Latent Trait Model Research Articles

Development of an exercise programme for balance abilities in people with multiple sclerosis: a development of concept study using Rasch analysis

BackgroundPeople with multiple sclerosis (PwMS) frequently have impaired balance from an early stage of the disease. Balance difficulties can be divided into categories; although, to date, these lack scientific foundation. Impaired balance in PwMS can be addressed using specific and challenging exercises. Such exercises should provide an optimal challenge point; however, the difficulty of balance exercises is often unknown, making it difficult to target the exercises to an individual’s abilities.The aims of this study were: to develop an exercise programme for PwMS relating the exercises to the balance problem categories; to establish the order of difficulty of exercises in each category and; to evaluate the content and structural validity of the exercise programme.MethodsA “construct map” approach was used to design and develop an exercise programme for PwMS. Potentially relevant balance exercises were identified, then a framework was set up, comprising four dimensions (subsequently reduced to three dimensions) of balance exercises. The relevance, comprehensibility, and comprehensiveness of the exercise programme were rated by 13 physiotherapists, who also linked 19 key exercises to balance categories. A total of 65 PwMS performed the 19 balance exercises, rated their difficulty and commented on the relevance and comprehensibility of each exercise. A Rasch model was used to evaluate the relative difficulty of the exercises. To assess fit of the data to the Rasch model a rating scale model was used, which is a unidimensional latent trait model for polytomous item responses.ResultsEvaluation by the physiotherapists and PwMS indicated that the content validity of the exercise programme was adequate. Rasch analysis showed that the latent trait “balance exercises in PwMS” comprised three subdimensions (“stable BOS”, “sway” and “step and walk”). The 19 balance exercises showed adequate fit to the respective dimensions. The difficulties of the balance exercises were adequate to cover the ability spectrum of the PwMS.ConclusionA balance exercise programme for PwMS comprising three dimensions of balance exercises was developed. Difficulty estimates have been established for each of the exercises, which can be used for targeted balance training. Content and structural validity of the programme was adequate.

Development and Validation of Implicit Measures of Emotional Intelligence Attributes

Emotional intelligence is important for success in a wide range of social and professional roles. Interest in EI has spawned a debate about whether EI should be defined and measured as a set of abilities or as a set of dispositional self-perceptions, the latter being typically assessed with self-report measures that are susceptible to inaccurate self-knowledge and impression management artifacts. This research used Implicit Association Test procedures to develop measures of emotional intelligence and examined their construct validity using a multitrait-multimethod design. The results of confirmatory factor analyses of nested latent trait models provided evidence of convergent and discriminant validity.

The efficacy of measuring judicial ideal points: The mis-analogy of IRTs

IRT models are among the most commonly used latent trait models in all of political science, particularly in the estimation of ideal points of political actors in institutions. While widely used, IRT models are often misapplied, and a key element of their estimation, the item parameters, are almost always ignored and discarded. In this paper, we look into the application of IRT models to the estimation of judicial ideology scores by Martin and Quinn (2002). Building off of a replication and extension of Martin and Quinn (2002), we demonstrate that the often-ignored item parameters are, in fact, inconsistent with the assumptions of IRTs. Then, using a post-estimation fix that is designed to ameliorate the problem, we run the model again, generating new scores. We then compare our new ideal points to the existing ideal points and discuss the implications for both ideal point modeling generally and in judicial politics specifically. We conclude by replicating a prominent study in judicial politics that demonstrates how inconsistencies in the estimation of IRT models can be consequential and bring up concerns with the implications for what this could mean for the usefulness of scores estimated via IRT models.

Open for innovation: An improved measurement approach using item response theory

Drawing on the theoretical foundations of attitudes and their role in the decision process underlying open innovation (OI) adoption, this study conveys a new perspective of examining firm-level openness as a construct. Based on Item Response Theory, a family of latent trait models rooted in psychology, and using data from the German section of the Community Innovation Survey, we advance a nuanced measure of openness capturing the firm-level attitudes toward external knowledge reception, going beyond current measures focusing on its attributed effects. This approach, based on an implicit attitude measure, allows us to assess the types of OI practices characterizing firms with different value structures (i.e., higher/lower attitudes toward external knowledge), thus offering a more reliable comparison of firms along the openness continuum. A systematic comparison with the widely used measures of external search breadth and depth shows that higher openness is not merely reflected by a higher number (or a more intensive use) of external knowledge sources but by a higher attitude toward complex search patterns, typically implying more challenging OI activities. The proposed construct has strong external validity, as it reflects the key theoretical features of openness and its paradoxes - an inverted U-shaped relationship with innovation performance. The results of this study provide both theoretical and practical implications.

Latent trait models for perceived risk assessment using a Covid-19 data survey

Aim of the contribution is analyzing potential events that may negatively impact individuals, assets, and/or the environment, and making judgments about the perceived personal and social riskiness of Covid-19 compared to other hazards belonging to health (AIDS, cancer, infarction), environmental (climate change), behavioral (serious car accidents), and technological (nuclear weapons) domains. The comparative risk analysis has been performed on a survey data collected during the first Italian Covid-19 lockdown. An item response theory model for polytomously scored items has been implemented for the analysis of the positioning of Covid-19 with respect to the other hazards in terms of perceived risk. Among the attributes determining the hazard's perceived risk, Covid-19 distinguishes for the knowledge of risks from the hazard, media attention, and fear caused by the hazard in the peers. Besides, through a latent regression analysis, the role of some individual characteristics on the perceived risk for Covid-19 has been examined. Our contribution allows us to disentangle among several aspects of hazards and describe the main factors affecting the perceived risk. It also contributes to determine if existing control measures are perceived as adequate and the interest for new media with related impact on a person's reaction.

Conflict Resolution Strategies and Marital Adjustment of Heterosexual Couples: Assessment of Actor–Partner Interaction

This study tested a dyadic theoretical model in which conflict resolution strategies have impact on couples’ marital adjustment. The study features a quantitative and transversal approach and a correlational and explanatory design. Participants included 231 heterosexual couples from different regions of Brazil, contacted after indication. The instrument composed of the Conflict Resolution Behavior Questionnaire (CRBQ) and the Revised Dyadic Adjustment Scale (R-DAS) was filled out in the residence of the participants. Data were submitted to dyadic analysis by the latent trait model. The results indicated that the strategies have a strong impact on the individual’s adjustment. Assessing the impact of one of the spouse’s strategies on the other, only the marital adjustment of the men was affected. The evidence suggests differences between husbands and wives regarding the impact of strategies on adjustment. The data are discussed in light of the literature and considering their applicability in the clinical area.

RETRACTED: Simulation of psychological course satisfaction based on android mobile system and neural network

Adolescents usually show a significant reduction in their inner motivation in their careers. Following self-determination theory, the traditional environment meets young people's three basic psychological needs when they mature their needs, namely autonomy, ability, and relevance. It is assumed that it is not enough. Existing systems are difficult-have a process to identify and computational analysis of psychology course scores. The proposed studies are inconsistent and dissatisfied with the online learning experience, combining a Neural Network analysis course level with a satisfying Android-based mobile phone system, or calculating a latent trait model of mental course scores. Course learning, organization, and evaluation: The findings identified three basic, satisfying components. The purpose of Neural Network is to verify and prepare the relationship between process satisfaction and professional identity and trust this relationship's mediating effect. It shows the strongest relationship of satisfaction, teaching psychological process variables, especially quality and expertise. Based on psychological variables, services, facilities, images, and research activities, Android smart systems are also important. Individual user characteristics, such as outcomes and attitudes, are related to psychological user satisfaction. Neural Network promote user matching of suitable thinking style psychology learning, psychological development course education quality and style, be accurate, and develop positive attitudes such as self-efficacy. For learning assistance, help learners will improve their satisfaction, including Android's intelligent system.

More robust local governance suggests positive effects of long‐term community conservation

AbstractCommunity‐based conservation (CBC) is essential to promoting biodiversity protection and livelihood development. Despite significant financial and institutional investment, performance of CBC interventions is mixed, with shortcomings especially evident in wildlife‐based CBC in Africa. CBC outcomes are typically evaluated through household livelihood gains, or through policy analysis at higher administrative levels such as the central state. Surprisingly, village or local governance capacity is often missing from project assessment. Through a controlled study, we evaluate CBC interventions at multiple scales in Tanzania. Employing Bayesian multilevel latent trait models, we find that CBC participation predicts stronger village governance institutions. Additionally, compared to control villages, CBC villages have more local civic organizations and small business enterprise, but do not experience greater elite capture of public goods. Together, and in the absence of direct CBC benefits provisioned to households or signs of success at the higher level of multi‐village CBC bodies, these findings point to the possibility that village‐level governance institutions can adapt in beneficial ways to prolonged CBC interventions.

A Comparison of Limited-Information Test Statistics for a Response Style MIRT Model

An increased use of models for measuring response styles is apparent in recent years with the multidimensional nominal response model (MNRM) as one prominent example. Inclusion of latent constructs representing extreme (ERS) or midpoint response style (MRS) often improves model fit according to information criteria. However, a test of absolute model fit is often not reported even though it could comprise an important piece of validity evidence. Limited information test statistics are candidates for this task, including the full (), ordinal (), and mixed () statistics, which differ in whether additional collapsing of univariate or bivariate contingency tables is conducted. Such collapsing makes sense when item categories are ordinal, which may not hold under the MNRM. More generally, limited information test statistics have gone unevaluated under nominal data and non-ordinal latent trait models. We present a simulation study evaluating the performance of and with the MNRM. Manipulated conditions included sample size, presence and type of response style, and strength of item slopes on substantive and style dimensions. We found that sometimes had inflated Type I error rates, always had little power, and lacked power under some conditions. and may provide complementary and valuable information regarding model fit.

On the structure of ordered latent trait models

Ordered item response models that are in common use can be divided into three groups, cumulative, sequential and adjacent categories model. The derivation and motivation of the models is typically based on the assumed presence of latent traits or underlying process models. In the construction frequently binary models play an important role. The objective of this paper is to give motivations for the models and to clarify the role of the binary models for the various types of ordinal models. It is investigated which binary models are included in an ordinal model but also how the models can be constructed from a sequence of binary models. In all the models one finds a Guttman space structure, which has previously been investigated in particular for the partial credit model. The consideration of the binary models adds to the interpretation of model parameters, which is helpful, in particular, in the case of the partial credit model, for which interpretation is less straightforward than for the other models. A specific topic that is addressed is the ordering of thresholds in the partial credit model because for some researchers reversed ordering is an anomaly, others disagree. It is argued that the ordering of thresholds is not a constitutive element of the partial credit model.

Comparison of Item Difficulty Estimates in a Basic Statistics Test using ltm and CTT Software Packages in R

Two free computer software packages “ltm” and “CTT” in the R software environment were tested to demonstrate its usefulness in an item test analysis. The calibration of the item difficulty parameters given the binary responses of two hundred five examinees for the fifteen items multiple choice test were analyzed using the Classical Test Theory (CTT) and Item Response Theory (IRT) methodologies. The software latent trait model “ltm” employed the IRT framework while the software classical test theory functions “CTT” operated under CTT. The IRT Rasch model was used to model the responses of the examinees. The conditional maximum likelihood estimation method was used to estimate the item difficulty parameters for all the items. On the other hand, all the item difficulty indices using the “CTT” software were also calculated. Both the statistical analyses of this study were done in the R software. Results showed that among the fifteen items, the estimates of their item difficulty parameters differed mostly on their values between the two methods. In an IRT framework, items showed extreme difficulty or easy cases as compared to CTT. However, when the estimated values were categorized into intervals and labelled according to its verbal difficulty description, both methodologies showed some similarities in their item difficulties.

Hello from the Other Side: Can We Perceive Others’ Darkness? Observers’ Accuracy of the Dark Triad

The current study builds on research concerning self-other agreement, specifically the Trait-Reputation-Identity (TRI) Model, and combines this theoretical approach and recent advances from multitrait-multimethod research, specifically the CTC(M-1) and the latent difference model. This combination was applied to avoid statistical problems associated with latent trait models of the type previously used in TRI Model research. A further aim was to fully exploit the TRI Model’s potential by simultaneously modeling more than one trait in one psychometric model. This makes it possible to explore whether raters use similar information to assess different traits or whether this information is observer-specific, as well as whether the traits themselves can shape an individual's Reputation. All analyses were based on a data set capturing the Dark Triad. As the Dark Triad has only rarely been examined from different rater perspectives before, the study also provides new insights into this network of maladaptive traits. A sample of 290 students, their best friends, and one parent were asked to fill out the NPI, Mach IV, and SRP-III. The results suggest that accuracy is high only for narcissism. Moreover, a dark halo could be observed among each of the other-raters for Machiavellianism and psychopathy; target’s standings on these two traits were also underestimated by the other-raters. The study’s combined use of the TRI Model and modern structural equation methods highlights the usefulness of the TRI Model and adds to the debate about the specific nature of Dark Triad traits.

Replicating and extending Martin-Quinn scores

We set to replicate and extend the commonly used Martin and Quinn (2002) scores of judicial ideology for the entire universe of U.S Supreme Court justices from 1793 onwards. Our replication strategy consists of three steps. First, we replicate the constant ideal point scores with a novel variable distinguishing between liberal and conservative case reversals. Using this variable, we show that the replicated scores exhibit a moderate-to-strong correlation with the original scores. Second, we extend the replication of constant ideal points to specific policy areas and show that the variation in latent judicial ideology in the areas of criminal procedure, economics, first amendment and due process strongly predict the overall scores. And third, we replicate and extend dynamic scores to capture the temporal changes in the judicial ideology using repeated sampling Monte Carlo Marko Chain simulation without imposing prior distribution on case-level parameters. To allow for judicial ideology to trend smoothly over time, we employ a large-scale MCMC simulation involving roughly 1.9 billion iterations of the baseline latent judicial trait model, and a filtering parameter to separate the long-run ideology trend from its cyclical component. The replicated dynamic ideal point estimates without prior restrictions generally confirm the trends of dynamic Martin-Quinn scores.

Not Just Generalizability: A Case for Multifaceted Latent Trait Models in Teacher Observation Systems

Teacher evaluation systems often include classroom observations in which raters use rating scales to evaluate teachers’ effectiveness. Recently, researchers have promoted the use of multifaceted approaches to investigating reliability using Generalizability theory, instead of rater reliability statistics. Generalizability theory allows analysts to quantify the contribution of multiple sources of variance (e.g., raters and tasks) to measurement error. We used data from a teacher evaluation system to illustrate another multifaceted approach that provides additional indicators of the quality of observational systems. We show how analysts can use Many-Facet Rasch models to identify and control for differences in rater severity, identify idiosyncratic ratings associated with various facets, and evaluate rating scale functioning. We discuss implications for research and practice in teacher evaluation.

Probing the Internal Validity of the LLAMA Language Aptitude Tests

AbstractOver the past decade, the LLAMA language aptitude test battery has come to play an increasingly important role as an instrument in research on individual differences in language development. However, a potentially serious problem that has been pointed out by several scholars is that the LLAMA has not yet been carefully validated. We addressed this issue by examining the internal validity of this test battery. We collected LLAMA data from 350 participants and assessed these data using classical item analysis, Rasch analysis, and principal component analysis within a framework of best practices in educational and psychological test validation. The results show that only one out of the four subtests (LLAMA B) produced scores that fit a latent trait model with sufficient accuracy. This suggests that researchers using the LLAMA battery must treat their results with appropriate carefulness and also that there is potential for refining the LLAMA further.

A Bayesian approach for individual-level drug benefit-risk assessment.

In existing benefit-risk assessment (BRA) methods, benefit and risk criteria are usually identified and defined separately based on aggregated clinical data and therefore ignore the individual-level differences as well as the association among the criteria. We proposed a Bayesian multicriteria decision-making method for BRA of drugs using individual-level data. We used a multidimensional latent trait model to account for the heterogeneity of treatment effects with latent variables introducing the dependencies among outcomes. We then applied the stochastic multicriteria acceptability analysis approach for BRA incorporating imprecise and heterogeneous patient preference information. We adopted an efficient Markov chain Monte Carlo algorithm when implementing the proposed method. We applied our method to a case study to illustrate how individual-level benefit-risk profiles could inform decision-making.

The Effect of Asymmetry of Item Characteristic Curves on Item Information Function Estimation: A Comparison of RH, 2PL, and 3PL IRT Models through Simulation Study

문항특성곡선의 비대칭성의 존재는 문항특성곡선의 기울기를 변화시킴으로써 문항정보함수 추정에 커다란 영향을 미친다. 이 연구는 문항특성곡선에 비대칭성을 가져오는 요인으로 문항복잡성(item complexity)과 이질적 잔여분산(heteroscedastic residual variance)으로 상정하고, 이 두 가지 특성을 반영한 모의실험 데이터를 분석하였다. 분석에는 비대칭성을 고려하는 확장된 문항반응이론(IRT) 모형인 RH 모형과 기존의 2모수/3모수 IRT 모형을 적용하였으며, 문항/검사정보함수 추정의 정확성을 비교․분석하였다. 문항특성곡선의 비대칭성을 고려하는 RH 모형은 기존의 2모수/3모수 IRT 모형보다 실제 문항정보함수를 전반적으로 더 정확하게 추정하였다. 이러한 결과는 RH 모형처럼 문항특성곡선의 비대칭성을 고려한 확장된 IRT 모형을 활용하는 것이 컴퓨터기반의 적응검사(CAT) 상황에서 문항선택 및 피험자 능력추정의 정확성에 대한 확신을 높일 수 있음을 시사한다.The presence of the asymmetry of the item characteristic curves (ICCs) can substantially affect ICC slopes and thus the estimation of the item information function. This study assumes that item complexity and heteroscedastic residual variance are the critical variables for the asymmetry of ICCs. The current study is comprised of two parts. In the first part, it was compared the results of the RH model against the 2PL/3PL IRT models in terms of estimated item information when a realistic form of asymmetry exists in simulated data sets with a mixture of five response process types that vary in item complexity. The second sets of simulated data were generated from an RH model having five different levels of heteroscedasticity. As a result, the Residual Heteroscedastic Latent Trait (RH) model, which considers the asymmetry of ICCs, more accurately estimates the quantity and maximum point of the actual item information function than the existing 2PL/3PL IRT models. These results suggest that the use of the extended IRT model considering the asymmetry of ICCs, like the RH model, can improve the accuracy of item selection and subject ability estimation in computer-based adaptive testing(CAT) situations.

Characterizing the Manifest Probability Distributions of Three Latent Trait Models for Accuracy and Response Time

In this paper we study the statistical relations between three latent trait models for accuracies and response times: the hierarchical model (HM) of van der Linden (Psychometrika 72(3):287–308, 2007), the signed residual time model (SM) proposed by Maris and van der Maas (Psychometrika 77(4):615–633, 2012), and the drift diffusion model (DM) as proposed by Tuerlinckx and De Boeck (Psychometrika 70(4):629–650, 2005). One important distinction between these models is that the HM and the DM either assume or imply that accuracies and response times are independent given the latent trait variables, while the SM does not. In this paper we investigate the impact of this conditional independence property—or a lack thereof—on the manifest probability distribution for accuracies and response times. We will find that the manifest distributions of the latent trait models share several important features, such as the dependency between accuracy and response time, but we also find important differences, such as in what function of response time is being modeled. Our method for characterizing the manifest probability distributions is related to the Dutch identity (Holland in Psychometrika 55(6):5–18, 1990).

The Effects of Incomplete Rating Designs in Combination With Rater Effects

AbstractResearchers have explored a variety of topics related to identifying and distinguishing among specific types of rater effects, as well as the implications of different types of incomplete data collection designs for rater‐mediated assessments. In this study, we used simulated data to examine the sensitivity of latent trait model indicators of three rater effects (leniency, central tendency, and severity) in combination with different types of incomplete rating designs (systematic links, anchor performances, and spiral). We used the rating scale model and the partial credit model to calculate rater location estimates, standard errors of rater estimates, model–data fit statistics, and the standard deviation of rating scale category thresholds as indicators of rater effects and we explored the sensitivity of these indicators to rater effects under different conditions. Our results suggest that it is possible to detect rater effects when each of the three types of rating designs is used. However, there are differences in the sensitivity of each indicator related to type of rater effect, type of rating design, and the overall proportion of effect raters. We discuss implications for research and practice related to rater‐mediated assessments.

Extracting stability increases the SNP heritability of emotional problems in young people

Twin studies have shown that emotional problems (anxiety and depression) in childhood and adolescence are moderately heritable (~20–50%). In contrast, DNA-based ‘SNP heritability’ estimates are generally <15% and non-significant. One notable feature of emotional problems is that they can be somewhat transient, but the moderate stability seen across time and across raters is predominantly influenced by stable genetic influences. This suggests that by capturing what is in common across time and across raters, we might be more likely to tap into any underlying genetic vulnerability. We therefore hypothesised that a phenotype capturing the pervasive stability of emotional problems would show higher heritability. We fitted single-factor latent trait models using 12 emotional problems measures across ages 7, 12 and 16, rated by parents, teachers and children themselves in the Twins Early Development Study sample. Twin and SNP heritability estimates for stable emotional problems (N = 6110 pairs and 6110 unrelated individuals, respectively) were compared to those for individual measures. Twin heritability increased from 45% on average for individual measures to 76% (se = 0.023) by focusing on stable trait variance. SNP heritability rose from 5% on average (n.s.) to 14% (se = 0.049; p = 0.002). Heritability was also higher for stable within-rater composites. Polygenic scores for both adult anxiety and depression significantly explained variance in stable emotional problems (0.4%; p = 0.0001). The variance explained was more than in most individual measures. Stable emotional problems also showed significant genetic correlation with adult depression and anxiety (average = 52%). These results demonstrate the value of examining stable emotional problems in gene-finding and prediction studies.