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Relevant bibliographies by topics / Item response theory – Statistical methods

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Academic literature on the topic 'Item response theory – Statistical methods'

Author: Grafiati

Published: 4 June 2021

Last updated: 2 February 2022

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Journal articles on the topic "Item response theory – Statistical methods"

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Ibrahim, Abdul Wahab. "The Applicability of Item Response Theory Based Statistics to Detect Differential Item Functioning in Polytomous Tests." Randwick International of Education and Linguistics Science Journal 1, no. 1 (June 23, 2020): 1–13. http://dx.doi.org/10.47175/rielsj.v1i1.23.

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The study used statistical procedures based on Item Response Theory to detect Differential Item Functioning (DIF) in polytomous tests. These were with a view to improving the quality of test items construction. The sample consisted of an intact class of 513 Part 3 undergraduate students who registered for the course EDU 304: Tests and Measurement at Sule Lamido University during 2017/2018 Second Semester. A self-developed polytomous research instrument was used to collect data. Data collected were analysed using Generalized Mantel Haenszel, Simultaneous Item Bias Test, and Logistic Discriminant Function Analysis. The results showed that there was no significant relationship between the proportions of test items that function differentially in the polytomous test when the different statistical methods are used. Further, the three parametric and non-parametric methods complement each other in their ability to detect DIF in the polytomous test format as all of them have capacity to detect DIF but perform differently. The study concluded that there was a high degree of correspondence between the three procedures in their ability to detect DIF in polytomous tests. It was recommended that test experts and developers should consider using procedure based on Item Response Theory in DIF detection.

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Veilleux, Jennifer C., and Kate M. Chapman. "Development of a Research Methods and Statistics Concept Inventory." Teaching of Psychology 44, no. 3 (May 30, 2017): 203–11. http://dx.doi.org/10.1177/0098628317711287.

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Research methods and statistics are core courses in the undergraduate psychology major. To assess learning outcomes, it would be useful to have a measure that assesses research methods and statistical literacy beyond course grades. In two studies, we developed and provided initial validation results for a research methods and statistical knowledge concept inventory for eventual use in further scholarship of teaching and learning. In Study 1, we created vignettes and administered open-ended questions to psychology subject pool students. In Study 2, we refined the vignettes and created multiple-choice items using participant responses from Study 1. After administering the measure to psychology subject pool students and a community-based sample of Amazon Mechanical Turk workers, we used item response theory to select 20 items to compose the final Psychological Research Inventory of Concepts.

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Fergadiotis, Gerasimos, Stacey Kellough, and William D. Hula. "Item Response Theory Modeling of the Philadelphia Naming Test." Journal of Speech, Language, and Hearing Research 58, no. 3 (June 2015): 865–77. http://dx.doi.org/10.1044/2015_jslhr-l-14-0249.

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Purpose In this study, we investigated the fit of the Philadelphia Naming Test (PNT; Roach, Schwartz, Martin, Grewal, & Brecher, 1996) to an item-response-theory measurement model, estimated the precision of the resulting scores and item parameters, and provided a theoretical rationale for the interpretation of PNT overall scores by relating explanatory variables to item difficulty. This article describes the statistical model underlying the computer adaptive PNT presented in a companion article (Hula, Kellough, & Fergadiotis, 2015). Method Using archival data, we evaluated the fit of the PNT to 1- and 2-parameter logistic models and examined the precision of the resulting parameter estimates. We regressed the item difficulty estimates on three predictor variables: word length, age of acquisition, and contextual diversity. Results The 2-parameter logistic model demonstrated marginally better fit, but the fit of the 1-parameter logistic model was adequate. Precision was excellent for both person ability and item difficulty estimates. Word length, age of acquisition, and contextual diversity all independently contributed to variance in item difficulty. Conclusions Item-response-theory methods can be productively used to analyze and quantify anomia severity in aphasia. Regression of item difficulty on lexical variables supported the validity of the PNT and interpretation of anomia severity scores in the context of current word-finding models.

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Blanchin, Myriam, Alice Guilleux, Jean-Benoit Hardouin, and Véronique Sébille. "Comparison of structural equation modelling, item response theory and Rasch measurement theory-based methods for response shift detection at item level: A simulation study." Statistical Methods in Medical Research 29, no. 4 (October 30, 2019): 1015–29. http://dx.doi.org/10.1177/0962280219884574.

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When assessing change in patient-reported outcomes, the meaning in patients’ self-evaluations of the target construct is likely to change over time. Therefore, methods evaluating longitudinal measurement non-invariance or response shift at item-level were proposed, based on structural equation modelling or on item response theory. Methods coming from Rasch measurement theory could also be valuable. The lack of evaluation of these approaches prevents determining the best strategy to adopt. A simulation study was performed to compare and evaluate the performance of structural equation modelling, item response theory and Rasch measurement theory approaches for item-level response shift detection. Performances of these three methods in different situations were evaluated with the rate of false detection of response shift (when response shift was not simulated) and the rate of correct response shift detection (when response shift was simulated). The Rasch measurement theory-based method performs better than the structural equation modelling and item response theory-based methods when recalibration was simulated. Consequently, the Rasch measurement theory-based approach should be preferred for studies investigating only recalibration response shift at item-level. For structural equation modelling and item response theory, the low rates of reprioritization detection raise issues on the potential different meaning and interpretation of reprioritization at item-level.

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Dardick, William R., and Brandi A. Weiss. "An Investigation of Chi-Square and Entropy Based Methods of Item-Fit Using Item Level Contamination in Item Response Theory." Journal of Modern Applied Statistical Methods 18, no. 2 (October 2, 2020): 2–43. http://dx.doi.org/10.22237/jmasm/1604190480.

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New variants of entropy as measures of item-fit in item response theory are investigated. Monte Carlo simulation(s) examine aberrant conditions of item-level misfit to evaluate relative (compare EMRj, X2, G2, S-X2, and PV-Q1) and absolute (Type I error and empirical power) performance. EMRj has utility in discovering misfit.

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Abdelhamid, Gomaa Said Mohamed, Marwa Gomaa Abdelghani Bassiouni, and Juana Gómez-Benito. "Assessing Cognitive Abilities Using the WAIS-IV: An Item Response Theory Approach." International Journal of Environmental Research and Public Health 18, no. 13 (June 25, 2021): 6835. http://dx.doi.org/10.3390/ijerph18136835.

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Background: The Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) has been adapted to 28 different cultures and there has been considerable interest in examining its structure through exploratory and confirmatory factor analysis. This study investigates item and scale properties of the Egyptian WAIS-IV using item response theory (IRT) models. Methods: The sample consisted of 250 adults from Egypt. The item-level and subtest statistical properties of the Egyptian WAIS-IV were established using a combination of four dichotomous IRT models and four polytomous IRT models. In addition, factor analysis was performed to investigate the dimensionality of each subtest. Results: Factor analysis indicated the unidimensionality of each subtest. Among IRT models, the two-parameter logistic model provided a good fit for dichotomous subtests, while the graded response model fitted the polytomous data. Most items of the Egyptian WAIS-IV showed high discrimination, and the scale was adequately informative across the levels of latent traits (i.e., cognitive variables). However, each subtest included at least some items with limited ability to distinguish between individuals with differing levels of the cognitive variable being measured. Furthermore, most subtests have items that do not follow the difficulty rank they are ascribed in the WAIS-IV manual. Conclusions: Overall, the results suggest that the Egyptian WAIS-IV offers a highly valid assessment of intellectual abilities, despite the need for some improvements.

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Lisova, Tetiana V. "МЕТОДИ ТА ПРОГРАМНІ ЗАСОБИ ДОСЛІДЖЕННЯ ВАЛІДНОСТІ ТЕСТОВИХ РЕЗУЛЬТАТІВ ДЛЯ ГРУП ТЕСТОВАНИХ З ПЕВНИМИ ІНДИВІДУАЛЬНИМИ ОСОБЛИВОСТЯМИ." Information Technologies and Learning Tools 50, no. 6 (January 1, 2016): 165. http://dx.doi.org/10.33407/itlt.v50i6.1283.

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The necessary condition for the presence of biased assessment by some test is differential item functioning in different groups of test takers. The ideas of some statistical methods for detecting Differential Item Functioning are described in the given article. They were developed in the framework of the main approaches to modeling test results: using contingency tables, regression models, multidimensional models and models of Item Response Theory. The Mantel-Haenszel procedure, logistic regression method, SIBTEST and Item Response Theory Likelihood Ratio Test are considered. The characteristics of each method and conditions of their application are specified. Overview of existing free software tools implementing these methods is carried out. Comparisons of these methods are conducted on the example of real data. Also notes that it is appropriate to use several methods simultaneously to reduce the risk of false conclusions.

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Et.al, Madeline D. Cabauatan. "Statistical Evaluation of Item Nonresponse Methods Using the World Bank’s 2015 Philippines Enterprise Survey." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (April 11, 2021): 4077–88. http://dx.doi.org/10.17762/turcomat.v12i3.1698.

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The main objective of the study was to evaluate item nonresponse procedures through a simulation study of different nonresponse levels or missing rates. A simulation study was used to explore how each of the response rates performs under a variety of circumstances. It also investigated the performance of procedures suggested for item nonresponse under various conditions and variable trends. The imputation methods considered were the cell mean imputation, random hotdeck, nearest neighbor, and simple regression. These variables are some of the major indicators for measuring productive labor and decent work in the country. For the purpose of this study, the researcher is interested in evaluating methods for imputing missing data for the number of workers and total cost of labor per establishment from the World Bank’s 2015 Enterprise Survey for the Philippines. The performances of the imputation techniques for item nonresponse were evaluated in terms of bias and coefficient of variation for accuracy and precision. Based on the results, the cell-mean imputation was seen to be most appropriate for imputing missing values for the total number of workers and total cost of labor per establishment. Since the study was limited to the variables cited, it is recommended to explore other labor indicators. Moreover, exploring choice of other clustering groups is highly recommended as clustering groups have great effect in the resulting estimates of imputation estimation. It is also recommended to explore other imputation techniques like multiple regression and other parametric models for nonresponse such as the Bayes estimation method. For regression based imputation, since the study is limited only in using the cluster groupings estimation, it is highly recommended to use other possible variables that might be related to the variable of interest to verify the results of this study.

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Liu, Yang, Guanyu Hu, Lei Cao, Xiaojing Wang, and Ming-Hui Chen. "A comparison of Monte Carlo methods for computing marginal likelihoods of item response theory models." Journal of the Korean Statistical Society 48, no. 4 (December 2019): 503–12. http://dx.doi.org/10.1016/j.jkss.2019.04.001.

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Bürkner, Paul-Christian, Niklas Schulte, and Heinz Holling. "On the Statistical and Practical Limitations of Thurstonian IRT Models." Educational and Psychological Measurement 79, no. 5 (February 22, 2019): 827–54. http://dx.doi.org/10.1177/0013164419832063.

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Forced-choice questionnaires have been proposed to avoid common response biases typically associated with rating scale questionnaires. To overcome ipsativity issues of trait scores obtained from classical scoring approaches of forced-choice items, advanced methods from item response theory (IRT) such as the Thurstonian IRT model have been proposed. For convenient model specification, we introduce the thurstonianIRT R package, which uses Mplus, lavaan, and Stan for model estimation. Based on practical considerations, we establish that items within one block need to be equally keyed to achieve similar social desirability, which is essential for creating forced-choice questionnaires that have the potential to resist faking intentions. According to extensive simulations, measuring up to five traits using blocks of only equally keyed items does not yield sufficiently accurate trait scores and inter-trait correlation estimates, neither for frequentist nor for Bayesian estimation methods. As a result, persons’ trait scores remain partially ipsative and, thus, do not allow for valid comparisons between persons. However, we demonstrate that trait scores based on only equally keyed blocks can be improved substantially by measuring a sizable number of traits. More specifically, in our simulations of 30 traits, scores based on only equally keyed blocks were non-ipsative and highly accurate. We conclude that in high-stakes situations where persons are motivated to give fake answers, Thurstonian IRT models should only be applied to tests measuring a sizable number of traits.

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Dissertations / Theses on the topic "Item response theory – Statistical methods"

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Combs, Adam. "Bayesian Model Checking Methods for Dichotomous Item Response Theory and Testlet Models." Bowling Green State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1394808820.

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Kopf, Julia [Verfasser]. "Model-based Recursive Partitioning Meets Item Response Theory. New Statistical Methods for the Detection of Differential Item Functioning and Appropriate Anchor Selection / Julia Kopf." München : Verlag Dr. Hut, 2013. http://d-nb.info/1045988804/34.

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Kopf, Julia [Verfasser], and Carolin [Akademischer Betreuer] Strobl. "Model-based recursive partitioning meets item response theory : new statistical methods for the detection of differential item functioning and appropriate anchor selection / Julia Kopf. Betreuer: Carolin Strobl." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2013. http://d-nb.info/1046503235/34.

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Carter, Nathan T. "APPLICATIONS OF DIFFERENTIAL FUNCTIONING METHODS TO THE GENERALIZED GRADED UNFOLDING MODEL." Bowling Green State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1290885927.

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Ueckert, Sebastian. "Novel Pharmacometric Methods for Design and Analysis of Disease Progression Studies." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-216537.

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With societies aging all around the world, the global burden of degenerative diseases is expected to increase exponentially. From the perspective drug development, degenerative diseases represent an especially challenging class. Clinical trials, in this context often termed disease progression studies, are long, costly, require many individuals, and have low success rates. Therefore, it is crucial to use informative study designs and to analyze efficiently the obtained trial data. The development of novel approaches intended towards facilitating both the design and the analysis of disease progression studies was the aim of this thesis. This aim was pursued in three stages (i) the characterization and extension of pharmacometric software, (ii) the development of new methodology around statistical power, and (iii) the demonstration of application benefits. The optimal design software PopED was extended to simplify the application of optimal design methodology when planning a disease progression study. The performance of non-linear mixed effect estimation algorithms for trial data analysis was evaluated in terms of bias, precision, robustness with respect to initial estimates, and runtime. A novel statistic allowing for explicit optimization of study design for statistical power was derived and found to perform superior to existing methods. Monte-Carlo power studies were accelerated through application of parametric power estimation, delivering full power versus sample size curves from a few hundred Monte-Carlo samples. Optimal design and an explicit optimization for statistical power were applied to the planning of a study in Alzheimer's disease, resulting in a 30% smaller study size when targeting 80% power. The analysis of ADAS-cog score data was improved through application of item response theory, yielding a more exact description of the assessment score, an increased statistical power and an enhanced insight in the assessment properties. In conclusion, this thesis presents novel pharmacometric methods that can help addressing the challenges of designing and planning disease progression studies.

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Jiang, Jing. "Regularization Methods for Detecting Differential Item Functioning:." Thesis, Boston College, 2019. http://hdl.handle.net/2345/bc-ir:108404.

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Thesis advisor: Zhushan Mandy Li
Differential item functioning (DIF) occurs when examinees of equal ability from different groups have different probabilities of correctly responding to certain items. DIF analysis aims to identify potentially biased items to ensure the fairness and equity of instruments, and has become a routine procedure in developing and improving assessments. This study proposed a DIF detection method using regularization techniques, which allows for simultaneous investigation of all items on a test for both uniform and nonuniform DIF. In order to evaluate the performance of the proposed DIF detection models and understand the factors that influence the performance, comprehensive simulation studies and empirical data analyses were conducted. Under various conditions including test length, sample size, sample size ratio, percentage of DIF items, DIF type, and DIF magnitude, the operating characteristics of three kinds of regularized logistic regression models: lasso, elastic net, and adaptive lasso, each characterized by their penalty functions, were examined and compared. Selection of optimal tuning parameter was investigated using two well-known information criteria AIC and BIC, and cross-validation. The results revealed that BIC outperformed other model selection criteria, which not only flagged high-impact DIF items precisely, but also prevented over-identification of DIF items with few false alarms. Among the regularization models, the adaptive lasso model achieved superior performance than the other two models in most conditions. The performance of the regularized DIF detection model using adaptive lasso was then compared to two commonly used DIF detection approaches including the logistic regression method and the likelihood ratio test. The proposed model was applied to analyzing empirical datasets to demonstrate the applicability of the method in real settings
Thesis (PhD) — Boston College, 2019
Submitted to: Boston College. Lynch School of Education
Discipline: Educational Research, Measurement and Evaluation

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Peterson, Jaime Leigh. "Multidimensional item response theory observed score equating methods for mixed-format tests." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/1379.

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The purpose of this study was to build upon the existing MIRT equating literature by introducing a full multidimensional item response theory (MIRT) observed score equating method for mixed-format exams because no such methods currently exist. At this time, the MIRT equating literature is limited to full MIRT observed score equating methods for multiple-choice only exams and Bifactor observed score equating methods for mixed-format exams. Given the high frequency with which mixed-format exams are used and the accumulating evidence that some tests are not purely unidimensional, it was important to present a full MIRT equating method for mixed-format tests. The performance of the full MIRT observed score method was compared with the traditional equipercentile method, and unidimensional IRT (UIRT) observed score method, and Bifactor observed score method. With the Bifactor methods, group-specific factors were defined according to item format or content subdomain. With the full MIRT methods, two- and four-dimensional models were included and correlations between latent abilities were freely estimated or set to zero. All equating procedures were carried out using three end-of-course exams: Chemistry, Spanish Language, and English Language and Composition. For all subjects, two separate datasets were created using pseudo-groups in order to have two separate equating criteria. The specific equating criteria that served as baselines for comparisons with all other methods were the theoretical Identity and the traditional equipercentile procedures. Several important conclusions were made. In general, the multidimensional methods were found to perform better for datasets that evidenced more multidimensionality, whereas unidimensional methods worked better for unidimensional datasets. In addition, the scale on which scores are reported influenced the comparative conclusions made among the studied methods. For performance classifications, which are most important to examinees, there typically were not large discrepancies among the UIRT, Bifactor, and full MIRT methods. However, this study was limited by its sole reliance on real data which was not very multidimensional and for which the true equating relationship was not known. Therefore, plans for improvements, including the addition of a simulation study to introduce a variety of dimensional data structures, are also discussed.

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Morse, Brendan J. "Controlling Type 1 errors in moderated multiple regression an application of item response theory for applied psychological research /." Ohio : Ohio University, 2009. http://www.ohiolink.edu/etd/view.cgi?ohiou1247063796.

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Choi, Jiwon. "Comparison of MIRT observed score equating methods under the common-item nonequivalent groups design." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6716.

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For equating tests that measure several distinct proficiencies, procedures that reflect the multidimensional structure of the data are needed. Although there exist a few equating procedures developed under the multidimensional item response theory (MIRT) framework, there is a need for further research in this area. Therefore, the primary objectives of this dissertation are to consolidate and expand MIRT observed score equating research with a specific focus on the common-item nonequivalent groups (CINEG) design, which requires scale linking. Content areas and item types are two focal points of dimensionality. This dissertation uses two studies with different data types and comparison criteria to address the research objectives. In general, a comparison between unidimensional item response theory (UIRT) and MIRT methods suggested a better performance of the MIRT methods over UIRT. The simple structure (SS) and full MIRT methods showed more accurate equating results compared to UIRT. In terms of calibration methods, concurrent calibration outperformed separate calibration for all equating methods under most of the studied conditions.

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Chen, Keyu. "A comparison of fixed item parameter calibration methods and reporting score scales in the development of an item pool." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6923.

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The purposes of the study were to compare the relative performances of three fixed item parameter calibration methods (FIPC) in item and ability parameter estimation and to examine how the ability estimates obtained from these different methods affect interpretations using reported scales of different lengths. Through a simulation design, the study was divided into two stages. The first stage was the calibration stage, where the parameters of pretest items were estimated. This stage investigated the accuracy of item parameter estimates and the recovery of the underlying ability distributions for different sample sizes, different numbers of pretest items, and different types of ability distributions under the three-parameter logistic model (3PL). The second stage was the operational stage, where the estimated parameters of the pretest items were put on operational forms and were used to score examinees. The second stage investigated the effect of item parameter estimation had on the ability estimation and reported scores for the new test forms. It was found that the item parameters estimated from the three FIPC methods showed subtle differences, but the results of the DeMars method were closer to those of the separate calibration with linking method than to the FIPC with simple-prior update and FIPC with iterative prior update methods, while the FIPC with simple-prior update and FIPC with iterative prior update methods performed similarly. Regarding the experimental factors that were manipulated in the simulation, the study found that the sample size influenced the estimation of item parameters. The effect of the number of pretest items on estimation of item parameters was strong but ambiguous, likely because the effect was confounded by changes of both the number of the pretest items and the characteristics of the pretest items among the item sets. The effect of ability distributions on estimation of item parameters was not as evident as the effect of the other two factors. After the pretest items were calibrated, the parameter estimates of these items were put into operational use. The abilities of the examinees were then estimated based on the examinees’ response to the existing operational items and the new items (previously called pretest items), of which the item parameters were estimated under different conditions. This study found that there were high correlations between the ability estimates and the true abilities of the examinees when forms containing pretest items calibrated using any of the three FIPC methods. The results suggested that all three FIPC methods were similarly competent in estimating parameters of the items, leading to satisfying determination of the examinees’ abilities. When considering the scale scores, because the estimated abilities were very similar, there were small differences among the scaled scores on the same scale; the relative frequency of examinees classified into performance categories and the classification consistency index also showed the interpretation of reported scores across scales were similar. The study provided a comprehensive comparison on the use of FIPC methods in parameter estimation. It was hoped that this study would help the practitioners choose among the methods according to the needs of the testing programs. When ability estimates were linearly transformed into scale scores, the lengths of scales did not affect the statistical properties of scores, however, they may impact how the scores are subjectively perceived by stakeholders and therefore should be carefully selected.

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Books on the topic "Item response theory – Statistical methods"

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Hutchinson, T. P. Controversies in item response theory. Adelaide, S. Aust: Rumsby Scientific Publishing, 1991.

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Hutchinson, T. P. Controversies in item response theory. Adelaide, S. Aust: Rumsby Scientific Pub., 1991.

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L, Nering Michael, ed. Polytomous item response theory models. Thousand Oaks: Sage Publications, 2006.

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Ostini, Remo. Polytomous item response theory models. Thousand Oaks, CA: Sage Publications, 2005.

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The theory and practice of item response theory. New York: Guildord Press, 2009.

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Fox, Jean-Paul. Bayesian item response modeling: Theory and applications. New York, NY: Springer, 2010.

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Boldt, Robert F. Simulated equating using several item response curves. Princeton, N.J: Educational Testing Service, 1993.

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McLeod, Lori Davis. A Bayesian method for the detection of item preknowledge in CAT. Newtown, PA: Law School Admission Council, 1999.

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Social choice with partial knowledge of treatment response. Princeton, NJ: Princeton University Press, 2006.

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Manski, Charles F. Social choice with partial knowledge of treatment response. Princeton, NJ: Princeton University Press, 2005.

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Book chapters on the topic "Item response theory – Statistical methods"

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Kolen, Michael J., and Robert L. Brennan. "Item Response Theory Methods." In Springer Series in Statistics, 156–209. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4757-2412-7_6.

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Cella, David, Chih-Hung Chang, and Allen W. Heinemann. "Item Response Theory (IRT): Applications in Quality of Life Measurement, Analysis and Interpretation." In Statistical Methods for Quality of Life Studies, 169–85. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3625-0_14.

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Molenaar, Ivo W. "Parametric and Nonparametric Item Response Theory Models in Health Related Quality of Life Measurement." In Statistical Methods for Quality of Life Studies, 143–54. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3625-0_12.

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Fan, Xitao, and Shaojing Sun. "Item Response Theory." In Handbook of Quantitative Methods for Educational Research, 45–67. Rotterdam: SensePublishers, 2013. http://dx.doi.org/10.1007/978-94-6209-404-8_3.

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Kolen, Michael J., and Robert L. Brennan. "Item Response Theory Methods." In Test Equating, Scaling, and Linking, 155–230. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4757-4310-4_6.

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Kolen, Michael J., and Robert L. Brennan. "Item Response Theory Methods." In Test Equating, Scaling, and Linking, 171–245. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0317-7_6.

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Holling, Heinz, and Rainer Schwabe. "Statistical Optimal Design Theory." In Handbook of Item Response Theory, 313–40. Boca Raton, FL: CRC Press, 2015- | Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences.: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/b19166-16.

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Reckase, Mark D. "Statistical Descriptions of Item and Test Functioning." In Multidimensional Item Response Theory, 113–35. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-89976-3_5.

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Rijmen, Frank, Minjeong Jeon, and Sophia Rabe-Hesketh. "Variational Approximation Methods." In Handbook of Item Response Theory, 259–70. Boca Raton, FL: CRC Press, 2015- | Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences.: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/b19166-14.

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Jansen, Margo G. H., and Cees A. W. Glas. "Statistical Tests for Differential Test Functioning in Rasch’s Model for Speed Tests." In Essays on Item Response Theory, 149–62. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0169-1_8.

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Conference papers on the topic "Item response theory – Statistical methods"

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Lo, Shih-Ching, Kuo-Chang Wang, Hsin-Li Chang, George Maroulis, and Theodore E. Simos. "Equal Area Logistic Estimation for Item Response Theory." In COMPUTATIONAL METHODS IN SCIENCE AND ENGINEERING: Advances in Computational Science: Lectures presented at the International Conference on Computational Methods in Sciences and Engineering 2008 (ICCMSE 2008). AIP, 2009. http://dx.doi.org/10.1063/1.3225354.

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Lalor, John, Hao Wu, and hong yu. "Building an Evaluation Scale using Item Response Theory." In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/d16-1062.

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Jianhua, Xiong, and Ding Shuliang. "Model-Based Methods for Test Equating Under Item Response Theory." In 2010 International Conference on E-Business and E-Government (ICEE). IEEE, 2010. http://dx.doi.org/10.1109/icee.2010.1367.

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Wang, Hua, Cuiqin Ma, and Ningning Chen. "A brief review on Item Response Theory models-based parameter estimation methods." In Education (ICCSE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccse.2010.5593443.

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Lalor, John P., Hao Wu, and Hong Yu. "Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds." In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-1434.

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Tong, Shiwei, Qi Liu, Runlong Yu, Wei Huang, Zhenya Huang, Zachary A. Pardos, and Weijie Jiang. "Item Response Ranking for Cognitive Diagnosis." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/241.

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Cognitive diagnosis, a fundamental task in education area, aims at providing an approach to reveal the proficiency level of students on knowledge concepts. Actually, monotonicity is one of the basic conditions in cognitive diagnosis theory, which assumes that student's proficiency is monotonic with the probability of giving the right response to a test item. However, few of previous methods consider the monotonicity during optimization. To this end, we propose Item Response Ranking framework (IRR), aiming at introducing pairwise learning into cognitive diagnosis to well model the monotonicity between item responses. Specifically, we first use an item specific sampling method to sample item responses and construct response pairs based on their partial order, where we propose the two-branch sampling methods to handle the unobserved responses. After that, we use a pairwise objective function to exploit the monotonicity in the pair formulation. In fact, IRR is a general framework which can be applied to most of contemporary cognitive diagnosis models. Extensive experiments demonstrate the effectiveness and interpretability of our method.

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Zakrizevska-Belogrudova, Maija, and Sanita Leimane. "Gamification and Using It in Organisational Consulting." In 14th International Scientific Conference "Rural Environment. Education. Personality. (REEP)". Latvia University of Life Sciences and Technologies. Faculty of Engineering. Institute of Education and Home Economics, 2021. http://dx.doi.org/10.22616/reep.2021.14.054.

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Gamification has been a topical item in education, marketing, human resources management, business, and organisational consulting in the past decade. Nowadays, companies have a wider range of available organisational consultations: organisational supervision is developing, coaching is popular, and there is a wide offer of business training sessions. This study aims to research gamification in organisational consulting, analyse the differences in the opinions regarding the use and availability of gamification in the professional activities of coaches, supervisors and business trainers. The survey developed by the authors of the study consisted of four sets of items (Information about Gamification, Application and Availability of Gamification, Believing Gamification Methods, Team/Group Responsiveness to Gamification) and two additional statements for the purpose of confirming the responses given by the respondents regarding their beliefs in gamification as an effective method and their readiness to use it. The associations related to the game and gamification were also researched. The questionnaire about gamification in the professional activities of supervisors, coaches and business trainers was sent electronically to professionals practising in Latvia. Questionnaires from 85 respondents were received and processed. The results demonstrated no statistically significant differences in the opinions of coaches, supervisors and business trainers regarding the use of gamification in organisational consulting. It was found out that the concept of gamification has not been sufficiently explained and there is still no common understanding regarding it in Latvia. More than half or 55 % of the 85 respondents in the survey do not know where to acquire gamification. At the same time, 91 % of the respondents in the survey specify that they are willing to acquire the methods of gamification. The authors of the study believe that it is important to proceed with the research in organisations to find out the experience of the organisations in gamification and to develop gamification training programmes for the organisations.

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Shergadwala, Murtuza, Karthik N. Kannan, and Jitesh H. Panchal. "Understanding the Impact of Expertise on Design Outcome: An Approach Based on Concept Inventories and Item Response Theory." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59038.

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Research on expertise in design has focused primarily on understanding expert-novice differences. Although it is well established that experts perform better than novices, there is a lack of formal methods to quantify the potential impact of expertise on the quality of design outcomes. The research question addressed in this paper is: How can the impact of expertise on the quality of design solutions be quantified? Quantifying such impacts can be of particular importance in product development, recruitment processes and design competitions. We utilize an approach based on Item Response Theory (IRT) and Concept Inventories (CI) for expertise quantification. We then investigate and validate the impact of expertise on solution quality through a behavioral experiment involving a track design problem. The results highlight the usefulness of the proposed approach and provide a functional relationship between expertise and solution quality. We also observe behavioral differences between participants with varying scores on a test taken in the behavioral experiment. The proposed approach could be used in the future work to quantify learning.

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Omegna, Federica, Gianfranco Genta, Emanuele M. Barini, Daniele L. Marchisio, and Raffaello Levi. "Sensitivity Testing Revisited: The Case of Sol-Gel Transition." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59091.

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Classical sensitivity testing addresses mainly problems where the level of one stimulus only governs an abrupt transition in output, or response. Both parametric and nonparametric methods developed, and successfully applied over last century to tackle such problems, provide estimates of critical levels beyond which an item will either respond, or not, to a single stimulus, and of related statistics. However classical methods sometimes may not readily provide an answer, namely when more than one stimulus may reach critical level, and either singularly or jointly trigger transition. Factorial and response surface designs, adequate when dealing with continuous responses, may not perform as well for transition threshold estimation. A practical case at hand in chemical engineering concerns the production, through hydrolysis of a specific precursor, of titania sols and gels that find industrial use as additive for paints, concrete and other building materials due to its optical, photo-catalytic and super-hydrophilic properties. Particles formation and aggregation — controlled by varying the primary process parameters, namely initial alkoxide concentration, water to alkoxide and acid to alkoxide ratios, mixing conditions — may yield either stable, transparent nanometric sols, or monolithic gels, where aggregation of nanometric particles produces a final ceramic object. Depending on the application, one of the two products may be desirable, and therefore it is crucial to control the final product properties. Aggregation kinetics and physical properties of sols, and sol to gel transition, were found to depend strongly upon several factors, that is water to alkoxide initial concentration ratio, acid to alkoxide initial concentration ratio, and their interaction. The approach developed in order to estimate parameters pertaining to transition, and related uncertainty, is presented in the paper, and discussed in the light of experimental results.

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Ghosh, Aritra, and Andrew Lan. "BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/332.

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Computerized adaptive testing (CAT) refers to a form of tests that are personalized to every student/test taker. CAT methods adaptively select the next most informative question/item for each student given their responses to previous questions, effectively reducing test length. Existing CAT methods use item response theory (IRT) models to relate student ability to their responses to questions and static question selection algorithms designed to reduce the ability estimation error as quickly as possible; therefore, these algorithms cannot improve by learning from large-scale student response data. In this paper, we propose BOBCAT, a Bilevel Optimization-Based framework for CAT to directly learn a data-driven question selection algorithm from training data. BOBCAT is agnostic to the underlying student response model and is computationally efficient during the adaptive testing process. Through extensive experiments on five real-world student response datasets, we show that BOBCAT outperforms existing CAT methods (sometimes significantly) at reducing test length.

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