China.MethodsThe research recruited 38 resident doctors responsible for 120 participants, and factor analyses were used to assess the construct validity of the scale. Convergent validity was evaluated by examining the correlation between DDPRQ-10 and depressive symptoms, burnout, and self-efficacy, using the Patient Health Questionnaire Depression Scale-9 item (PHQ-9), and the Maslach Burnout Inventory (MBI). Both multidimensional item response theory (MIRT) and unidimensional item response theory (IRT) frameworks were used to estimate the parameters of each item.ResultsThe Chinese version of DDPRQ-10 showed satisfactory internal consistency (Cronbach's alpha = 0.931), and fitted in a modified two-factor model of positive feelings and negative feelings (χ2/df = 1.494, GFI = 0.925, RMSEA = 0.071, SRMR = 0.008, CFI = 0.985, NFI = 0.958, NNFI = 0.980, TLI = 0.980, IFI = 0.986). Significant correlations with PHQ-9 with DDPRQ-10 and both subscales were revealed (r = 0.293 ~ 0.333, p < .001), while DDPRQ-10 score also significantly correlated with doctors’ MBI score (r = -0.467, p < .001). The MIRT model of full scale and IRT models of both subscales showed high discrimination of all items (a = 2.30 ~ 10.18), and the test information within the range of low-quality relationship was relatively high.ConclusionThe Chinese version of DDPRQ-10 displayed satisfactory reliability and validity and thus was appropriate for measuring the DPR in Chinese medical settings.

A 13-item Health of the Nation Outcome Scale (HoNOS-13): validation by item response theory (IRT) in patients with substance use disorder

BackgroundThe Health of the Nation Outcome Scale (HoNOS) is a widely used 12-item tool to assess mental health and social functioning. The French version has an added 13th item measuring adherence to psychotropic medication. The aim of the current study is to uncover the unknown pattern of the new item 13 and to compare the unidimensional and multidimensional fit of the new HoNOS-13 using Item Response Theory (IRT). This research question was studied among inpatients with substance use disorder (SUD).MethodsSix hundred and nine valid questionnaires of HoNOS-13 were analyzed using unidimensional (one-factor) and multidimensional (two-factor) IRT modeling.ResultsThe multidimensional model suggesting a first factor capturing psychiatric/impairment-related issues and a second factor reflecting social-related issues yielded better goodness-of-fit values compared to the unidimensional solution. This resulted in an improvement of all slope parameters which in turn translates to better discriminative power. Significant improvement in item location parameters were observed as well. The new item 13 had a good discriminative power (1.17) and covered a wide range of the latent trait (− 0.14 to 2.64).ConclusionsWe were able to validate the 13-item questionnaire including medication compliance and suggest that the HoNOS-13 can be recommended as a clinical evaluation tool to assess the problems and treatment needs for inpatients with SUD. Interestingly, the majority of item response categories are endorsed by respondents who are below and above the average levels of HoNOS. This indicates that the scale is able to discriminate between participants both at the low and at the high ends of the latent trait continuum. More importantly, the new item 13 has a good discriminative power and covers a broad range of the latent trait below and above the mean. It therefore has the desired profile of a good item and is a useful measure for the assessment of mental health and social functioning.Trial registration ClinicalTrials.gov, Identifier: NCT03551301. Registered: 11.06.2018. Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03551301.

Measuring PROMIS pain interference in German patients with chronic conditions: calibration, validation, and cross-cultural use of item parameters

PurposeTo calibrate the item parameters of the German PROMIS® Pain interference (PROMIS PI) items using an item-response theory (IRT) model and investigate psychometric properties of the item bank.MethodsForty items of the PROMIS PI item bank were collected in a convenience sample of 660 patients, which were recruited during inpatient rheumatological treatment or outpatient psychosomatic medicine visits in Germany. Unidimensionality, monotonicity, and local independence were tested as required for IRT analyses. Unidimensionality was examined using confirmatory factor analyses (CFA) and exploratory factor analysis (EFA). Unidimensional and bifactor graded-response IRT models were fitted to the data. Bifactor indices were used to investigate whether multidimensionality would lead to biased scores. To evaluate convergent and discriminant validity, the item bank was correlated with legacy pain instruments. Potential differential item functioning (DIF) was examined for gender, age, and subsample. To investigate whether U.S. item parameters may be used to derive T-scores in German patients, T-scores based on previously published U.S. and newly estimated German item parameters were compared with each other after adjusting for sample specific differences.ResultsAll items were sufficiently unidimensional, locally independent, and monotonic. Whereas the fit of the unidimensional IRT model was not acceptable, a bifactor IRT model demonstrated acceptable fit. Explained common variance and Omega hierarchical suggested that using the unidimensional model would not lead to biased scores. One item demonstrated DIF between subsamples. High correlations with legacy pain instruments supported construct validity of the item bank. T-scores based on U.S. and German item parameters were similar suggesting that U.S. parameters could be used in German samples.ConclusionThe German PROMIS PI item bank proved to be a clinically valid and precise instrument for assessing pain interference in patients with chronic conditions.

An Attempt to Measure and Model Women’s Attitudes to Saving for Retirement

Abstract Research background Because of the convergence of demographic, political, and economic trends, retirement has become a significant stage of human life, which currently requires thoughtful and careful planning. Therefore, social pension schemes – a type of system under which the benefits are being provided – and women’s individual saving decisions should give consideration to the fact that it is necessary to accumulate additional funds which should be sufficient for several decades after retirement. Purpose Social pension schemes are widely discussed in all European countries, and in this context we can pose the following question: What is it exactly that makes women save for retirement? This paper has two objectives: to identify the factors that encourage women to save and to measure these factors and develop a model which shows correlations. Research methodology A questionnaire survey was used for collecting the primary data. Subsequently, the analysis is based on 4 indexes created for the purposes of this paper. Then, the indexes were estimated on the basis of the unidimensional two-parameter IRT model, rho and CR coefficients, and multiple-group logistic regression analysis. Novelty The conducted calculations lead to the conclusion that regardless of age, several factors are statistically significant for the whole analysed group, e.g. a place of residence. This is the first paper that shows determinants important for women when it comes to saving for retirement.

A Comparison of Response Time Threshold Scoring Procedures in Mitigating Bias From Rapid Guessing Behavior

Rapid guessing (RG) is a form of non-effortful responding that is characterized by short response latencies. This construct-irrelevant behavior has been shown in previous research to bias inferences concerning measurement properties and scores. To mitigate these deleterious effects, a number of response time threshold scoring procedures have been proposed, which recode RG responses (e.g., treat them as incorrect or missing, or impute probable values) and then estimate parameters for the recoded dataset using a unidimensional or multidimensional IRT model. To date, there have been limited attempts to compare these methods under the possibility that RG may be misclassified in practice. To address this shortcoming, the present simulation study compared item and ability parameter recovery for four scoring procedures by manipulating sample size, the linear relationship between RG propensity and ability, the percentage of RG responses, and the type and rate of RG misclassifications. Results demonstrated two general trends. First, across all conditions, treating RG responses as incorrect produced the largest degree of combined systematic and random error (larger than ignoring RG). Second, the remaining scoring approaches generally provided equal accuracy in parameter recovery when RG was perfectly identified; however, the multidimensional IRT approach was susceptible to increased error as misclassification rates grew. Overall, the findings suggest that recoding RG as missing and employing a unidimensional IRT model is a promising approach.

Physical performance tasks were linked to the PROMIS physical function metric in patients undergoing hemodialysis

ObjectivesTo investigate whether a multi-item performance outcome measure, the physical performance test (PPT), can be calibrated to a common scale with patient-reported outcome measures, using the Patient-Reported Outcomes Measurement Information System (PROMIS) physical function (PF) metric. Study Design and SettingWe analyzed baseline data (N = 1,113) from the CONVINCE study, an international trial in end-stage kidney disease patients comparing high-dose hemodiafiltration with high-flux hemodialysis. Assumptions of item response theory (IRT) modelling were investigated for the combined set of the nine-item PPT and a four-item PROMIS PF short form (PROMIS-PF4a). We applied unidimensional IRT linking for calibrating the PPT to the PROMIS PF metric. ResultsAlthough some evidence for multidimensionality was found, classical test statistics (Cronbach's Alpha = 0.93), Mokken (Loevinger's H = 0.50), and bifactor analysis (explained common variance = 0.65) indicated that PPT and PROMIS-PF4a items can be used to assess a common PF construct. On the group level, the agreement between PROMIS-PF4a and linked PPT scores was stable across several subsamples. On the individual level, scores differed considerably. ConclusionWe found preliminary evidence that the PPT can be linked to the PROMIS PF metric in hemodialysis patients, enabling group comparisons across patient-reported outcome and performance outcome measures. Alternative linking methods should be applied in future studies using a more comprehensive PROMIS PF item set.

Item Response Theory Models for Difference-in-Difference Estimates (and Whether They Are Worth the Trouble)

When randomized control trials are not possible, quasi-experimental methods often represent the gold standard. One quasi-experimental method is difference-in-difference (DiD), which compares changes in outcomes before and after treatment across groups to estimate a causal effect. DiD researchers often use fairly exhaustive robustness checks to make sure the assumptions of the DiD are met. However, less thought is often put into the approach to score item responses from the outcome measure used. For example, surveys are often scored by adding up the item responses to produce sum scores, and achievement tests often rely on scores produced by test vendors, which frequently employ a unidimensional item response theory (IRT) scoring model that implicitly assumes control and treatment participants are exchangeable (i.e., that they come from the same distribution). In this study, several IRT models that parallel the DiD design in terms of groups and timepoints are presented, and their performance is examined. Results indicate that using a scoring approach that parallels the DiD study design reduces bias and improves power, though these approaches can also lead to increased Type I error rates.

The Chinese version of patient-doctor-relationship questionnaire (PDRQ-9): Factor structure, validation, and IRT psychometric analysis.

The patient-doctor relationship has been considered as a crucial concept in primary healthcare, while the medical reform launched by the Chinese government in 2009 has brought significant changes to the healthcare system, which made it urgent to introduce reliable measurement instruments for assessing today's doctor-patient relationship in China. This study examined the psychometric properties of the Chinese version of the Patient-Doctor-Relationship Questionnaire-9 item (PDRQ-9) scale among general hospital inpatients in China. A total of 203 participants responded to the survey, of which 39 completed retest after 7 days. Factor analyses were used to test the construct validity of the scale. Convergent validity was evaluated by the correlation between PDRQ-9 and depressive symptoms measured using PHQ-9 (Patient Health Questionnaire Depression Scale-9 item). Both multidimensional item response theory (MIRT) and unidimensional item response theory (IRT) framework were used to estimate the parameters of each item. The two-factor model of relationship quality and treatment quality was supported (χ2/df = 1.494, GFI = 0.925, RMSEA = 0.071, RMR = 0.008, CFI = 0.985, NFI = 0.958, NNFI = 0.980, TLI = 0.980, IFI = 0.986). The PDRQ-9 and both subscales showed significant correlation with PHQ-9 (r = -0.196∼-0.309) and good internal consistency (Cronbach's alpha = 0.865∼0.933). ANCOVA analysis adjusted with age revealed significant difference in PDRQ-9 ratings between patients with or without significant depressive symptoms (P = 0.019). The 7-day test-retest reliability of the scale was 0.730. The MIRT model of full scale and IRT models of both subscales showed high discrimination of all items (a = 2.46∼38.46), and the test information within the range of low-quality relationship was relatively high. The Chinese version of PDRQ-9 is a valid and reliable rating scale, which can measure the doctor-patient relationship among Chinese patients.

이요인 모형 기반 혼합형 검사를 위한 다차원 IRT 척도 연계 방법

Like unidimensional item response theory (IRT) models, bifactor models in multidimensional IRT have a scale indeterminacy problem, and due to this problem scale linking methods are needed to place all bifactor model parameter estimates from separate calibrations on a common ability scale. Four bifactor scale linking methods including the direct least squares (DLS), mean/least squares (MLS), item category response function (ICRF), and test response function (TRF) methods have been presented for use with single-format tests. Parallel to the 2006 paper of Kim and Lee, this paper extends the four scale linking methods to a mixture of bifactor models for mixed-format tests. Each linking method extended is intended to handle mixed-format tests using any mixture of the following bifactor extensions of four unidimensional IRT models: the bifactor three-parameter logistic, bifactor graded response, bifactor generalized partial credit, and bifactor nominal response models. For generality, symmetric criterion functions are proposed for the ICRF and TRF methods. Given two sets of parameter estimates for the common items linking two test forms, each linking method estimates the dilation (slope) and translation (intercept) coefficients of a linear transformation. Simulations are conducted to investigate the performance of the four linking methods. The results indicate that overall, the ICRF method performs very well, the MLS and DLS methods perform well (the MLS method is slightly better than the DLS method), and the TRF method performs poorly in estimating the linking coefficients. The inferiority of the TRF method is mainly due to its poor estimation of the translation coefficients.

Digital Module 29: Multidimensional Item Response Theory Equating

AbstractIn this digital ITEMS module, Dr. Stella Kim provides an overview of multidimensional item response theory (MIRT) equating. Traditional unidimensional item response theory (IRT) equating methods impose the sometimes untenable restriction on data that only a single ability is assessed. This module discusses potential sources of multidimensionality and presents potential consequences of multidimensionality on equating. To remedy these effects, MIRT equating can be used as a viable alternative to traditional methods of IRT equating. In conducting MIRT equating, the choice of an appropriate MIRT model is necessary, and thus the module describes several existing MIRT models and illustrates each using hypothetical examples. After a brief description of MIRT models, an extensive review of the current literature is presented to identify gaps in the literature on MIRT equating. Then, the steps for conducting MIRT observed‐score equating are described. Finally, the module discusses practical considerations in applying MIRT equating to testing practices and suggests potential areas of research for future studies.

Multidimensional item response theory to assess psychometric properties of GHQ-12 in parents of school children

Introduction: The multidimensional item response theory (MIRT) model provides an ideal foundation for assessing the psychological properties of a questionnaire designed with multidimensional structure. This study aimed to present the first use of MIRT models to investigate the psychometric properties of general health questionnaire (GHQ-12) in parents of school-aged children.&#x0D; Methods: A total of 1104 parents of school children-aged completed the Persian version of GHQ-12 questionnaire. One-dimensional IRT model and MIRT models with two and three factors were used to model the observed scores for each of the GHQ-12 items as a function of the subject's latent characteristics to consider the correlation between the dimensions of the questionnaire. Goodness of fit indices were reported for the three models, and the fits of items were assessed for the best model. Individual items were described in detail through item characteristic curves, and the amount of information carried by different items was presented using information curves.&#x0D; Results: The MIRT analysis with three factors corresponding with anxiety depression, social dysfunction and loss of confidence provided the best account of the GHQ-12 data. The model showed that all items were fitted adequately. Items varied in their discrimination ranged from 0.94 to 2.13, 1.31 to 2.74, and 2.87 to 3.57 for social dysfunction, anxiety depression, and loss of confidence, respectively. Moreover, items 8 and 2 provided the least information in social dysfunction and anxiety depression dimensions, respectively. Items in the loss of confidence dimension carried the most information among all items of the GHQ-12.&#x0D; Conclusion: The developed framework for evaluating the psychometric properties of GHQ-12 can be a suitable alternative to traditional approaches as well as unidimensional IRT models, the use of which has been restricted due to the multidimensional structure of the questionnaire.

Application of longitudinal item response theory models to modeling Parkinson's disease progression.

The Movement Disorder Society revised version of the Unified Parkinson’s Disease Rating Scale (MDS‐UPDRS) parts 2 and 3 reflect patient‐reported functional impact and clinician‐reported severity of motor signs of Parkinson’s disease (PD), respectively. Total scores are common clinical outcomes but may obscure important time‐based changes in items. We aim to analyze longitudinal disease progression based on MDS‐UPRDS parts 2 and 3 item‐level responses over time and as functions of Hoehn & Yahr (H&Y) stages 1 and 2 for subjects with early PD. The longitudinal item response theory (IRT) modeling is a novel statistical method addressing limitations in traditional linear regression approaches, such as ignoring varying item sensitivities and the sum score balancing out improvements and declines. We utilized a harmonized dataset consisting of six studies with 3573 subjects with early PD and 14,904 visits, and mean follow‐up time of 2.5 years (±1.57). We applied both a unidimensional (each part separately) and multidimensional (both parts combined) longitudinal IRT models. We assessed the progression rates for both parts, anchored to baseline H&Y stages 1 and 2. Both the uni‐ and multidimensional longitudinal IRT models indicate significant worsening time effects in both parts 2 and 3. Baseline H&Y stage 2 was associated with significantly higher baseline severities, but slower progression rates in both parts, as compared with stage 1. Patients with baseline H&Y stage 1 demonstrated slower progression in part 2 severity compared to part 3, whereas patients with baseline H&Y stage 2 progressed faster in part 2 than part 3. The multidimensional model had a superior fit compared to the unidimensional models and it had excellent model performance.

Dissecting the Domains of Parkinson's Disease: Insights from Longitudinal Item Response Theory Modeling.

Longitudinal item response theory (IRT) models previously suggested that the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor examination has two salient domains, tremor and nontremor, that progress in time and in response to treatment differently. Apply longitudinal IRT modeling, separating tremor and nontremor domains, to reanalyze outcomes in the previously published clinical trial (Study of Urate Elevation in Parkinson's Disease, Phase 3) that showed no overall treatment effects. We applied unidimensional and multidimensional longitudinal IRT models to MDS-UPDRS motor examination items in 298 participants with Parkinson's disease from the Study of Urate Elevation in Parkinson's Disease, Phase 3 (placebo vs. inosine) study. We separated 10 tremor items from 23 nontremor items and used Bayesian inference to estimate progression rates and sensitivity to treatment in overall motor severity and tremor and nontremor domains. The progression rate was faster in the tremor domain than the nontremor domain before levodopa treatment. Inosine treatment had no effect on either domain relative to placebo. Levodopa treatment was associated with greater slowing of progression in the tremor domain than the nontremor domain regardless of inosine exposure. Linear patterns of progression were observed. Despite different domain-specific progression patterns, tremor and nontremor severities at baseline and over time were significantly correlated. Longitudinal IRT analysis is a novel statistical method addressing limitations of traditional linear regression approaches. It is particularly useful because it can simultaneously monitor changes in different, but related, domains over time and in response to treatment interventions. We suggest that in neurological diseases with distinct impairment domains, clinical or anatomical, this application may identify patterns of change unappreciated by standard statistical methods. © 2022 International Parkinson and Movement Disorder Society.

Diagnostic Classification Models for a Mixture of Ordered and Non-ordered Response Options in Rating Scales.

When developing ordinal rating scales, we may include potentially unordered response options such as “Neither Agree nor Disagree,” “Neutral,” “Don’t Know,” “No Opinion,” or “Hard to Say.” To handle responses to a mixture of ordered and unordered options, Huggins-Manley et al. (2018) proposed a class of semi-ordered models under the unidimensional item response theory framework. This study extends the concept of semi-ordered models into the area of diagnostic classification models. Specifically, we propose a flexible framework of semi-ordered DCMs that accommodates most earlier DCMs and allows for analyzing the relationship between those potentially unordered responses and the measured traits. Results from an operational study and two simulation studies show that the proposed framework can incorporate both ordered and non-ordered responses into the estimation of the latent traits and thus provide useful information about both the items and the respondents.