scholarly journals Two-Tier Latent Class IRT Models in R

The R Journal ◽  
2016 ◽  
Vol 8 (2) ◽  
pp. 139 ◽  
Author(s):  
Silvia Bacci ◽  
Francesco Bartolucci
Keyword(s):  
Latent Class ◽  
Irt Models

New Evidence on the Construct Validity of the ASI-3 and the Dimensional Conceptualization of Trait Anxiety Sensitivity From IRT Modeling

2017 ◽  
Vol 33 (3) ◽  
pp. 181-189 ◽  
Author(s):  
Christoph J. Kemper ◽  
Michael Hock
Keyword(s):  
Construct Validity ◽  
Anxiety Sensitivity ◽  
Latent Class ◽  
Dimensional Structure ◽  
Sensitivity Index ◽  
Response Scale ◽  
Established Risk Factor ◽  
Irt Models ◽  
Level Data ◽  
Extreme Response

Abstract. Anxiety Sensitivity (AS) denotes the tendency to fear anxiety-related sensations. Trait AS is an established risk factor for anxiety pathology. The Anxiety Sensitivity Index-3 (ASI-3) is a widely used measure of AS and its three most robust dimensions with well-established construct validity. At present, the dimensional conceptualization of AS, and thus, the construct validity of the ASI-3 is challenged. A latent class structure with two distinct and qualitatively different forms, an adaptive form (normative AS) and a maladaptive form (AS taxon, predisposing for anxiety pathology) was postulated. Item Response Theory (IRT) models were applied to item-level data of the ASI-3 in an attempt to replicate previous findings in a large nonclinical sample (N = 2,603) and to examine possible interpretations for the latent discontinuity observed. Two latent classes with a pattern of distinct responses to ASI-3 items were found. However, classes were indicative of participant’s differential use of the response scale (midpoint and extreme response style) rather than differing in AS content (adaptive and maladaptive AS forms). A dimensional structure of AS and the construct validity of the ASI-3 was supported.

Clustering students according to their proficiency: a comparison between different approaches based on item response theory models

2021 ◽  
pp. 43-48
Author(s):  
Rosa Fabbricatore ◽  
Francesco Palumbo
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Clustering Algorithm ◽  
Latent Class ◽  
Latent Class Models ◽  
Response Theory ◽  
Homogeneous Groups ◽  
Final Grade ◽  
Irt Model ◽  
Irt Models

Evaluating learners' competencies is a crucial concern in education, and home and classroom structured tests represent an effective assessment tool. Structured tests consist of sets of items that can refer to several abilities or more than one topic. Several statistical approaches allow evaluating students considering the items in a multidimensional way, accounting for their structure. According to the evaluation's ending aim, the assessment process assigns a final grade to each student or clusters students in homogeneous groups according to their level of mastery and ability. The latter represents a helpful tool for developing tailored recommendations and remediations for each group. At this aim, latent class models represent a reference. In the item response theory (IRT) paradigm, the multidimensional latent class IRT models, releasing both the traditional constraints of unidimensionality and continuous nature of the latent trait, allow to detect sub-populations of homogeneous students according to their proficiency level also accounting for the multidimensional nature of their ability. Moreover, the semi-parametric formulation leads to several advantages in practice: It avoids normality assumptions that may not hold and reduces the computation demanding. This study compares the results of the multidimensional latent class IRT models with those obtained by a two-step procedure, which consists of firstly modeling a multidimensional IRT model to estimate students' ability and then applying a clustering algorithm to classify students accordingly. Regarding the latter, parametric and non-parametric approaches were considered. Data refer to the admission test for the degree course in psychology exploited in 2014 at the University of Naples Federico II. Students involved were N=944, and their ability dimensions were defined according to the domains assessed by the entrance exam, namely Humanities, Reading and Comprehension, Mathematics, Science, and English. In particular, a multidimensional two-parameter logistic IRT model for dichotomously-scored items was considered for students' ability estimation.

scholarly journals A Multilevel Multidimensional Finite Mixture Item Response Model to Cluster Respondents and Countries

2020 ◽  
pp. 1-12
Author(s):  
Martin Kanovský ◽  
Júlia Halamová ◽  
David C. Zuroff ◽  
Nicholas A. Troop ◽  
Paul Gilbert ◽  
...  
Keyword(s):  
Item Response ◽  
Latent Class ◽  
Latent Trait ◽  
Three Dimensional ◽  
Finite Mixture ◽  
Response Model ◽  
Item Response Model ◽  
Irt Models ◽  
Dimensional Measure ◽  
Different Levels

Abstract. The aim of this study was to test the multilevel multidimensional finite mixture item response model of the Forms of Self-Criticising/Attacking and Self-Reassuring Scale (FSCRS) to cluster respondents and countries from 13 samples ( N = 7,714) and from 12 countries. The practical goal was to learn how many discrete classes there are on the level of individuals (i.e., how many cut-offs are to be used) and countries (i.e., the magnitude of similarities and dissimilarities among them). We employed the multilevel multidimensional finite mixture approach which is based on an extended class of multidimensional latent class Item Response Theory (IRT) models. Individuals and countries are partitioned into discrete latent classes with different levels of self-criticism and self-reassurance, taking into account at the same time the multidimensional structure of the construct. This approach was applied to the analysis of the relationships between observed characteristics and latent trait at different levels (individuals and countries), and across different dimensions using the three-dimensional measure of the FSCRS. Results showed that respondents’ scores were dependent on unobserved (latent class) individual and country membership, the multidimensional structure of the instrument, and justified the use of a multilevel multidimensional finite mixture item response model in the comparative psychological assessment of individuals and countries. Latent class analysis of the FSCRS showed that individual participants and countries could be divided into discrete classes. Along with the previous findings that the FSCRS is psychometrically robust we can recommend using the FSCRS for measuring self-criticism.

scholarly journals Measurement of Inter-Individual Variability in Assessing the Quality of Life in Respondents with Celiac Disease

Psych ◽  
2020 ◽  
Vol 2 (4) ◽  
pp. 296-314
Author(s):  
Silvia Bacci ◽  
Daniela Caso ◽  
Rosa Fabbricatore ◽  
Maria Iannario
Keyword(s):  
Quality Of Life ◽  
Social Support ◽  
Celiac Disease ◽  
Latent Class ◽  
Perceived Social Support ◽  
Well Being ◽  
Individual Variability ◽  
Adult Age ◽  
Irt Models

Quality of life of Celiac Disease (CD) patients is affected by constraints in their physical, social and emotional behaviour. Our objective is to assess differences in two relevant dimensions of the Celiac Quality of Life (CQoL) scale, Limitations due to the disease and Dysphoria (i.e., feelings of depression and discomfort), in relation to the perceived social support and some individual and disease-related characteristics. The paper exploits suitable unidimensional Item Response Theory (IRT) models to individually analyse the two mentioned dimensions of the CQoL and Multidimensional Latent Class IRT models for ordinal polytomous items in order to detect sub-populations of CD patients that are homogenous with respect to the perceived CQoL. The latter methods allow to address patients with similar characteristics to the same treatment, performing at the same time a more tailored overture to health promotion programmes. The analysis extracts the relevant patterns and relations among CD patients, disentangling respondents receiving CD diagnosis in adolescence or adult age rather than in childhood (the first perceive high levels of Limitations and Dysphoria), patients with high perceived social support, a factor influencing in a positive way motivation to engage in management of CD-related distress and psychological well-being, and participants who are married or cohabiting. The latter report higher latent trait levels.

scholarly journals Are attitudes toward immigration changing in Europe? An analysis based on latent class IRT models

2021 ◽  
Author(s):  
Ewa Genge ◽  
Francesco Bartolucci
Keyword(s):  
Latent Class ◽  
Temporal Dynamics ◽  
Latent Trait ◽  
European Social Survey ◽  
Host Countries ◽  
Irt Models ◽  
Specific Interpretation ◽  
Changing Attitudes ◽  
Time Varying Covariates ◽  
Attitudes Toward Immigration

AbstractWe analyze the changing attitudes toward immigration in EU host countries in the last few years (2010–2018) on the basis of the European Social Survey data. These data are collected by the administration of a questionnaire made of items concerning different aspects related to the immigration phenomenon. For this analysis, we rely on a latent class approach considering a variety of models that allow for: (1) multidimensionality; (2) discreteness of the latent trait distribution; (3) time-constant and time-varying covariates; and (4) sample weights. Through these models we find latent classes of Europeans with similar levels of immigration acceptance and we study the effect of different socio-economic covariates on the probability of belonging to these classes for which we provide a specific interpretation. In this way we show which countries tend to be more or less positive toward immigration and we analyze the temporal dynamics of the phenomenon under study.

scholarly journals LC and LC-IRT Models in the Identification of Polish Households with Similar Perception of Financial Position

2021 ◽  
Vol 13 (8) ◽  
pp. 4130
Author(s):  
Ewa Genge
Keyword(s):  
Quality Of Life ◽  
Latent Class ◽  
Finite Mixture Models ◽  
Well Being ◽  
Family Type ◽  
Subjective Well Being ◽  
Financial Position ◽  
Irt Models ◽  
Latent Structures

One of the pillars of sustainable development is related to the elimination of poverty and improvement of quality of life. Financial situation of the households plays a crucial role in the subjective well-being, quality of life and overall satisfaction. According to most recent Eurostat data, Poland is one of the countries with the lowest level of subjective material well-being. In this paper we aim to find latent structures of Poles with similar tendency of self-reporting their income position additionally influenced by the socio-economic features and analyze the item characteristics of the questionnaire as well. To address the questions at hand, first we apply the variant of finite mixture models, i.e., latent class (LC) model for data from all, eight waves (2000–2015) of the Polish Household Panel. We are especially focused on the constrained version of the model under IRT parameterization. We compare the results for LC and LC-IRT models and show the influence of the covariates such as family type, socio-economic status and place of living on the probability of belonging to the three identified classes of Polish households, based both on multinomial and global logit parameterization. In this way we can show which types of families tend to be more satisfied with their financial position and those whose members are prone to belong to the worst situated group of Poles. Note that, we present the results for the data including survey weighs, being omitted in most of the studies concerning Polish financial well-being.

scholarly journals A Multilevel Mixture IRT Framework for Modeling Response Times as Predictors or Indicators of Response Engagement in IRT Models

2021 ◽  
pp. 001316442110453
Author(s):  
Gabriel Nagy ◽  
Esther Ulitzsch
Keyword(s):  
Large Scale ◽  
Latent Class ◽  
Response Times ◽  
Marginal Maximum Likelihood ◽  
Irt Model ◽  
Large Scale Data ◽  
Irt Models ◽  
Mixture Irt ◽  
Item Parameters ◽  
Item Responses

Disengaged item responses pose a threat to the validity of the results provided by large-scale assessments. Several procedures for identifying disengaged responses on the basis of observed response times have been suggested, and item response theory (IRT) models for response engagement have been proposed. We outline that response time-based procedures for classifying response engagement and IRT models for response engagement are based on common ideas, and we propose the distinction between independent and dependent latent class IRT models. In all IRT models considered, response engagement is represented by an item-level latent class variable, but the models assume that response times either reflect or predict engagement. We summarize existing IRT models that belong to each group and extend them to increase their flexibility. Furthermore, we propose a flexible multilevel mixture IRT framework in which all IRT models can be estimated by means of marginal maximum likelihood. The framework is based on the widespread Mplus software, thereby making the procedure accessible to a broad audience. The procedures are illustrated on the basis of publicly available large-scale data. Our results show that the different IRT models for response engagement provided slightly different adjustments of item parameters of individuals’ proficiency estimates relative to a conventional IRT model.

Sign in / Sign up

Export Citation Format

Share Document