An Evaluation of Fit Indices Used in Model Selection of Dichotomous Mixture IRT Models.

A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's information criterion (DIC), sample size adjusted BIC (SABIC), relative entropy, the integrated classification likelihood criterion (ICL-BIC), the adjusted Lo-Mendell-Rubin (LMR), and Vuong-Lo-Mendell-Rubin (VLMR). The accuracy of the fit indices was assessed for correct detection of the number of latent classes for different simulation conditions including sample size (2,500 and 5,000), test length (15, 30, and 45), mixture proportions (equal and unequal), number of latent classes (2, 3, and 4), and latent class separation (no-separation and small separation).

Sequential Bayesian Ability Estimation Applied to Mixed-Format Item Tests.

Large-scale tests often contain mixed-format items, such as when multiple-choice (MC) items and constructed-response (CR) items are both contained in the same test. Although previous research has analyzed both types of items simultaneously, this may not always provide the best estimate of ability. In this paper, a two-step sequential Bayesian (SB) analytic method under the concept of empirical Bayes is explored for mixed item response models.

Exploring examinees' responses to constructed response items with a supervised topic model.

Textual data are increasingly common in test data as many assessments include constructed response (CR) items as indicators of participants' understanding. The development of techniques based on natural language processing has made it possible for researchers to rapidly analyse large sets of textual data. One family of statistical techniques for this purpose are probabilistic topic models.

The Impact of Sample Size and Various Other Factors on Estimation of Dichotomous Mixture IRT Models.

The purpose of this study was to examine the effects of different data conditions on item parameter recovery and classification accuracy of three dichotomous mixture item response theory (IRT) models: the Mix1PL, Mix2PL, and Mix3PL. Manipulated factors in the simulation included the sample size (11 different sample sizes from 100 to 5000), test length (10, 30, and 50), number of classes (2 and 3), the degree of latent class separation (normal/no separation, small, medium, and large), and class sizes (equal vs. nonequal).

Corrigendum: Integrating a Statistical Topic Model and a Diagnostic Classification Model for Analyzing Items in a Mixed Format Assessment.

[This corrects the article DOI: 10.3389/fpsyg.2020.

Integrating a Statistical Topic Model and a Diagnostic Classification Model for Analyzing Items in a Mixed Format Assessment.

Selected response items and constructed response (CR) items are often found in the same test. Conventional psychometric models for these two types of items typically focus on using the scores for correctness of the responses. Recent research suggests, however, that more information may be available from the CR items than just scores for correctness.

Sample Size Requirements for Applying Diagnostic Classification Models.

Results of a comprehensive simulation study are reported investigating the effects of sample size, test length, number of attributes and base rate of mastery on item parameter recovery and classification accuracy of four DCMs (i.e., C-RUM, DINA, DINO, and LCDMREDUCED).

Pedagogy, Partnership, and Collaboration: A Longitudinal, Empirical Study of Serious Educational Gameplay in Secondary Biology Classrooms.

The use of serious educational games has the potential to increase student learning outcomes in science education by providing students with opportunities to explore phenomena in ways that vary from traditional instruction; yet, empirical research to support this assertion is limited. This study aimed to explore deeply what learning gains were associated with the use of three serious educational games (SEGs) created for use in secondary biology classrooms that partner teachers implemented during a 2-week curriculum unit. This longitudinal, mixed method study includes a control year, in which we examined how six highly qualified teachers taught students ( = 407) a 2-week curriculum unit addressing cellular biology the SEGs, followed by 2 years in which the teachers integrated the SEGs into the curriculum unit with students ( =871).

The Impact of Markov Chain Convergence on Estimation of Mixture IRT Model Parameters.

A nonconverged Markov chain can potentially lead to invalid inferences about model parameters. The purpose of this study was to assess the effect of a nonconverged Markov chain on the estimation of parameters for mixture item response theory models using a Markov chain Monte Carlo algorithm. A simulation study was conducted to investigate the accuracy of model parameters estimated with different degree of convergence.

The Impact of Test and Sample Characteristics on Model Selection and Classification Accuracy in the Multilevel Mixture IRT Model.

The standard item response theory (IRT) model assumption of a single homogenous population may be violated in real data. Mixture extensions of IRT models have been proposed to account for latent heterogeneous populations, but these models are not designed to handle multilevel data structures. Ignoring the multilevel structure is problematic as it results in lower-level units aggregated with higher-level units and yields less accurate results, because of dependencies in the data.

Reliability for Tests With Items Having Different Numbers of Ordered Categories.

This study describes a structural equation modeling (SEM) approach to reliability for tests with items having different numbers of ordered categories. A simulation study is provided to compare the performance of this reliability coefficient, coefficient alpha and population reliability for tests having items with different numbers of ordered categories, a one-factor and a bifactor structures, and different skewness distributions of test scores. Results indicated that the proposed reliability coefficient was close to the population reliability in most conditions.

Priors in Bayesian Estimation under the Rasch Model.

A review of various priors used in Bayesian estimation under the Rasch model is presented together with clear mathematical definitions of the hierarchical prior distributions. A Bayesian estimation method, Gibbs sampling, was compared with conditional, marginal, and joint maximum likelihood estimation methods using the Knox Cube Test data under the Rasch model. The shrinkage effect of the priors on item and ability parameter estimates was also investigated using the Knox Cube Test data.

Model Selection for Multilevel Mixture Rasch Models.

Mixture item response theory (MixIRT) models can sometimes be used to model the heterogeneity among the individuals from different subpopulations, but these models do not account for the multilevel structure that is common in educational and psychological data. Multilevel extensions of the MixIRT models have been proposed to address this shortcoming. Successful applications of multilevel MixIRT models depend in part on detection of the best fitting model.

Use of Information Criteria in the Study of Group Differences in Trace Lines.

A brief review of various information criteria is presented for the detection of differential item functioning (DIF) under item response theory (IRT). An illustration of using information criteria for model selection as well as results with simulated data are presented and contrasted with the IRT likelihood ratio (LR) DIF detection method. Use of information criteria for general IRT model selection is discussed.

NIDA Clinical Trials Network CTN-0051, Extended-Release Naltrexone vs. Buprenorphine for Opioid Treatment (X:BOT): Study design and rationale.

Introduction: For opioid-dependent patients in the US and elsewhere, detoxification and counseling-only aftercare are treatment mainstays. Long-term abstinence is rarely achieved; many patients relapse and overdose after detoxification. Methadone, buprenorphine-naloxone (BUP-NX) and extended-release naltrexone (XR-NTX) can prevent opioid relapse but are underutilized.

A Latent Transition Analysis Model for Assessing Change in Cognitive Skills.

Latent transition analysis (LTA) was initially developed to provide a means of measuring change in dynamic latent variables. In this article, we illustrate the use of a cognitive diagnostic model, the DINA model, as the measurement model in a LTA, thereby demonstrating a means of analyzing change in cognitive skills over time. An example is presented of an instructional treatment on a sample of seventh-grade students in several classrooms in a Midwestern school district.

The Impact of Non-Normality on Extraction of Spurious Latent Classes in Mixture IRT Models.

Unidimensional, item response theory (IRT) models assume a single homogeneous population. Mixture IRT (MixIRT) models can be useful when subpopulations are suspected. The usual MixIRT model is typically estimated assuming a normally distributed latent ability.

Comparing the Two- and Three-Parameter Logistic Models via Likelihood Ratio Tests: A Commonly Misunderstood Problem.

Selection of an appropriate item response model is critical in the measurement of latent examinee ability. The one-, two-, and three-parameter logistic (1PL, 2PL, and 3PL) models are nested, and as such can be compared using likelihood ratio (LR) tests. The null hypothesis in the LR test for selection among the 2PL and 3PL models sets the guessing parameters to their lower bound of 0.

Patient perspectives on buprenorphine/naloxone: a qualitative study of retention during the starting treatment with agonist replacement therapies (START) study.

This study examines the barriers and facilitators of retention among patients receiving buprenorphine/naloxone at eight community-based opioid treatment programs across the United States. Participants (n = 105) were recruited up to three and a half years after having participated in a randomized clinical trial comparing the effect of buprenorphine/naloxone and methadone on liver function. Semi-structured interviews were conducted with 67 patients provided with buprenorphine/naloxone who had terminated early and 38 patients who had completed at least 24 weeks of the trial.

Detecting intervention effects using a multilevel latent transition analysis with a mixture IRT model.

A multilevel latent transition analysis (LTA) with a mixture IRT measurement model (MixIRTM) is described for investigating the effectiveness of an intervention. The addition of a MixIRTM to the multilevel LTA permits consideration of both potential heterogeneity in students' response to instructional intervention as well as a methodology for assessing stage sequential change over time at both student and teacher levels. Results from an LTA-MixIRTM and multilevel LTA-MixIRTM were compared in the context of an educational intervention study.

Treatment retention among patients randomized to buprenorphine/naloxone compared to methadone in a multi-site trial.

Aims: To examine patient and medication characteristics associated with retention and continued illicit opioid use in methadone (MET) versus buprenorphine/naloxone (BUP) treatment for opioid dependence.

Design, Settings And Participants: This secondary analysis included 1267 opioid-dependent individuals participating in nine opioid treatment programs between 2006 and 2009 and randomized to receive open-label BUP or MET for 24 weeks.

Measurements: The analyses included measures of patient characteristics at baseline (demographics; use of alcohol, cigarettes and illicit drugs; self-rated mental and physical health), medication dose and urine drug screens during treatment, and treatment completion and days in treatment during the 24-week trial.

Buprenorphine/Naloxone and methadone effects on laboratory indices of liver health: a randomized trial.

Background: Buprenorphine/naloxone (BUP) and methadone (MET) are efficacious treatments for opioid dependence, although concerns about a link between BUP and drug-induced hepatitis have been raised. This study compares the effects of BUP and MET on liver health in opioid-dependent participants.

Methods: This was a randomized controlled trial of 1269 opioid-dependent participants seeking treatment at 8 federally licensed opioid treatment programs and followed for up to 32 weeks between May 2006 and August 2010; 731 participants met "evaluable" criteria defined as completing 24 weeks of medication and providing at least 4 blood samples for transaminase testing.