Generalizability in Item Response Modeling

ERIC Educational Resources Information Center

Briggs, Derek C.; Wilson, Mark

2007-01-01

An approach called generalizability in item response modeling (GIRM) is introduced in this article. The GIRM approach essentially incorporates the sampling model of generalizability theory (GT) into the scaling model of item response theory (IRT) by making distributional assumptions about the relevant measurement facets. By specifying a random…

A Comparison of Linking and Concurrent Calibration under the Graded Response Model.

ERIC Educational Resources Information Center

Kim, Seock-Ho; Cohen, Allan S.

Applications of item response theory to practical testing problems including equating, differential item functioning, and computerized adaptive testing, require that item parameter estimates be placed onto a common metric. In this study, two methods for developing a common metric for the graded response model under item response theory were…

A Semiparametric Model for Jointly Analyzing Response Times and Accuracy in Computerized Testing

ERIC Educational Resources Information Center

Wang, Chun; Fan, Zhewen; Chang, Hua-Hua; Douglas, Jeffrey A.

2013-01-01

The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs mainly focus on parametric models, which have the…

A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means

ERIC Educational Resources Information Center

Polak, Marike; De Rooij, Mark; Heiser, Willem J.

2012-01-01

In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) "criterion…

Using Response Times for Item Selection in Adaptive Testing

ERIC Educational Resources Information Center

van der Linden, Wim J.

2008-01-01

Response times on items can be used to improve item selection in adaptive testing provided that a probabilistic model for their distribution is available. In this research, the author used a hierarchical modeling framework with separate first-level models for the responses and response times and a second-level model for the distribution of the…

Item Response Models for Local Dependence among Multiple Ratings

ERIC Educational Resources Information Center

Wang, Wen-Chung; Su, Chi-Ming; Qiu, Xue-Lan

2014-01-01

Ratings given to the same item response may have a stronger correlation than those given to different item responses, especially when raters interact with one another before giving ratings. The rater bundle model was developed to account for such local dependence by forming multiple ratings given to an item response as a bundle and assigning…

Asymptotic Properties of Induced Maximum Likelihood Estimates of Nonlinear Models for Item Response Variables: The Finite-Generic-Item-Pool Case.

ERIC Educational Resources Information Center

Jones, Douglas H.

The progress of modern mental test theory depends very much on the techniques of maximum likelihood estimation, and many popular applications make use of likelihoods induced by logistic item response models. While, in reality, item responses are nonreplicate within a single examinee and the logistic models are only ideal, practitioners make…

Rasch Measurement and Item Banking: Theory and Practice.

ERIC Educational Resources Information Center

Nakamura, Yuji

The Rasch Model is an item response theory, one parameter model developed that states that the probability of a correct response on a test is a function of the difficulty of the item and the ability of the candidate. Item banking is useful for language testing. The Rasch Model provides estimates of item difficulties that are meaningful,…

Sample Invariance of the Structural Equation Model and the Item Response Model: A Case Study.

ERIC Educational Resources Information Center

Breithaupt, Krista; Zumbo, Bruno D.

2002-01-01

Evaluated the sample invariance of item discrimination statistics in a case study using real data, responses of 10 random samples of 500 people to a depression scale. Results lend some support to the hypothesized superiority of a two-parameter item response model over the common form of structural equation modeling, at least when responses are…

Quantifying Local, Response Dependence between Two Polytomous Items Using the Rasch Model

ERIC Educational Resources Information Center

Andrich, David; Humphry, Stephen M.; Marais, Ida

2012-01-01

Models of modern test theory imply statistical independence among responses, generally referred to as "local independence." One violation of local independence occurs when the response to one item governs the response to a subsequent item. Expanding on a formulation of this kind of violation as a process in the dichotomous Rasch model,…

Least Squares Distance Method of Cognitive Validation and Analysis for Binary Items Using Their Item Response Theory Parameters

ERIC Educational Resources Information Center

Dimitrov, Dimiter M.

2007-01-01

The validation of cognitive attributes required for correct answers on binary test items or tasks has been addressed in previous research through the integration of cognitive psychology and psychometric models using parametric or nonparametric item response theory, latent class modeling, and Bayesian modeling. All previous models, each with their…

The Consequences of Ignoring Item Parameter Drift in Longitudinal Item Response Models

ERIC Educational Resources Information Center

Lee, Wooyeol; Cho, Sun-Joo

2017-01-01

Utilizing a longitudinal item response model, this study investigated the effect of item parameter drift (IPD) on item parameters and person scores via a Monte Carlo study. Item parameter recovery was investigated for various IPD patterns in terms of bias and root mean-square error (RMSE), and percentage of time the 95% confidence interval covered…

Modeling Answer Change Behavior: An Application of a Generalized Item Response Tree Model

ERIC Educational Resources Information Center

Jeon, Minjeong; De Boeck, Paul; van der Linden, Wim

2017-01-01

We present a novel application of a generalized item response tree model to investigate test takers' answer change behavior. The model allows us to simultaneously model the observed patterns of the initial and final responses after an answer change as a function of a set of latent traits and item parameters. The proposed application is illustrated…

Stochastic Approximation Methods for Latent Regression Item Response Models. Research Report. ETS RR-09-09

ERIC Educational Resources Information Center

von Davier, Matthias; Sinharay, Sandip

2009-01-01

This paper presents an application of a stochastic approximation EM-algorithm using a Metropolis-Hastings sampler to estimate the parameters of an item response latent regression model. Latent regression models are extensions of item response theory (IRT) to a 2-level latent variable model in which covariates serve as predictors of the…

Application of a General Polytomous Testlet Model to the Reading Section of a Large-Scale English Language Assessment. Research Report. ETS RR-10-21

ERIC Educational Resources Information Center

Li, Yanmei; Li, Shuhong; Wang, Lin

2010-01-01

Many standardized educational tests include groups of items based on a common stimulus, known as "testlets". Standard unidimensional item response theory (IRT) models are commonly used to model examinees' responses to testlet items. However, it is known that local dependence among testlet items can lead to biased item parameter estimates…

A Comparison of the One-, the Modified Three-, and the Three-Parameter Item Response Theory Models in the Test Development Item Selection Process.

ERIC Educational Resources Information Center

Eignor, Daniel R.; Douglass, James B.

This paper attempts to provide some initial information about the use of a variety of item response theory (IRT) models in the item selection process; its purpose is to compare the information curves derived from the selection of items characterized by several different IRT models and their associated parameter estimation programs. These…

A Comparison of Limited-Information and Full-Information Methods in M"plus" for Estimating Item Response Theory Parameters for Nonnormal Populations

ERIC Educational Resources Information Center

DeMars, Christine E.

2012-01-01

In structural equation modeling software, either limited-information (bivariate proportions) or full-information item parameter estimation routines could be used for the 2-parameter item response theory (IRT) model. Limited-information methods assume the continuous variable underlying an item response is normally distributed. For skewed and…

Examination of Different Item Response Theory Models on Tests Composed of Testlets

ERIC Educational Resources Information Center

Kogar, Esin Yilmaz; Kelecioglu, Hülya

2017-01-01

The purpose of this research is to first estimate the item and ability parameters and the standard error values related to those parameters obtained from Unidimensional Item Response Theory (UIRT), bifactor (BIF) and Testlet Response Theory models (TRT) in the tests including testlets, when the number of testlets, number of independent items, and…

Item Response Theory Using Hierarchical Generalized Linear Models

ERIC Educational Resources Information Center

Ravand, Hamdollah

2015-01-01

Multilevel models (MLMs) are flexible in that they can be employed to obtain item and person parameters, test for differential item functioning (DIF) and capture both local item and person dependence. Papers on the MLM analysis of item response data have focused mostly on theoretical issues where applications have been add-ons to simulation…

Introduction to Multilevel Item Response Theory Analysis: Descriptive and Explanatory Models

ERIC Educational Resources Information Center

Sulis, Isabella; Toland, Michael D.

2017-01-01

Item response theory (IRT) models are the main psychometric approach for the development, evaluation, and refinement of multi-item instruments and scaling of latent traits, whereas multilevel models are the primary statistical method when considering the dependence between person responses when primary units (e.g., students) are nested within…

IRTPRO 2.1 for Windows (Item Response Theory for Patient-Reported Outcomes)

ERIC Educational Resources Information Center

Paek, Insu; Han, Kyung T.

2013-01-01

This article reviews a new item response theory (IRT) model estimation program, IRTPRO 2.1, for Windows that is capable of unidimensional and multidimensional IRT model estimation for existing and user-specified constrained IRT models for dichotomously and polytomously scored item response data. (Contains 1 figure and 2 notes.)

Vegetable parenting practices scale: Item response modeling analyses

USDA-ARS?s Scientific Manuscript database

Our objective was to evaluate the psychometric properties of a vegetable parenting practices scale using multidimensional polytomous item response modeling which enables assessing item fit to latent variables and the distributional characteristics of the items in comparison to the respondents. We al...

An Evaluation of Three Approximate Item Response Theory Models for Equating Test Scores.

ERIC Educational Resources Information Center

Marco, Gary L.; And Others

Three item response models were evaluated for estimating item parameters and equating test scores. The models, which approximated the traditional three-parameter model, included: (1) the Rasch one-parameter model, operationalized in the BICAL computer program; (2) an approximate three-parameter logistic model based on coarse group data divided…

Vegetable parenting practices scale. Item response modeling analyses

PubMed Central

Chen, Tzu-An; O’Connor, Teresia; Hughes, Sheryl; Beltran, Alicia; Baranowski, Janice; Diep, Cassandra; Baranowski, Tom

2015-01-01

Objective To evaluate the psychometric properties of a vegetable parenting practices scale using multidimensional polytomous item response modeling which enables assessing item fit to latent variables and the distributional characteristics of the items in comparison to the respondents. We also tested for differences in the ways item function (called differential item functioning) across child’s gender, ethnicity, age, and household income groups. Method Parents of 3–5 year old children completed a self-reported vegetable parenting practices scale online. Vegetable parenting practices consisted of 14 effective vegetable parenting practices and 12 ineffective vegetable parenting practices items, each with three subscales (responsiveness, structure, and control). Multidimensional polytomous item response modeling was conducted separately on effective vegetable parenting practices and ineffective vegetable parenting practices. Results One effective vegetable parenting practice item did not fit the model well in the full sample or across demographic groups, and another was a misfit in differential item functioning analyses across child’s gender. Significant differential item functioning was detected across children’s age and ethnicity groups, and more among effective vegetable parenting practices than ineffective vegetable parenting practices items. Wright maps showed items only covered parts of the latent trait distribution. The harder- and easier-to-respond ends of the construct were not covered by items for effective vegetable parenting practices and ineffective vegetable parenting practices, respectively. Conclusions Several effective vegetable parenting practices and ineffective vegetable parenting practices scale items functioned differently on the basis of child’s demographic characteristics; therefore, researchers should use these vegetable parenting practices scales with caution. Item response modeling should be incorporated in analyses of parenting practice questionnaires to better assess differences across demographic characteristics. PMID:25895694

Mixture Item Response Theory-MIMIC Model: Simultaneous Estimation of Differential Item Functioning for Manifest Groups and Latent Classes

ERIC Educational Resources Information Center

Bilir, Mustafa Kuzey

2009-01-01

This study uses a new psychometric model (mixture item response theory-MIMIC model) that simultaneously estimates differential item functioning (DIF) across manifest groups and latent classes. Current DIF detection methods investigate DIF from only one side, either across manifest groups (e.g., gender, ethnicity, etc.), or across latent classes…

Theoretical and Empirical Comparisons between Two Models for Continuous Item Responses.

ERIC Educational Resources Information Center

Ferrando, Pere J.

2002-01-01

Analyzed the relations between two continuous response models intended for typical response items: the linear congeneric model and Samejima's continuous response model (CRM). Illustrated the relations described using an empirical example and assessed the relations through a simulation study. (SLD)

Examination of Polytomous Items' Psychometric Properties According to Nonparametric Item Response Theory Models in Different Test Conditions

ERIC Educational Resources Information Center

Sengul Avsar, Asiye; Tavsancil, Ezel

2017-01-01

This study analysed polytomous items' psychometric properties according to nonparametric item response theory (NIRT) models. Thus, simulated datasets--three different test lengths (10, 20 and 30 items), three sample distributions (normal, right and left skewed) and three samples sizes (100, 250 and 500)--were generated by conducting 20…

Item Response Theory Models for Wording Effects in Mixed-Format Scales

ERIC Educational Resources Information Center

Wang, Wen-Chung; Chen, Hui-Fang; Jin, Kuan-Yu

2015-01-01

Many scales contain both positively and negatively worded items. Reverse recoding of negatively worded items might not be enough for them to function as positively worded items do. In this study, we commented on the drawbacks of existing approaches to wording effect in mixed-format scales and used bi-factor item response theory (IRT) models to…

Structural Equation Model Approach to the Use of Response Times for Improving Estimation in Item Response Models

ERIC Educational Resources Information Center

Sen, Rohini

2012-01-01

In the last five decades, research on the uses of response time has extended into the field of psychometrics (Schnikpe & Scrams, 1999; van der Linden, 2006; van der Linden, 2007), where interest has centered around the usefulness of response time information in item calibration and person measurement within an item response theory. framework.…

Fitting measurement models to vocational interest data: are dominance models ideal?

PubMed

Tay, Louis; Drasgow, Fritz; Rounds, James; Williams, Bruce A

2009-09-01

In this study, the authors examined the item response process underlying 3 vocational interest inventories: the Occupational Preference Inventory (C.-P. Deng, P. I. Armstrong, & J. Rounds, 2007), the Interest Profiler (J. Rounds, T. Smith, L. Hubert, P. Lewis, & D. Rivkin, 1999; J. Rounds, C. M. Walker, et al., 1999), and the Interest Finder (J. E. Wall & H. E. Baker, 1997; J. E. Wall, L. L. Wise, & H. E. Baker, 1996). Item response theory (IRT) dominance models, such as the 2-parameter and 3-parameter logistic models, assume that item response functions (IRFs) are monotonically increasing as the latent trait increases. In contrast, IRT ideal point models, such as the generalized graded unfolding model, have IRFs that peak where the latent trait matches the item. Ideal point models are expected to fit better because vocational interest inventories ask about typical behavior, as opposed to requiring maximal performance. Results show that across all 3 interest inventories, the ideal point model provided better descriptions of the response process. The importance of specifying the correct item response model for precise measurement is discussed. In particular, scores computed by a dominance model were shown to be sometimes illogical: individuals endorsing mostly realistic or mostly social items were given similar scores, whereas scores based on an ideal point model were sensitive to which type of items respondents endorsed.

Modelling Mathematics Problem Solving Item Responses Using a Multidimensional IRT Model

ERIC Educational Resources Information Center

Wu, Margaret; Adams, Raymond

2006-01-01

This research examined students' responses to mathematics problem-solving tasks and applied a general multidimensional IRT model at the response category level. In doing so, cognitive processes were identified and modelled through item response modelling to extract more information than would be provided using conventional practices in scoring…

Practical methods for dealing with 'not applicable' item responses in the AMC Linear Disability Score project

PubMed Central

Holman, Rebecca; Glas, Cees AW; Lindeboom, Robert; Zwinderman, Aeilko H; de Haan, Rob J

2004-01-01

Background Whenever questionnaires are used to collect data on constructs, such as functional status or health related quality of life, it is unlikely that all respondents will respond to all items. This paper examines ways of dealing with responses in a 'not applicable' category to items included in the AMC Linear Disability Score (ALDS) project item bank. Methods The data examined in this paper come from the responses of 392 respondents to 32 items and form part of the calibration sample for the ALDS item bank. The data are analysed using the one-parameter logistic item response theory model. The four practical strategies for dealing with this type of response are: cold deck imputation; hot deck imputation; treating the missing responses as if these items had never been offered to those individual patients; and using a model which takes account of the 'tendency to respond to items'. Results The item and respondent population parameter estimates were very similar for the strategies involving hot deck imputation; treating the missing responses as if these items had never been offered to those individual patients; and using a model which takes account of the 'tendency to respond to items'. The estimates obtained using the cold deck imputation method were substantially different. Conclusions The cold deck imputation method was not considered suitable for use in the ALDS item bank. The other three methods described can be usefully implemented in the ALDS item bank, depending on the purpose of the data analysis to be carried out. These three methods may be useful for other data sets examining similar constructs, when item response theory based methods are used. PMID:15200681

Distinguishing Fast and Slow Processes in Accuracy - Response Time Data.

PubMed

Coomans, Frederik; Hofman, Abe; Brinkhuis, Matthieu; van der Maas, Han L J; Maris, Gunter

2016-01-01

We investigate the relation between speed and accuracy within problem solving in its simplest non-trivial form. We consider tests with only two items and code the item responses in two binary variables: one indicating the response accuracy, and one indicating the response speed. Despite being a very basic setup, it enables us to study item pairs stemming from a broad range of domains such as basic arithmetic, first language learning, intelligence-related problems, and chess, with large numbers of observations for every pair of problems under consideration. We carry out a survey over a large number of such item pairs and compare three types of psychometric accuracy-response time models present in the literature: two 'one-process' models, the first of which models accuracy and response time as conditionally independent and the second of which models accuracy and response time as conditionally dependent, and a 'two-process' model which models accuracy contingent on response time. We find that the data clearly violates the restrictions imposed by both one-process models and requires additional complexity which is parsimoniously provided by the two-process model. We supplement our survey with an analysis of the erroneous responses for an example item pair and demonstrate that there are very significant differences between the types of errors in fast and slow responses.

Analysis Test of Understanding of Vectors with the Three-Parameter Logistic Model of Item Response Theory and Item Response Curves Technique

ERIC Educational Resources Information Center

Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

2016-01-01

This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming…

Effect of Item Response Theory (IRT) Model Selection on Testlet-Based Test Equating. Research Report. ETS RR-14-19

ERIC Educational Resources Information Center

Cao, Yi; Lu, Ru; Tao, Wei

2014-01-01

The local item independence assumption underlying traditional item response theory (IRT) models is often not met for tests composed of testlets. There are 3 major approaches to addressing this issue: (a) ignore the violation and use a dichotomous IRT model (e.g., the 2-parameter logistic [2PL] model), (b) combine the interdependent items to form a…

Numerical Differentiation Methods for Computing Error Covariance Matrices in Item Response Theory Modeling: An Evaluation and a New Proposal

ERIC Educational Resources Information Center

Tian, Wei; Cai, Li; Thissen, David; Xin, Tao

2013-01-01

In item response theory (IRT) modeling, the item parameter error covariance matrix plays a critical role in statistical inference procedures. When item parameters are estimated using the EM algorithm, the parameter error covariance matrix is not an automatic by-product of item calibration. Cai proposed the use of Supplemented EM algorithm for…

The Dutch Identity: A New Tool for the Study of Item Response Models.

ERIC Educational Resources Information Center

Holland, Paul W.

1990-01-01

The Dutch Identity is presented as a useful tool for expressing the basic equations of item response models that relate the manifest probabilities to the item response functions and the latent trait distribution. Ways in which the identity may be exploited are suggested and illustrated. (SLD)

A note on monotonicity of item response functions for ordered polytomous item response theory models.

PubMed

Kang, Hyeon-Ah; Su, Ya-Hui; Chang, Hua-Hua

2018-03-08

A monotone relationship between a true score (τ) and a latent trait level (θ) has been a key assumption for many psychometric applications. The monotonicity property in dichotomous response models is evident as a result of a transformation via a test characteristic curve. Monotonicity in polytomous models, in contrast, is not immediately obvious because item response functions are determined by a set of response category curves, which are conceivably non-monotonic in θ. The purpose of the present note is to demonstrate strict monotonicity in ordered polytomous item response models. Five models that are widely used in operational assessments are considered for proof: the generalized partial credit model (Muraki, 1992, Applied Psychological Measurement, 16, 159), the nominal model (Bock, 1972, Psychometrika, 37, 29), the partial credit model (Masters, 1982, Psychometrika, 47, 147), the rating scale model (Andrich, 1978, Psychometrika, 43, 561), and the graded response model (Samejima, 1972, A general model for free-response data (Psychometric Monograph no. 18). Psychometric Society, Richmond). The study asserts that the item response functions in these models strictly increase in θ and thus there exists strict monotonicity between τ and θ under certain specified conditions. This conclusion validates the practice of customarily using τ in place of θ in applied settings and provides theoretical grounds for one-to-one transformations between the two scales. © 2018 The British Psychological Society.

Applications of Multidimensional Item Response Theory Models with Covariates to Longitudinal Test Data. Research Report. ETS RR-16-21

ERIC Educational Resources Information Center

Fu, Jianbin

2016-01-01

The multidimensional item response theory (MIRT) models with covariates proposed by Haberman and implemented in the "mirt" program provide a flexible way to analyze data based on item response theory. In this report, we discuss applications of the MIRT models with covariates to longitudinal test data to measure skill differences at the…

A Person Fit Test for IRT Models for Polytomous Items

ERIC Educational Resources Information Center

Glas, C. A. W.; Dagohoy, Anna Villa T.

2007-01-01

A person fit test based on the Lagrange multiplier test is presented for three item response theory models for polytomous items: the generalized partial credit model, the sequential model, and the graded response model. The test can also be used in the framework of multidimensional ability parameters. It is shown that the Lagrange multiplier…

Some Issues in Item Response Theory: Dimensionality Assessment and Models for Guessing

ERIC Educational Resources Information Center

Smith, Jessalyn

2009-01-01

Currently, standardized tests are widely used as a method to measure how well schools and students meet academic standards. As a result, measurement issues have become an increasingly popular topic of study. Unidimensional item response models are used to model latent abilities and specific item characteristics. This class of models makes…

Improving the Reliability of Student Scores from Speeded Assessments: An Illustration of Conditional Item Response Theory Using a Computer-Administered Measure of Vocabulary.

PubMed

Petscher, Yaacov; Mitchell, Alison M; Foorman, Barbara R

2015-01-01

A growing body of literature suggests that response latency, the amount of time it takes an individual to respond to an item, may be an important factor to consider when using assessment data to estimate the ability of an individual. Considering that tests of passage and list fluency are being adapted to a computer administration format, it is possible that accounting for individual differences in response times may be an increasingly feasible option to strengthen the precision of individual scores. The present research evaluated the differential reliability of scores when using classical test theory and item response theory as compared to a conditional item response model which includes response time as an item parameter. Results indicated that the precision of student ability scores increased by an average of 5 % when using the conditional item response model, with greater improvements for those who were average or high ability. Implications for measurement models of speeded assessments are discussed.

Improving the Reliability of Student Scores from Speeded Assessments: An Illustration of Conditional Item Response Theory Using a Computer-Administered Measure of Vocabulary

PubMed Central

Petscher, Yaacov; Mitchell, Alison M.; Foorman, Barbara R.

2016-01-01

A growing body of literature suggests that response latency, the amount of time it takes an individual to respond to an item, may be an important factor to consider when using assessment data to estimate the ability of an individual. Considering that tests of passage and list fluency are being adapted to a computer administration format, it is possible that accounting for individual differences in response times may be an increasingly feasible option to strengthen the precision of individual scores. The present research evaluated the differential reliability of scores when using classical test theory and item response theory as compared to a conditional item response model which includes response time as an item parameter. Results indicated that the precision of student ability scores increased by an average of 5 % when using the conditional item response model, with greater improvements for those who were average or high ability. Implications for measurement models of speeded assessments are discussed. PMID:27721568

Using Data Augmentation and Markov Chain Monte Carlo for the Estimation of Unfolding Response Models

ERIC Educational Resources Information Center

Johnson, Matthew S.; Junker, Brian W.

2003-01-01

Unfolding response models, a class of item response theory (IRT) models that assume a unimodal item response function (IRF), are often used for the measurement of attitudes. Verhelst and Verstralen (1993)and Andrich and Luo (1993) independently developed unfolding response models by relating the observed responses to a more common monotone IRT…

An NCME Instructional Module on Item-Fit Statistics for Item Response Theory Models

ERIC Educational Resources Information Center

Ames, Allison J.; Penfield, Randall D.

2015-01-01

Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing…

Higher-Order Item Response Models for Hierarchical Latent Traits

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming

2013-01-01

Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…

Evaluating Item Fit for Multidimensional Item Response Models

ERIC Educational Resources Information Center

Zhang, Bo; Stone, Clement A.

2008-01-01

This research examines the utility of the s-x[superscript 2] statistic proposed by Orlando and Thissen (2000) in evaluating item fit for multidimensional item response models. Monte Carlo simulation was conducted to investigate both the Type I error and statistical power of this fit statistic in analyzing two kinds of multidimensional test…

Using Explanatory Item Response Models to Evaluate Complex Scientific Tasks Designed for the Next Generation Science Standards

NASA Astrophysics Data System (ADS)

Chiu, Tina

This dissertation includes three studies that analyze a new set of assessment tasks developed by the Learning Progressions in Middle School Science (LPS) Project. These assessment tasks were designed to measure science content knowledge on the structure of matter domain and scientific argumentation, while following the goals from the Next Generation Science Standards (NGSS). The three studies focus on the evidence available for the success of this design and its implementation, generally labelled as "validity" evidence. I use explanatory item response models (EIRMs) as the overarching framework to investigate these assessment tasks. These models can be useful when gathering validity evidence for assessments as they can help explain student learning and group differences. In the first study, I explore the dimensionality of the LPS assessment by comparing the fit of unidimensional, between-item multidimensional, and Rasch testlet models to see which is most appropriate for this data. By applying multidimensional item response models, multiple relationships can be investigated, and in turn, allow for a more substantive look into the assessment tasks. The second study focuses on person predictors through latent regression and differential item functioning (DIF) models. Latent regression models show the influence of certain person characteristics on item responses, while DIF models test whether one group is differentially affected by specific assessment items, after conditioning on latent ability. Finally, the last study applies the linear logistic test model (LLTM) to investigate whether item features can help explain differences in item difficulties.

Different Approaches to Covariate Inclusion in the Mixture Rasch Model

ERIC Educational Resources Information Center

Li, Tongyun; Jiao, Hong; Macready, George B.

2016-01-01

The present study investigates different approaches to adding covariates and the impact in fitting mixture item response theory models. Mixture item response theory models serve as an important methodology for tackling several psychometric issues in test development, including the detection of latent differential item functioning. A Monte Carlo…

An Extension of IRT-Based Equating to the Dichotomous Testlet Response Theory Model

ERIC Educational Resources Information Center

Tao, Wei; Cao, Yi

2016-01-01

Current procedures for equating number-correct scores using traditional item response theory (IRT) methods assume local independence. However, when tests are constructed using testlets, one concern is the violation of the local item independence assumption. The testlet response theory (TRT) model is one way to accommodate local item dependence.…

A Note on Item-Restscore Association in Rasch Models

ERIC Educational Resources Information Center

Kreiner, Svend

2011-01-01

To rule out the need for a two-parameter item response theory (IRT) model during item analysis by Rasch models, it is important to check the Rasch model's assumption that all items have the same item discrimination. Biserial and polyserial correlation coefficients measuring the association between items and restscores are often used in an informal…

A Unidimensional Item Response Model for Unfolding Responses from a Graded Disagree-Agree Response Scale.

ERIC Educational Resources Information Center

Roberts, James S.; Laughlin, James E.

1996-01-01

A parametric item response theory model for unfolding binary or graded responses is developed. The graded unfolding model (GUM) is a generalization of the hyperbolic cosine model for binary data of D. Andrich and G. Luo (1993). Applicability of the GUM to attitude testing is illustrated with real data. (SLD)

Distinguishing Fast and Slow Processes in Accuracy - Response Time Data

PubMed Central

Coomans, Frederik; Hofman, Abe; Brinkhuis, Matthieu; van der Maas, Han L. J.; Maris, Gunter

2016-01-01

We investigate the relation between speed and accuracy within problem solving in its simplest non-trivial form. We consider tests with only two items and code the item responses in two binary variables: one indicating the response accuracy, and one indicating the response speed. Despite being a very basic setup, it enables us to study item pairs stemming from a broad range of domains such as basic arithmetic, first language learning, intelligence-related problems, and chess, with large numbers of observations for every pair of problems under consideration. We carry out a survey over a large number of such item pairs and compare three types of psychometric accuracy-response time models present in the literature: two ‘one-process’ models, the first of which models accuracy and response time as conditionally independent and the second of which models accuracy and response time as conditionally dependent, and a ‘two-process’ model which models accuracy contingent on response time. We find that the data clearly violates the restrictions imposed by both one-process models and requires additional complexity which is parsimoniously provided by the two-process model. We supplement our survey with an analysis of the erroneous responses for an example item pair and demonstrate that there are very significant differences between the types of errors in fast and slow responses. PMID:27167518

Item Response Modeling with Sum Scores

ERIC Educational Resources Information Center

Johnson, Timothy R.

2013-01-01

One of the distinctions between classical test theory and item response theory is that the former focuses on sum scores and their relationship to true scores, whereas the latter concerns item responses and their relationship to latent scores. Although item response theory is often viewed as the richer of the two theories, sum scores are still…

Using SAS PROC MCMC for Item Response Theory Models

PubMed Central

Samonte, Kelli

2014-01-01

Interest in using Bayesian methods for estimating item response theory models has grown at a remarkable rate in recent years. This attentiveness to Bayesian estimation has also inspired a growth in available software such as WinBUGS, R packages, BMIRT, MPLUS, and SAS PROC MCMC. This article intends to provide an accessible overview of Bayesian methods in the context of item response theory to serve as a useful guide for practitioners in estimating and interpreting item response theory (IRT) models. Included is a description of the estimation procedure used by SAS PROC MCMC. Syntax is provided for estimation of both dichotomous and polytomous IRT models, as well as a discussion on how to extend the syntax to accommodate more complex IRT models. PMID:29795834

Kernel-Smoothing Estimation of Item Characteristic Functions for Continuous Personality Items: An Empirical Comparison with the Linear and the Continuous-Response Models

ERIC Educational Resources Information Center

Ferrando, Pere J.

2004-01-01

This study used kernel-smoothing procedures to estimate the item characteristic functions (ICFs) of a set of continuous personality items. The nonparametric ICFs were compared with the ICFs estimated (a) by the linear model and (b) by Samejima's continuous-response model. The study was based on a conditioned approach and used an error-in-variables…

Extreme Response Style: Which Model Is Best?

ERIC Educational Resources Information Center

Leventhal, Brian

2017-01-01

More robust and rigorous psychometric models, such as multidimensional Item Response Theory models, have been advocated for survey applications. However, item responses may be influenced by construct-irrelevant variance factors such as preferences for extreme response options. Through empirical and simulation methods, this study evaluates the use…

Improving measurement of injection drug risk behavior using item response theory.

PubMed

Janulis, Patrick

2014-03-01

Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored. To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning. Data is used from three studies in the National Institute on Drug Abuse's Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning. Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data. Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.

Accounting for Local Dependence with the Rasch Model: The Paradox of Information Increase.

PubMed

Andrich, David

Test theories imply statistical, local independence. Where local independence is violated, models of modern test theory that account for it have been proposed. One violation of local independence occurs when the response to one item governs the response to a subsequent item. Expanding on a formulation of this kind of violation between two items in the dichotomous Rasch model, this paper derives three related implications. First, it formalises how the polytomous Rasch model for an item constituted by summing the scores of the dependent items absorbs the dependence in its threshold structure. Second, it shows that as a consequence the unit when the dependence is accounted for is not the same as if the items had no response dependence. Third, it explains the paradox, known, but not explained in the literature, that the greater the dependence of the constituent items the greater the apparent information in the constituted polytomous item when it should provide less information.

A Bayesian Semiparametric Item Response Model with Dirichlet Process Priors

ERIC Educational Resources Information Center

Miyazaki, Kei; Hoshino, Takahiro

2009-01-01

In Item Response Theory (IRT), item characteristic curves (ICCs) are illustrated through logistic models or normal ogive models, and the probability that examinees give the correct answer is usually a monotonically increasing function of their ability parameters. However, since only limited patterns of shapes can be obtained from logistic models…

The Definition of Difficulty and Discrimination for Multidimensional Item Response Theory Models.

ERIC Educational Resources Information Center

Reckase, Mark D.; McKinley, Robert L.

A study was undertaken to develop guidelines for the interpretation of the parameters of three multidimensional item response theory models and to determine the relationship between the parameters and traditional concepts of item difficulty and discrimination. The three models considered were multidimensional extensions of the one-, two-, and…

Item Response Theory at Subject- and Group-Level. Research Report 90-1.

ERIC Educational Resources Information Center

Tobi, Hilde

This paper reviews the literature about item response models for the subject level and aggregated level (group level). Group-level item response models (IRMs) are used in the United States in large-scale assessment programs such as the National Assessment of Educational Progress and the California Assessment Program. In the Netherlands, these…

Estimating the Nominal Response Model under Nonnormal Conditions

ERIC Educational Resources Information Center

Preston, Kathleen Suzanne Johnson; Reise, Steven Paul

2014-01-01

The nominal response model (NRM), a much understudied polytomous item response theory (IRT) model, provides researchers the unique opportunity to evaluate within-item category distinctions. Polytomous IRT models, such as the NRM, are frequently applied to psychological assessments representing constructs that are unlikely to be normally…

A signal detection-item response theory model for evaluating neuropsychological measures.

PubMed

Thomas, Michael L; Brown, Gregory G; Gur, Ruben C; Moore, Tyler M; Patt, Virginie M; Risbrough, Victoria B; Baker, Dewleen G

2018-02-05

Models from signal detection theory are commonly used to score neuropsychological test data, especially tests of recognition memory. Here we show that certain item response theory models can be formulated as signal detection theory models, thus linking two complementary but distinct methodologies. We then use the approach to evaluate the validity (construct representation) of commonly used research measures, demonstrate the impact of conditional error on neuropsychological outcomes, and evaluate measurement bias. Signal detection-item response theory (SD-IRT) models were fitted to recognition memory data for words, faces, and objects. The sample consisted of U.S. Infantry Marines and Navy Corpsmen participating in the Marine Resiliency Study. Data comprised item responses to the Penn Face Memory Test (PFMT; N = 1,338), Penn Word Memory Test (PWMT; N = 1,331), and Visual Object Learning Test (VOLT; N = 1,249), and self-report of past head injury with loss of consciousness. SD-IRT models adequately fitted recognition memory item data across all modalities. Error varied systematically with ability estimates, and distributions of residuals from the regression of memory discrimination onto self-report of past head injury were positively skewed towards regions of larger measurement error. Analyses of differential item functioning revealed little evidence of systematic bias by level of education. SD-IRT models benefit from the measurement rigor of item response theory-which permits the modeling of item difficulty and examinee ability-and from signal detection theory-which provides an interpretive framework encompassing the experimentally validated constructs of memory discrimination and response bias. We used this approach to validate the construct representation of commonly used research measures and to demonstrate how nonoptimized item parameters can lead to erroneous conclusions when interpreting neuropsychological test data. Future work might include the development of computerized adaptive tests and integration with mixture and random-effects models.

Item Response Theory Modeling of the Philadelphia Naming Test.

PubMed

Fergadiotis, Gerasimos; Kellough, Stacey; Hula, William D

2015-06-01

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). 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. 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. 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.

Item response theory and structural equation modelling for ordinal data: Describing the relationship between KIDSCREEN and Life-H.

PubMed

Titman, Andrew C; Lancaster, Gillian A; Colver, Allan F

2016-10-01

Both item response theory and structural equation models are useful in the analysis of ordered categorical responses from health assessment questionnaires. We highlight the advantages and disadvantages of the item response theory and structural equation modelling approaches to modelling ordinal data, from within a community health setting. Using data from the SPARCLE project focussing on children with cerebral palsy, this paper investigates the relationship between two ordinal rating scales, the KIDSCREEN, which measures quality-of-life, and Life-H, which measures participation. Practical issues relating to fitting models, such as non-positive definite observed or fitted correlation matrices, and approaches to assessing model fit are discussed. item response theory models allow properties such as the conditional independence of particular domains of a measurement instrument to be assessed. When, as with the SPARCLE data, the latent traits are multidimensional, structural equation models generally provide a much more convenient modelling framework. © The Author(s) 2013.

Modeling the Severity of Drinking Consequences in First-Year College Women: An Item Response Theory Analysis of the Rutgers Alcohol Problem Index*

PubMed Central

Cohn, Amy M.; Hagman, Brett T.; Graff, Fiona S.; Noel, Nora E.

2011-01-01

Objective: The present study examined the latent continuum of alcohol-related negative consequences among first-year college women using methods from item response theory and classical test theory. Method: Participants (N = 315) were college women in their freshman year who reported consuming any alcohol in the past 90 days and who completed assessments of alcohol consumption and alcohol-related negative consequences using the Rutgers Alcohol Problem Index. Results: Item response theory analyses showed poor model fit for five items identified in the Rutgers Alcohol Problem Index. Two-parameter item response theory logistic models were applied to the remaining 18 items to examine estimates of item difficulty (i.e., severity) and discrimination parameters. The item difficulty parameters ranged from 0.591 to 2.031, and the discrimination parameters ranged from 0.321 to 2.371. Classical test theory analyses indicated that the omission of the five misfit items did not significantly alter the psychometric properties of the construct. Conclusions: Findings suggest that those consequences that had greater severity and discrimination parameters may be used as screening items to identify female problem drinkers at risk for an alcohol use disorder. PMID:22051212

The e-MSWS-12: improving the multiple sclerosis walking scale using item response theory.

PubMed

Engelhard, Matthew M; Schmidt, Karen M; Engel, Casey E; Brenton, J Nicholas; Patek, Stephen D; Goldman, Myla D

2016-12-01

The Multiple Sclerosis Walking Scale (MSWS-12) is the predominant patient-reported measure of multiple sclerosis (MS) -elated walking ability, yet it had not been analyzed using item response theory (IRT), the emerging standard for patient-reported outcome (PRO) validation. This study aims to reduce MSWS-12 measurement error and facilitate computerized adaptive testing by creating an IRT model of the MSWS-12 and distributing it online. MSWS-12 responses from 284 subjects with MS were collected by mail and used to fit and compare several IRT models. Following model selection and assessment, subpopulations based on age and sex were tested for differential item functioning (DIF). Model comparison favored a one-dimensional graded response model (GRM). This model met fit criteria and explained 87 % of response variance. The performance of each MSWS-12 item was characterized using category response curves (CRCs) and item information. IRT-based MSWS-12 scores correlated with traditional MSWS-12 scores (r = 0.99) and timed 25-foot walk (T25FW) speed (r =  -0.70). Item 2 showed DIF based on age (χ 2  = 19.02, df = 5, p < 0.01), and Item 11 showed DIF based on sex (χ 2  = 13.76, df = 5, p = 0.02). MSWS-12 measurement error depends on walking ability, but could be lowered by improving or replacing items with low information or DIF. The e-MSWS-12 includes IRT-based scoring, error checking, and an estimated T25FW derived from MSWS-12 responses. It is available at https://ms-irt.shinyapps.io/e-MSWS-12 .

Handbook of Polytomous Item Response Theory Models

ERIC Educational Resources Information Center

Nering, Michael L., Ed.; Ostini, Remo, Ed.

2010-01-01

This comprehensive "Handbook" focuses on the most used polytomous item response theory (IRT) models. These models help us understand the interaction between examinees and test questions where the questions have various response categories. The book reviews all of the major models and includes discussions about how and where the models…

Item Response Theory Models for Performance Decline during Testing

ERIC Educational Resources Information Center

Jin, Kuan-Yu; Wang, Wen-Chung

2014-01-01

Sometimes, test-takers may not be able to attempt all items to the best of their ability (with full effort) due to personal factors (e.g., low motivation) or testing conditions (e.g., time limit), resulting in poor performances on certain items, especially those located toward the end of a test. Standard item response theory (IRT) models fail to…

Standard Errors and Confidence Intervals from Bootstrapping for Ramsay-Curve Item Response Theory Model Item Parameters

ERIC Educational Resources Information Center

Gu, Fei; Skorupski, William P.; Hoyle, Larry; Kingston, Neal M.

2011-01-01

Ramsay-curve item response theory (RC-IRT) is a nonparametric procedure that estimates the latent trait using splines, and no distributional assumption about the latent trait is required. For item parameters of the two-parameter logistic (2-PL), three-parameter logistic (3-PL), and polytomous IRT models, RC-IRT can provide more accurate estimates…

Conjunctive and Disjunctive Extensions of the Least Squares Distance Model of Cognitive Diagnosis

ERIC Educational Resources Information Center

Dimitrov, Dimiter M.; Atanasov, Dimitar V.

2012-01-01

Many models of cognitive diagnosis, including the "least squares distance model" (LSDM), work under the "conjunctive" assumption that a correct item response occurs when all latent attributes required by the item are correctly performed. This article proposes a "disjunctive" version of the LSDM under which the correct item response occurs when "at…

A Multidimensional Partial Credit Model with Associated Item and Test Statistics: An Application to Mixed-Format Tests

ERIC Educational Resources Information Center

Yao, Lihua; Schwarz, Richard D.

2006-01-01

Multidimensional item response theory (IRT) models have been proposed for better understanding the dimensional structure of data or to define diagnostic profiles of student learning. A compensatory multidimensional two-parameter partial credit model (M-2PPC) for constructed-response items is presented that is a generalization of those proposed to…

A Study of Reverse-Worded Matched Item Pairs Using the Generalized Partial Credit and Nominal Response Models

ERIC Educational Resources Information Center

Matlock Cole, Ki Lynn; Turner, Ronna C.; Gitchel, W. Dent

2018-01-01

The generalized partial credit model (GPCM) is often used for polytomous data; however, the nominal response model (NRM) allows for the investigation of how adjacent categories may discriminate differently when items are positively or negatively worded. Ten items from three different self-reported scales were used (anxiety, depression, and…

Covariates of the Rating Process in Hierarchical Models for Multiple Ratings of Test Items

ERIC Educational Resources Information Center

Mariano, Louis T.; Junker, Brian W.

2007-01-01

When constructed response test items are scored by more than one rater, the repeated ratings allow for the consideration of individual rater bias and variability in estimating student proficiency. Several hierarchical models based on item response theory have been introduced to model such effects. In this article, the authors demonstrate how these…

Bayesian Analysis of Multidimensional Item Response Theory Models: A Discussion and Illustration of Three Response Style Models

ERIC Educational Resources Information Center

Leventhal, Brian C.; Stone, Clement A.

2018-01-01

Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

On the Relationship between Classical Test Theory and Item Response Theory: From One to the Other and Back

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2016-01-01

The frequently neglected and often misunderstood relationship between classical test theory and item response theory is discussed for the unidimensional case with binary measures and no guessing. It is pointed out that popular item response models can be directly obtained from classical test theory-based models by accounting for the discrete…

A Comparison between Discrimination Indices and Item-Response Theory Using the Rasch Model in a Clinical Course Written Examination of a Medical School.

PubMed

Park, Jong Cook; Kim, Kwang Sig

2012-03-01

The reliability of test is determined by each items' characteristics. Item analysis is achieved by classical test theory and item response theory. The purpose of the study was to compare the discrimination indices with item response theory using the Rasch model. Thirty-one 4th-year medical school students participated in the clinical course written examination, which included 22 A-type items and 3 R-type items. Point biserial correlation coefficient (C(pbs)) was compared to method of extreme group (D), biserial correlation coefficient (C(bs)), item-total correlation coefficient (C(it)), and corrected item-total correlation coeffcient (C(cit)). Rasch model was applied to estimate item difficulty and examinee's ability and to calculate item fit statistics using joint maximum likelihood. Explanatory power (r2) of Cpbs is decreased in the following order: C(cit) (1.00), C(it) (0.99), C(bs) (0.94), and D (0.45). The ranges of difficulty logit and standard error and ability logit and standard error were -0.82 to 0.80 and 0.37 to 0.76, -3.69 to 3.19 and 0.45 to 1.03, respectively. Item 9 and 23 have outfit > or =1.3. Student 1, 5, 7, 18, 26, 30, and 32 have fit > or =1.3. C(pbs), C(cit), and C(it) are good discrimination parameters. Rasch model can estimate item difficulty parameter and examinee's ability parameter with standard error. The fit statistics can identify bad items and unpredictable examinee's responses.

Optimal Linking Design for Response Model Parameters

ERIC Educational Resources Information Center

Barrett, Michelle D.; van der Linden, Wim J.

2017-01-01

Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…

Sequential Computerized Mastery Tests--Three Simulation Studies

ERIC Educational Resources Information Center

Wiberg, Marie

2006-01-01

A simulation study of a sequential computerized mastery test is carried out with items modeled with the 3 parameter logistic item response theory model. The examinees' responses are either identically distributed, not identically distributed, or not identically distributed together with estimation errors in the item characteristics. The…

General mixture item response models with different item response structures: Exposition with an application to Likert scales.

PubMed

Tijmstra, Jesper; Bolsinova, Maria; Jeon, Minjeong

2018-01-10

This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person's responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category ("neither agree nor disagree") is taken to be qualitatively similar to the other categories, and is taken to provide information about the person's endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person's willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example.

Examining the Process of Responding to Circumplex Scales of Interpersonal Values Items: Should Ideal Point Scoring Methods Be Considered?

PubMed

Ling, Ying; Zhang, Minqiang; Locke, Kenneth D; Li, Guangming; Li, Zonglong

2016-01-01

The Circumplex Scales of Interpersonal Values (CSIV) is a 64-item self-report measure of goals from each octant of the interpersonal circumplex. We used item response theory methods to compare whether dominance models or ideal point models best described how people respond to CSIV items. Specifically, we fit a polytomous dominance model called the generalized partial credit model and an ideal point model of similar complexity called the generalized graded unfolding model to the responses of 1,893 college students. The results of both graphical comparisons of item characteristic curves and statistical comparisons of model fit suggested that an ideal point model best describes the process of responding to CSIV items. The different models produced different rank orderings of high-scoring respondents, but overall the models did not differ in their prediction of criterion variables (agentic and communal interpersonal traits and implicit motives).

Randomized Item Response Theory Models

ERIC Educational Resources Information Center

Fox, Jean-Paul

2005-01-01

The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…

Detection of Differential Item Functioning Using the Lasso Approach

ERIC Educational Resources Information Center

Magis, David; Tuerlinckx, Francis; De Boeck, Paul

2015-01-01

This article proposes a novel approach to detect differential item functioning (DIF) among dichotomously scored items. Unlike standard DIF methods that perform an item-by-item analysis, we propose the "LR lasso DIF method": logistic regression (LR) model is formulated for all item responses. The model contains item-specific intercepts,…

Measuring change for a multidimensional test using a generalized explanatory longitudinal item response model.

PubMed

Cho, Sun-Joo; Athay, Michele; Preacher, Kristopher J

2013-05-01

Even though many educational and psychological tests are known to be multidimensional, little research has been done to address how to measure individual differences in change within an item response theory framework. In this paper, we suggest a generalized explanatory longitudinal item response model to measure individual differences in change. New longitudinal models for multidimensional tests and existing models for unidimensional tests are presented within this framework and implemented with software developed for generalized linear models. In addition to the measurement of change, the longitudinal models we present can also be used to explain individual differences in change scores for person groups (e.g., learning disabled students versus non-learning disabled students) and to model differences in item difficulties across item groups (e.g., number operation, measurement, and representation item groups in a mathematics test). An empirical example illustrates the use of the various models for measuring individual differences in change when there are person groups and multiple skill domains which lead to multidimensionality at a time point. © 2012 The British Psychological Society.

On Multidimensional Item Response Theory: A Coordinate-Free Approach. Research Report. ETS RR-07-30

ERIC Educational Resources Information Center

Antal, Tamás

2007-01-01

A coordinate-free definition of complex-structure multidimensional item response theory (MIRT) for dichotomously scored items is presented. The point of view taken emphasizes the possibilities and subtleties of understanding MIRT as a multidimensional extension of the classical unidimensional item response theory models. The main theorem of the…

Robust Estimation of Latent Ability in Item Response Models

ERIC Educational Resources Information Center

Schuster, Christof; Yuan, Ke-Hai

2011-01-01

Because of response disturbances such as guessing, cheating, or carelessness, item response models often can only approximate the "true" individual response probabilities. As a consequence, maximum-likelihood estimates of ability will be biased. Typically, the nature and extent to which response disturbances are present is unknown, and, therefore,…

A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means.

PubMed

Polak, Marike; de Rooij, Mark; Heiser, Willem J

2012-09-01

In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) criterion of irrelevance, which is a graphical, exploratory method for evaluating the "relevance" of dichotomous attitude items. We generalized this criterion to graded response items and quantified the relevance by fitting a unimodal smoother. The resulting goodness-of-fit was used to determine item fit and aggregated scale fit. Based on a simulation procedure, cutoff values were proposed for the measures of item fit. These cutoff values showed high power rates and acceptable Type I error rates. We present 2 applications of the OCM method. First, we apply the OCM method to personality data from the Developmental Profile; second, we analyze attitude data collected by Roberts and Laughlin (1996) concerning opinions of capital punishment.

Assessing the Item Response Theory with Covariate (IRT-C) Procedure for Ascertaining Differential Item Functioning

ERIC Educational Resources Information Center

Tay, Louis; Vermunt, Jeroen K.; Wang, Chun

2013-01-01

We evaluate the item response theory with covariates (IRT-C) procedure for assessing differential item functioning (DIF) without preknowledge of anchor items (Tay, Newman, & Vermunt, 2011). This procedure begins with a fully constrained baseline model, and candidate items are tested for uniform and/or nonuniform DIF using the Wald statistic.…

A Conditional Joint Modeling Approach for Locally Dependent Item Responses and Response Times

ERIC Educational Resources Information Center

Meng, Xiang-Bin; Tao, Jian; Chang, Hua-Hua

2015-01-01

The assumption of conditional independence between the responses and the response times (RTs) for a given person is common in RT modeling. However, when the speed of a test taker is not constant, this assumption will be violated. In this article we propose a conditional joint model for item responses and RTs, which incorporates a covariance…

Application of Group-Level Item Response Models in the Evaluation of Consumer Reports about Health Plan Quality

ERIC Educational Resources Information Center

Reise, Steven P.; Meijer, Rob R.; Ainsworth, Andrew T.; Morales, Leo S.; Hays, Ron D.

2006-01-01

Group-level parametric and non-parametric item response theory models were applied to the Consumer Assessment of Healthcare Providers and Systems (CAHPS[R]) 2.0 core items in a sample of 35,572 Medicaid recipients nested within 131 health plans. Results indicated that CAHPS responses are dominated by within health plan variation, and only weakly…

Projective Item Response Model for Test-Independent Measurement

ERIC Educational Resources Information Center

Ip, Edward Hak-Sing; Chen, Shyh-Huei

2012-01-01

The problem of fitting unidimensional item-response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that contains a major dimension of interest but that may also contain minor nuisance dimensions. Because fitting a unidimensional model to multidimensional data results in…

Calibrating Item Families and Summarizing the Results Using Family Expected Response Functions

ERIC Educational Resources Information Center

Sinharay, Sandip; Johnson, Matthew S.; Williamson, David M.

2003-01-01

Item families, which are groups of related items, are becoming increasingly popular in complex educational assessments. For example, in automatic item generation (AIG) systems, a test may consist of multiple items generated from each of a number of item models. Item calibration or scoring for such an assessment requires fitting models that can…

Model Selection Indices for Polytomous Items

ERIC Educational Resources Information Center

Kang, Taehoon; Cohen, Allan S.; Sung, Hyun-Jung

2009-01-01

This study examines the utility of four indices for use in model selection with nested and nonnested polytomous item response theory (IRT) models: a cross-validation index and three information-based indices. Four commonly used polytomous IRT models are considered: the graded response model, the generalized partial credit model, the partial credit…

A Multidimensional Ideal Point Item Response Theory Model for Binary Data.

PubMed

Maydeu-Olivares, Albert; Hernández, Adolfo; McDonald, Roderick P

2006-12-01

We introduce a multidimensional item response theory (IRT) model for binary data based on a proximity response mechanism. Under the model, a respondent at the mode of the item response function (IRF) endorses the item with probability one. The mode of the IRF is the ideal point, or in the multidimensional case, an ideal hyperplane. The model yields closed form expressions for the cell probabilities. We estimate and test the goodness of fit of the model using only information contained in the univariate and bivariate moments of the data. Also, we pit the new model against the multidimensional normal ogive model estimated using NOHARM in four applications involving (a) attitudes toward censorship, (b) satisfaction with life, (c) attitudes of morality and equality, and (d) political efficacy. The normal PDF model is not invariant to simple operations such as reverse scoring. Thus, when there is no natural category to be modeled, as in many personality applications, it should be fit separately with and without reverse scoring for comparisons.

Reevaluation of the Amsterdam Inventory for Auditory Disability and Handicap Using Item Response Theory.

PubMed

Boeschen Hospers, J Mirjam; Smits, Niels; Smits, Cas; Stam, Mariska; Terwee, Caroline B; Kramer, Sophia E

2016-04-01

We reevaluated the psychometric properties of the Amsterdam Inventory for Auditory Disability and Handicap (AIADH; Kramer, Kapteyn, Festen, & Tobi, 1995) using item response theory. Item response theory describes item functioning along an ability continuum. Cross-sectional data from 2,352 adults with and without hearing impairment, ages 18-70 years, were analyzed. They completed the AIADH in the web-based prospective cohort study "Netherlands Longitudinal Study on Hearing." A graded response model was fitted to the AIADH data. Category response curves, item information curves, and the standard error as a function of self-reported hearing ability were plotted. The graded response model showed a good fit. Item information curves were most reliable for adults who reported having hearing disability and less reliable for adults with normal hearing. The standard error plot showed that self-reported hearing ability is most reliably measured for adults reporting mild up to moderate hearing disability. This is one of the few item response theory studies on audiological self-reports. All AIADH items could be hierarchically placed on the self-reported hearing ability continuum, meaning they measure the same construct. This provides a promising basis for developing a clinically useful computerized adaptive test, where item selection adapts to the hearing ability of individuals, resulting in efficient assessment of hearing disability.

Innovative Application of a Multidimensional Item Response Model in Assessing the Influence of Social Desirability on the Pseudo-Relationship between Self-Efficacy and Behavior

ERIC Educational Resources Information Center

Watson, Kathy; Baranowski, Tom; Thompson, Debbe; Jago, Russell; Baranowski, Janice; Klesges, Lisa M.

2006-01-01

This study examined multidimensional item response theory (MIRT) modeling to assess social desirability (SocD) influences on self-reported physical activity self-efficacy (PASE) and fruit and vegetable self-efficacy (FVSE). The observed sample included 473 Houston-area adolescent males (10-14 years). SocD (nine items), PASE (19 items) and FVSE (21…

Fitting the Rasch Model to Account for Variation in Item Discrimination

ERIC Educational Resources Information Center

Weitzman, R. A.

2009-01-01

Building on the Kelley and Gulliksen versions of classical test theory, this article shows that a logistic model having only a single item parameter can account for varying item discrimination, as well as difficulty, by using item-test correlations to adjust incorrect-correct (0-1) item responses prior to an initial model fit. The fit occurs…

Fitting a Mixture Item Response Theory Model to Personality Questionnaire Data: Characterizing Latent Classes and Investigating Possibilities for Improving Prediction

ERIC Educational Resources Information Center

Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk

2008-01-01

Mixture item response theory (IRT) models aid the interpretation of response behavior on personality tests and may provide possibilities for improving prediction. Heterogeneity in the population is modeled by identifying homogeneous subgroups that conform to different measurement models. In this study, mixture IRT models were applied to the…

Item Response Theory Modeling of the Philadelphia Naming Test

ERIC Educational Resources Information Center

Fergadiotis, Gerasimos; Kellough, Stacey; Hula, William D.

2015-01-01

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…

Data Visualization of Item-Total Correlation by Median Smoothing

ERIC Educational Resources Information Center

Yu, Chong Ho; Douglas, Samantha; Lee, Anna; An, Min

2016-01-01

This paper aims to illustrate how data visualization could be utilized to identify errors prior to modeling, using an example with multi-dimensional item response theory (MIRT). MIRT combines item response theory and factor analysis to identify a psychometric model that investigates two or more latent traits. While it may seem convenient to…

Semiparametric Item Response Functions in the Context of Guessing

ERIC Educational Resources Information Center

Falk, Carl F.; Cai, Li

2016-01-01

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood-based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

A Bayesian Beta-Mixture Model for Nonparametric IRT (BBM-IRT)

ERIC Educational Resources Information Center

Arenson, Ethan A.; Karabatsos, George

2017-01-01

Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…

The Graded Unfolding Model: A Unidimensional Item Response Model for Unfolding Graded Responses.

ERIC Educational Resources Information Center

Roberts, James S.; Laughlin, James E.

Binary or graded disagree-agree responses to attitude items are often collected for the purpose of attitude measurement. Although such data are sometimes analyzed with cumulative measurement models, recent investigations suggest that unfolding models are more appropriate (J. S. Roberts, 1995; W. H. Van Schuur and H. A. L. Kiers, 1994). Advances in…

An Estimation Procedure for the Structural Parameters of the Unified Cognitive/IRT Model.

ERIC Educational Resources Information Center

Jiang, Hai; And Others

L. V. DiBello, W. F. Stout, and L. A. Roussos (1993) have developed a new item response model, the Unified Model, which brings together the discrete, deterministic aspects of cognition favored by cognitive scientists, and the continuous, stochastic aspects of test response behavior that underlie item response theory (IRT). The Unified Model blends…

Best Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model

PubMed Central

Seo, Dong Gi; Weiss, David J.

2015-01-01

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection. PMID:29795848

Comparison of Multidimensional Item Response Models: Multivariate Normal Ability Distributions versus Multivariate Polytomous Ability Distributions. Research Report. ETS RR-08-45

ERIC Educational Resources Information Center

Haberman, Shelby J.; von Davier, Matthias; Lee, Yi-Hsuan

2008-01-01

Multidimensional item response models can be based on multivariate normal ability distributions or on multivariate polytomous ability distributions. For the case of simple structure in which each item corresponds to a unique dimension of the ability vector, some applications of the two-parameter logistic model to empirical data are employed to…

Bayesian Estimation of Multi-Unidimensional Graded Response IRT Models

ERIC Educational Resources Information Center

Kuo, Tzu-Chun

2015-01-01

Item response theory (IRT) has gained an increasing popularity in large-scale educational and psychological testing situations because of its theoretical advantages over classical test theory. Unidimensional graded response models (GRMs) are useful when polytomous response items are designed to measure a unified latent trait. They are limited in…

Using a Multivariate Multilevel Polytomous Item Response Theory Model to Study Parallel Processes of Change: The Dynamic Association between Adolescents' Social Isolation and Engagement with Delinquent Peers in the National Youth Survey

ERIC Educational Resources Information Center

Hsieh, Chueh-An; von Eye, Alexander A.; Maier, Kimberly S.

2010-01-01

The application of multidimensional item response theory models to repeated observations has demonstrated great promise in developmental research. It allows researchers to take into consideration both the characteristics of item response and measurement error in longitudinal trajectory analysis, which improves the reliability and validity of the…

Developing a short version of the Toronto Structured Interview for Alexithymia using item response theory.

PubMed

Sekely, Angela; Taylor, Graeme J; Bagby, R Michael

2018-03-17

The Toronto Structured Interview for Alexithymia (TSIA) was developed to provide a structured interview method for assessing alexithymia. One drawback of this instrument is the amount of time it takes to administer and score. The current study used item response theory (IRT) methods to analyze data from a large heterogeneous multi-language sample (N = 842) to investigate whether a subset of items could be selected to create a short version of the instrument. Samejima's (1969) graded response model was used to fit the item responses. Items providing maximum information were retained in the short model, resulting in the elimination of 12-items from the original 24-items. Despite the 50% reduction in the number of items, 65.22% of the information was retained. Further studies are needed to validate the short version. A short version of the TSIA is potentially of practical value to clinicians and researchers with time constraints. Copyright © 2018. Published by Elsevier B.V.

What can we learn from PISA?: Investigating PISA's approach to scientific literacy

NASA Astrophysics Data System (ADS)

Schwab, Cheryl Jean

This dissertation is an investigation of the relationship between the multidimensional conception of scientific literacy and its assessment. The Programme for International Student Assessment (PISA), developed under the auspices of the Organization for Economic Cooperation and Development (OECD), offers a unique opportunity to evaluate the assessment of scientific literacy. PISA developed a continuum of performance for scientific literacy across three competencies (i.e., process, content, and situation). Foundational to the interpretation of PISA science assessment is PISA's definition of scientific literacy, which I argue incorporates three themes drawn from history: (a) scientific way of thinking, (b) everyday relevance of science, and (c) scientific literacy for all students. Three coordinated studies were conducted to investigate the validity of PISA science assessment and offer insight into the development of items to assess scientific 2 literacy. Multidimensional models of the internal structure of the PISA 2003 science items were found not to reflect the complex character of PISA's definition of scientific literacy. Although the multidimensional models across the three competencies significantly decreased the G2 statistic from the unidimensional model, high correlations between the dimensions suggest that the dimensions are similar. A cognitive analysis of student verbal responses to PISA science items revealed that students were using competencies of scientific literacy, but the competencies were not elicited by the PISA science items at the depth required by PISA's definition of scientific literacy. Although student responses contained only knowledge of scientific facts and simple scientific concepts, students were using more complex skills to interpret and communicate their responses. Finally the investigation of different scoring approaches and item response models illustrated different ways to interpret student responses to assessment items. These analyses highlighted the complexities of students' responses to the PISA science items and the use of the ordered partition model to accommodate different but equal item responses. The results of the three investigations are used to discuss ways to improve the development and interpretation of PISA's science items.

Dealing with Omitted and Not-Reached Items in Competence Tests: Evaluating Approaches Accounting for Missing Responses in Item Response Theory Models

ERIC Educational Resources Information Center

Pohl, Steffi; Gräfe, Linda; Rose, Norman

2014-01-01

Data from competence tests usually show a number of missing responses on test items due to both omitted and not-reached items. Different approaches for dealing with missing responses exist, and there are no clear guidelines on which of those to use. While classical approaches rely on an ignorable missing data mechanism, the most recently developed…

Log-Multiplicative Association Models as Item Response Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Yu, Hsiu-Ting

2007-01-01

Log-multiplicative association (LMA) models, which are special cases of log-linear models, have interpretations in terms of latent continuous variables. Two theoretical derivations of LMA models based on item response theory (IRT) arguments are presented. First, we show that Anderson and colleagues (Anderson & Vermunt, 2000; Anderson & Bockenholt,…

Unidimensional Interpretations for Multidimensional Test Items

ERIC Educational Resources Information Center

Kahraman, Nilufer

2013-01-01

This article considers potential problems that can arise in estimating a unidimensional item response theory (IRT) model when some test items are multidimensional (i.e., show a complex factorial structure). More specifically, this study examines (1) the consequences of model misfit on IRT item parameter estimates due to unintended minor item-level…

Using Response-Time Constraints in Item Selection To Control for Differential Speededness in Computerized Adaptive Testing. LSAC Research Report Series.

ERIC Educational Resources Information Center

van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L.

This paper proposes an item selection algorithm that can be used to neutralize the effect of time limits in computer adaptive testing. The method is based on a statistical model for the response-time distributions of the test takers on the items in the pool that is updated each time a new item has been administered. Predictions from the model are…

Evaluation of Internal Construct Validity and Unidimensionality of the Brachial Assessment Tool, A Patient-Reported Outcome Measure for Brachial Plexus Injury.

PubMed

Hill, Bridget; Pallant, Julie; Williams, Gavin; Olver, John; Ferris, Scott; Bialocerkowski, Andrea

2016-12-01

To evaluate the internal construct validity and dimensionality of a new patient-reported outcome measure for people with traumatic brachial plexus injury (BPI) based on the International Classification of Functioning, Disability and Health definition of activity. Cross-sectional study. Outpatient clinics. Adults (age range, 18-82y) with a traumatic BPI (N=106). There were 106 people with BPI who completed a 51-item 5-response questionnaire. Responses were analyzed in 4 phases (missing responses, item correlations, exploratory factor analysis, and Rasch analysis) to evaluate the properties of fit to the Rasch model, threshold response, local dependency, dimensionality, differential item functioning, and targeting. Not applicable, as this study addresses the development of an outcome measure. Six items were deleted for missing responses, and 10 were deleted for high interitem correlations >.81. The remaining 35 items, while demonstrating fit to the Rasch model, showed evidence of local dependency and multidimensionality. Items were divided into 3 subscales: dressing and grooming (8 items), arm and hand (17 items), and no hand (6 items). All 3 subscales demonstrated fit to the model with no local dependency, minimal disordered thresholds, no unidimensionality or differential item functioning for age, time postinjury, or self-selected dominance. Subscales were combined into 3 subtests and demonstrated fit to the model, no misfit, and unidimensionality, allowing calculation of a summary score. This preliminary analysis supports the internal construct validity of the Brachial Assessment Tool, a unidimensional targeted 4-response patient-reported outcome measure designed to solely assess activity after traumatic BPI regardless of level of injury, age at recruitment, premorbid limb dominance, and time postinjury. Further examination is required to determine test-retest reliability and responsiveness. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Item Parameter Estimation for the MIRT Model: Bias and Precision of Confirmatory Factor Analysis-Based Models

ERIC Educational Resources Information Center

Finch, Holmes

2010-01-01

The accuracy of item parameter estimates in the multidimensional item response theory (MIRT) model context is one that has not been researched in great detail. This study examines the ability of two confirmatory factor analysis models specifically for dichotomous data to properly estimate item parameters using common formulae for converting factor…

Using Item Response Theory to Develop Measures of Acquisitive and Protective Self-Monitoring From the Original Self-Monitoring Scale.

PubMed

Wilmot, Michael P; Kostal, Jack W; Stillwell, David; Kosinski, Michal

2017-07-01

For the past 40 years, the conventional univariate model of self-monitoring has reigned as the dominant interpretative paradigm in the literature. However, recent findings associated with an alternative bivariate model challenge the conventional paradigm. In this study, item response theory is used to develop measures of the bivariate model of acquisitive and protective self-monitoring using original Self-Monitoring Scale (SMS) items, and data from two large, nonstudent samples ( Ns = 13,563 and 709). Results indicate that the new acquisitive (six-item) and protective (seven-item) self-monitoring scales are reliable, unbiased in terms of gender and age, and demonstrate theoretically consistent relations to measures of personality traits and cognitive ability. Additionally, by virtue of using original SMS items, previously collected responses can be reanalyzed in accordance with the alternative bivariate model. Recommendations for the reanalysis of archival SMS data, as well as directions for future research, are provided.

Development of a subjective cognitive decline questionnaire using item response theory: a pilot study.

PubMed

Gifford, Katherine A; Liu, Dandan; Romano, Raymond; Jones, Richard N; Jefferson, Angela L

2015-12-01

Subjective cognitive decline (SCD) may indicate unhealthy cognitive changes, but no standardized SCD measurement exists. This pilot study aims to identify reliable SCD questions. 112 cognitively normal (NC, 76±8 years, 63% female), 43 mild cognitive impairment (MCI; 77±7 years, 51% female), and 33 diagnostically ambiguous participants (79±9 years, 58% female) were recruited from a research registry and completed 57 self-report SCD questions. Psychometric methods were used for item-reduction. Factor analytic models assessed unidimensionality of the latent trait (SCD); 19 items were removed with extreme response distribution or trait-fit. Item response theory (IRT) provided information about question utility; 17 items with low information were dropped. Post-hoc simulation using computerized adaptive test (CAT) modeling selected the most commonly used items (n=9 of 21 items) that represented the latent trait well (r=0.94) and differentiated NC from MCI participants (F(1,146)=8.9, p=0.003). Item response theory and computerized adaptive test modeling identified nine reliable SCD items. This pilot study is a first step toward refining SCD assessment in older adults. Replication of these findings and validation with Alzheimer's disease biomarkers will be an important next step for the creation of a SCD screener.

Item Estimates under Low-Stakes Conditions: How Should Omits Be Treated?

ERIC Educational Resources Information Center

DeMars, Christine

Using data from a pilot test of science and math from students in 30 high schools, item difficulties were estimated with a one-parameter model (partial-credit model for the multi-point items). Some items were multiple-choice items, and others were constructed-response items (open-ended). Four sets of estimates were obtained: estimates for males…

Bayes Factor Covariance Testing in Item Response Models.

PubMed

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Using Rasch rating scale model to reassess the psychometric properties of the Persian version of the PedsQL™ 4.0 Generic Core Scales in school children.

PubMed

Jafari, Peyman; Bagheri, Zahra; Ayatollahi, Seyyed Mohamad Taghi; Soltani, Zahra

2012-03-13

Item response theory (IRT) is extensively used to develop adaptive instruments of health-related quality of life (HRQoL). However, each IRT model has its own function to estimate item and category parameters, and hence different results may be found using the same response categories with different IRT models. The present study used the Rasch rating scale model (RSM) to examine and reassess the psychometric properties of the Persian version of the PedsQL™ 4.0 Generic Core Scales. The PedsQL™ 4.0 Generic Core Scales was completed by 938 Iranian school children and their parents. Convergent, discriminant and construct validity of the instrument were assessed by classical test theory (CTT). The RSM was applied to investigate person and item reliability, item statistics and ordering of response categories. The CTT method showed that the scaling success rate for convergent and discriminant validity were 100% in all domains with the exception of physical health in the child self-report. Moreover, confirmatory factor analysis supported a four-factor model similar to its original version. The RSM showed that 22 out of 23 items had acceptable infit and outfit statistics (<1.4, >0.6), person reliabilities were low, item reliabilities were high, and item difficulty ranged from -1.01 to 0.71 and -0.68 to 0.43 for child self-report and parent proxy-report, respectively. Also the RSM showed that successive response categories for all items were not located in the expected order. This study revealed that, in all domains, the five response categories did not perform adequately. It is not known whether this problem is a function of the meaning of the response choices in the Persian language or an artifact of a mostly healthy population that did not use the full range of the response categories. The response categories should be evaluated in further validation studies, especially in large samples of chronically ill patients.

Item Response Modeling: An Evaluation of the Children's Fruit and Vegetable Self-Efficacy Questionnaire

ERIC Educational Resources Information Center

Watson, Kathy; Baranowski, Tom; Thompson, Debbe

2006-01-01

Perceived self-efficacy (SE) for eating fruit and vegetables (FV) is a key variable mediating FV change in interventions. This study applies item response modeling (IRM) to a fruit, juice and vegetable self-efficacy questionnaire (FVSEQ) previously validated with classical test theory (CTT) procedures. The 24-item (five-point Likert scale) FVSEQ…

Semi-Parametric Item Response Functions in the Context of Guessing. CRESST Report 844

ERIC Educational Resources Information Center

Falk, Carl F.; Cai, Li

2015-01-01

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

Using the Item Response Theory (IRT) for Educational Evaluation through Games

ERIC Educational Resources Information Center

Euzébio Batista, Marcelo Henrique; Victória Barbosa, Jorge Luis; da Rosa Tavares, João Elison; Hackenhaar, Jonathan Luis

2013-01-01

This article shows the application of Item Response Theory (IRT) for educational evaluation using games. The article proposes a computational model to create user profiles, called Psychometric Profile Generator (PPG). PPG uses the IRT mathematical model for exploring the levels of skills and behaviors in the form of items and/or stimuli. The model…

[Instrument to measure adherence in hypertensive patients: contribution of Item Response Theory].

PubMed

Rodrigues, Malvina Thaís Pacheco; Moreira, Thereza Maria Magalhaes; Vasconcelos, Alexandre Meira de; Andrade, Dalton Francisco de; Silva, Daniele Braz da; Barbetta, Pedro Alberto

2013-06-01

To analyze, by means of "Item Response Theory", an instrument to measure adherence to t treatment for hypertension. Analytical study with 406 hypertensive patients with associated complications seen in primary care in Fortaleza, CE, Northeastern Brazil, 2011 using "Item Response Theory". The stages were: dimensionality test, calibrating the items, processing data and creating a scale, analyzed using the gradual response model. A study of the dimensionality of the instrument was conducted by analyzing the polychoric correlation matrix and factor analysis of complete information. Multilog software was used to calibrate items and estimate the scores. Items relating to drug therapy are the most directly related to adherence while those relating to drug-free therapy need to be reworked because they have less psychometric information and low discrimination. The independence of items, the small number of levels in the scale and low explained variance in the adjustment of the models show the main weaknesses of the instrument analyzed. The "Item Response Theory" proved to be a relevant analysis technique because it evaluated respondents for adherence to treatment for hypertension, the level of difficulty of the items and their ability to discriminate between individuals with different levels of adherence, which generates a greater amount of information. The instrument analyzed is limited in measuring adherence to hypertension treatment, by analyzing the "Item Response Theory" of the item, and needs adjustment. The proper formulation of the items is important in order to accurately measure the desired latent trait.

Cognitive diagnosis modelling incorporating item response times.

PubMed

Zhan, Peida; Jiao, Hong; Liao, Dandan

2018-05-01

To provide more refined diagnostic feedback with collateral information in item response times (RTs), this study proposed joint modelling of attributes and response speed using item responses and RTs simultaneously for cognitive diagnosis. For illustration, an extended deterministic input, noisy 'and' gate (DINA) model was proposed for joint modelling of responses and RTs. Model parameter estimation was explored using the Bayesian Markov chain Monte Carlo (MCMC) method. The PISA 2012 computer-based mathematics data were analysed first. These real data estimates were treated as true values in a subsequent simulation study. A follow-up simulation study with ideal testing conditions was conducted as well to further evaluate model parameter recovery. The results indicated that model parameters could be well recovered using the MCMC approach. Further, incorporating RTs into the DINA model would improve attribute and profile correct classification rates and result in more accurate and precise estimation of the model parameters. © 2017 The British Psychological Society.

Calibration and Validation of the Dutch-Flemish PROMIS Pain Interference Item Bank in Patients with Chronic Pain

PubMed Central

Crins, Martine H. P.; Roorda, Leo D.; Smits, Niels; de Vet, Henrica C. W.; Westhovens, Rene; Cella, David; Cook, Karon F.; Revicki, Dennis; van Leeuwen, Jaap; Boers, Maarten; Dekker, Joost; Terwee, Caroline B.

2015-01-01

The Dutch-Flemish PROMIS Group translated the adult PROMIS Pain Interference item bank into Dutch-Flemish. The aims of the current study were to calibrate the parameters of these items using an item response theory (IRT) model, to evaluate the cross-cultural validity of the Dutch-Flemish translations compared to the original English items, and to evaluate their reliability and construct validity. The 40 items in the bank were completed by 1085 Dutch chronic pain patients. Before calibrating the items, IRT model assumptions were evaluated using confirmatory factor analysis (CFA). Items were calibrated using the graded response model (GRM), an IRT model appropriate for items with more than two response options. To evaluate cross-cultural validity, differential item functioning (DIF) for language (Dutch vs. English) was examined. Reliability was evaluated based on standard errors and Cronbach’s alpha. To evaluate construct validity correlations with scores on legacy instruments (e.g., the Disabilities of the Arm, Shoulder and Hand Questionnaire) were calculated. Unidimensionality of the Dutch-Flemish PROMIS Pain Interference item bank was supported by CFA tests of model fit (CFI = 0.986, TLI = 0.986). Furthermore, the data fit the GRM and showed good coverage across the pain interference continuum (threshold-parameters range: -3.04 to 3.44). The Dutch-Flemish PROMIS Pain Interference item bank has good cross-cultural validity (only two out of 40 items showing DIF), good reliability (Cronbach’s alpha = 0.98), and good construct validity (Pearson correlations between 0.62 and 0.75). A computer adaptive test (CAT) and Dutch-Flemish PROMIS short forms of the Dutch-Flemish PROMIS Pain Interference item bank can now be developed. PMID:26214178

Calibration and Validation of the Dutch-Flemish PROMIS Pain Interference Item Bank in Patients with Chronic Pain.

PubMed

Crins, Martine H P; Roorda, Leo D; Smits, Niels; de Vet, Henrica C W; Westhovens, Rene; Cella, David; Cook, Karon F; Revicki, Dennis; van Leeuwen, Jaap; Boers, Maarten; Dekker, Joost; Terwee, Caroline B

2015-01-01

The Dutch-Flemish PROMIS Group translated the adult PROMIS Pain Interference item bank into Dutch-Flemish. The aims of the current study were to calibrate the parameters of these items using an item response theory (IRT) model, to evaluate the cross-cultural validity of the Dutch-Flemish translations compared to the original English items, and to evaluate their reliability and construct validity. The 40 items in the bank were completed by 1085 Dutch chronic pain patients. Before calibrating the items, IRT model assumptions were evaluated using confirmatory factor analysis (CFA). Items were calibrated using the graded response model (GRM), an IRT model appropriate for items with more than two response options. To evaluate cross-cultural validity, differential item functioning (DIF) for language (Dutch vs. English) was examined. Reliability was evaluated based on standard errors and Cronbach's alpha. To evaluate construct validity correlations with scores on legacy instruments (e.g., the Disabilities of the Arm, Shoulder and Hand Questionnaire) were calculated. Unidimensionality of the Dutch-Flemish PROMIS Pain Interference item bank was supported by CFA tests of model fit (CFI = 0.986, TLI = 0.986). Furthermore, the data fit the GRM and showed good coverage across the pain interference continuum (threshold-parameters range: -3.04 to 3.44). The Dutch-Flemish PROMIS Pain Interference item bank has good cross-cultural validity (only two out of 40 items showing DIF), good reliability (Cronbach's alpha = 0.98), and good construct validity (Pearson correlations between 0.62 and 0.75). A computer adaptive test (CAT) and Dutch-Flemish PROMIS short forms of the Dutch-Flemish PROMIS Pain Interference item bank can now be developed.

Locally Dependent Linear Logistic Test Model with Person Covariates

ERIC Educational Resources Information Center

Ip, Edward H.; Smits, Dirk J. M.; De Boeck, Paul

2009-01-01

The article proposes a family of item-response models that allow the separate and independent specification of three orthogonal components: item attribute, person covariate, and local item dependence. Special interest lies in extending the linear logistic test model, which is commonly used to measure item attributes, to tests with embedded item…

Multidimensional Extension of Multiple Indicators Multiple Causes Models to Detect DIF

ERIC Educational Resources Information Center

Lee, Soo; Bulut, Okan; Suh, Youngsuk

2017-01-01

A number of studies have found multiple indicators multiple causes (MIMIC) models to be an effective tool in detecting uniform differential item functioning (DIF) for individual items and item bundles. A recently developed MIMIC-interaction model is capable of detecting both uniform and nonuniform DIF in the unidimensional item response theory…

Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers

PubMed Central

2012-01-01

Background Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related) Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires. Methods Scalability of data from 1) a cross-sectional health survey (the Scottish Health Education Population Survey) and 2) a general population birth cohort study (the National Child Development Study) illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale. Results and conclusions After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items) we show that all items from the 12-item General Health Questionnaire (GHQ-12) – when binary scored – were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech’s “well-being” and “distress” clinical scales). An illustration of ordinal item analysis confirmed that all 14 positively worded items of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) met criteria for the monotone homogeneity model but four items violated double monotonicity with respect to a single underlying dimension. Software availability and commands used to specify unidimensionality and reliability analysis and graphical displays for diagnosing monotone homogeneity and double monotonicity are discussed, with an emphasis on current implementations in freeware. PMID:22686586

Mokken scale analysis of mental health and well-being questionnaire item responses: a non-parametric IRT method in empirical research for applied health researchers.

PubMed

Stochl, Jan; Jones, Peter B; Croudace, Tim J

2012-06-11

Mokken scaling techniques are a useful tool for researchers who wish to construct unidimensional tests or use questionnaires that comprise multiple binary or polytomous items. The stochastic cumulative scaling model offered by this approach is ideally suited when the intention is to score an underlying latent trait by simple addition of the item response values. In our experience, the Mokken model appears to be less well-known than for example the (related) Rasch model, but is seeing increasing use in contemporary clinical research and public health. Mokken's method is a generalisation of Guttman scaling that can assist in the determination of the dimensionality of tests or scales, and enables consideration of reliability, without reliance on Cronbach's alpha. This paper provides a practical guide to the application and interpretation of this non-parametric item response theory method in empirical research with health and well-being questionnaires. Scalability of data from 1) a cross-sectional health survey (the Scottish Health Education Population Survey) and 2) a general population birth cohort study (the National Child Development Study) illustrate the method and modeling steps for dichotomous and polytomous items respectively. The questionnaire data analyzed comprise responses to the 12 item General Health Questionnaire, under the binary recoding recommended for screening applications, and the ordinal/polytomous responses to the Warwick-Edinburgh Mental Well-being Scale. After an initial analysis example in which we select items by phrasing (six positive versus six negatively worded items) we show that all items from the 12-item General Health Questionnaire (GHQ-12)--when binary scored--were scalable according to the double monotonicity model, in two short scales comprising six items each (Bech's "well-being" and "distress" clinical scales). An illustration of ordinal item analysis confirmed that all 14 positively worded items of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS) met criteria for the monotone homogeneity model but four items violated double monotonicity with respect to a single underlying dimension.Software availability and commands used to specify unidimensionality and reliability analysis and graphical displays for diagnosing monotone homogeneity and double monotonicity are discussed, with an emphasis on current implementations in freeware.

The Generalized Multilevel Facets Model for Longitudinal Data

ERIC Educational Resources Information Center

Hung, Lai-Fa; Wang, Wen-Chung

2012-01-01

In the human sciences, ability tests or psychological inventories are often repeatedly conducted to measure growth. Standard item response models do not take into account possible autocorrelation in longitudinal data. In this study, the authors propose an item response model to account for autocorrelation. The proposed three-level model consists…

Extended Mixed-Efects Item Response Models with the MH-RM Algorithm

ERIC Educational Resources Information Center

Chalmers, R. Philip

2015-01-01

A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…

Modeling Nonignorable Missing Data in Speeded Tests

ERIC Educational Resources Information Center

Glas, Cees A. W.; Pimentel, Jonald L.

2008-01-01

In tests with time limits, items at the end are often not reached. Usually, the pattern of missing responses depends on the ability level of the respondents; therefore, missing data are not ignorable in statistical inference. This study models data using a combination of two item response theory (IRT) models: one for the observed response data and…

Model Choice and Sample Size in Item Response Theory Analysis of Aphasia Tests

ERIC Educational Resources Information Center

Hula, William D.; Fergadiotis, Gerasimos; Martin, Nadine

2012-01-01

Purpose: The purpose of this study was to identify the most appropriate item response theory (IRT) measurement model for aphasia tests requiring 2-choice responses and to determine whether small samples are adequate for estimating such models. Method: Pyramids and Palm Trees (Howard & Patterson, 1992) test data that had been collected from…

Item Response Modeling of Multivariate Count Data with Zero Inflation, Maximum Inflation, and Heaping

ERIC Educational Resources Information Center

Magnus, Brooke E.; Thissen, David

2017-01-01

Questionnaires that include items eliciting count responses are becoming increasingly common in psychology. This study proposes methodological techniques to overcome some of the challenges associated with analyzing multivariate item response data that exhibit zero inflation, maximum inflation, and heaping at preferred digits. The modeling…

Online Calibration of Polytomous Items Under the Generalized Partial Credit Model

PubMed Central

Zheng, Yi

2016-01-01

Online calibration is a technology-enhanced architecture for item calibration in computerized adaptive tests (CATs). Many CATs are administered continuously over a long term and rely on large item banks. To ensure test validity, these item banks need to be frequently replenished with new items, and these new items need to be pretested before being used operationally. Online calibration dynamically embeds pretest items in operational tests and calibrates their parameters as response data are gradually obtained through the continuous test administration. This study extends existing formulas, procedures, and algorithms for dichotomous item response theory models to the generalized partial credit model, a popular model for items scored in more than two categories. A simulation study was conducted to investigate the developed algorithms and procedures under a variety of conditions, including two estimation algorithms, three pretest item selection methods, three seeding locations, two numbers of score categories, and three calibration sample sizes. Results demonstrated acceptable estimation accuracy of the two estimation algorithms in some of the simulated conditions. A variety of findings were also revealed for the interacted effects of included factors, and recommendations were made respectively. PMID:29881063

The Effects of Test Length and Sample Size on Item Parameters in Item Response Theory

ERIC Educational Resources Information Center

Sahin, Alper; Anil, Duygu

2017-01-01

This study investigates the effects of sample size and test length on item-parameter estimation in test development utilizing three unidimensional dichotomous models of item response theory (IRT). For this purpose, a real language test comprised of 50 items was administered to 6,288 students. Data from this test was used to obtain data sets of…

Item Response Theory with Covariates (IRT-C): Assessing Item Recovery and Differential Item Functioning for the Three-Parameter Logistic Model

ERIC Educational Resources Information Center

Tay, Louis; Huang, Qiming; Vermunt, Jeroen K.

2016-01-01

In large-scale testing, the use of multigroup approaches is limited for assessing differential item functioning (DIF) across multiple variables as DIF is examined for each variable separately. In contrast, the item response theory with covariate (IRT-C) procedure can be used to examine DIF across multiple variables (covariates) simultaneously. To…

Adaptive Quadrature for Item Response Models. Research Report. ETS RR-06-29

ERIC Educational Resources Information Center

Haberman, Shelby J.

2006-01-01

Adaptive quadrature is applied to marginal maximum likelihood estimation for item response models with normal ability distributions. Even in one dimension, significant gains in speed and accuracy of computation may be achieved.

Application of Item Response Theory to Tests of Substance-related Associative Memory

PubMed Central

Shono, Yusuke; Grenard, Jerry L.; Ames, Susan L.; Stacy, Alan W.

2015-01-01

A substance-related word association test (WAT) is one of the commonly used indirect tests of substance-related implicit associative memory and has been shown to predict substance use. This study applied an item response theory (IRT) modeling approach to evaluate psychometric properties of the alcohol- and marijuana-related WATs and their items among 775 ethnically diverse at-risk adolescents. After examining the IRT assumptions, item fit, and differential item functioning (DIF) across gender and age groups, the original 18 WAT items were reduced to 14- and 15-items in the alcohol- and marijuana-related WAT, respectively. Thereafter, unidimensional one- and two-parameter logistic models (1PL and 2PL models) were fitted to the revised WAT items. The results demonstrated that both alcohol- and marijuana-related WATs have good psychometric properties. These results were discussed in light of the framework of a unified concept of construct validity (Messick, 1975, 1989, 1995). PMID:25134051

Careful with Those Priors: A Note on Bayesian Estimation in Two-Parameter Logistic Item Response Theory Models

ERIC Educational Resources Information Center

Marcoulides, Katerina M.

2018-01-01

This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…

Applying Multidimensional Item Response Theory Models in Validating Test Dimensionality: An Example of K-12 Large-Scale Science Assessment

ERIC Educational Resources Information Center

Li, Ying; Jiao, Hong; Lissitz, Robert W.

2012-01-01

This study investigated the application of multidimensional item response theory (IRT) models to validate test structure and dimensionality. Multiple content areas or domains within a single subject often exist in large-scale achievement tests. Such areas or domains may cause multidimensionality or local item dependence, which both violate the…

Recovery of Item Parameters in the Nominal Response Model: A Comparison of Marginal Maximum Likelihood Estimation and Markov Chain Monte Carlo Estimation.

ERIC Educational Resources Information Center

Wollack, James A.; Bolt, Daniel M.; Cohen, Allan S.; Lee, Young-Sun

2002-01-01

Compared the quality of item parameter estimates for marginal maximum likelihood (MML) and Markov Chain Monte Carlo (MCMC) with the nominal response model using simulation. The quality of item parameter recovery was nearly identical for MML and MCMC, and both methods tended to produce good estimates. (SLD)

An NCME Instructional Module on Estimating Item Response Theory Models Using Markov Chain Monte Carlo Methods

ERIC Educational Resources Information Center

Kim, Jee-Seon; Bolt, Daniel M.

2007-01-01

The purpose of this ITEMS module is to provide an introduction to Markov chain Monte Carlo (MCMC) estimation for item response models. A brief description of Bayesian inference is followed by an overview of the various facets of MCMC algorithms, including discussion of prior specification, sampling procedures, and methods for evaluating chain…

Estimation of a Ramsay-Curve Item Response Theory Model by the Metropolis-Hastings Robbins-Monro Algorithm. CRESST Report 834

ERIC Educational Resources Information Center

Monroe, Scott; Cai, Li

2013-01-01

In Ramsay curve item response theory (RC-IRT, Woods & Thissen, 2006) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's (1981) EM algorithm, which yields maximum marginal likelihood estimates. This method, however,…

Estimation of a Ramsay-Curve Item Response Theory Model by the Metropolis-Hastings Robbins-Monro Algorithm

ERIC Educational Resources Information Center

Monroe, Scott; Cai, Li

2014-01-01

In Ramsay curve item response theory (RC-IRT) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's EM algorithm, which yields maximum marginal likelihood estimates. This method, however, does not produce the…

Psychometric analysis of the Generalized Anxiety Disorder scale (GAD-7) in primary care using modern item response theory.

PubMed

Jordan, Pascal; Shedden-Mora, Meike C; Löwe, Bernd

2017-01-01

The Generalized Anxiety Disorder scale (GAD-7) is one of the most frequently used diagnostic self-report scales for screening, diagnosis and severity assessment of anxiety disorder. Its psychometric properties from the view of the Item Response Theory paradigm have rarely been investigated. We aimed to close this gap by analyzing the GAD-7 within a large sample of primary care patients with respect to its psychometric properties and its implications for scoring using Item Response Theory. Robust, nonparametric statistics were used to check unidimensionality of the GAD-7. A graded response model was fitted using a Bayesian approach. The model fit was evaluated using posterior predictive p-values, item information functions were derived and optimal predictions of anxiety were calculated. The sample included N = 3404 primary care patients (60% female; mean age, 52,2; standard deviation 19.2) The analysis indicated no deviations of the GAD-7 scale from unidimensionality and a decent fit of a graded response model. The commonly suggested ultra-brief measure consisting of the first two items, the GAD-2, was supported by item information analysis. The first four items discriminated better than the last three items with respect to latent anxiety. The information provided by the first four items should be weighted more heavily. Moreover, estimates corresponding to low to moderate levels of anxiety show greater variability. The psychometric validity of the GAD-2 was supported by our analysis.

Psychometric analysis of the Generalized Anxiety Disorder scale (GAD-7) in primary care using modern item response theory

PubMed Central

Shedden-Mora, Meike C.; Löwe, Bernd

2017-01-01

Objective The Generalized Anxiety Disorder scale (GAD-7) is one of the most frequently used diagnostic self-report scales for screening, diagnosis and severity assessment of anxiety disorder. Its psychometric properties from the view of the Item Response Theory paradigm have rarely been investigated. We aimed to close this gap by analyzing the GAD-7 within a large sample of primary care patients with respect to its psychometric properties and its implications for scoring using Item Response Theory. Methods Robust, nonparametric statistics were used to check unidimensionality of the GAD-7. A graded response model was fitted using a Bayesian approach. The model fit was evaluated using posterior predictive p-values, item information functions were derived and optimal predictions of anxiety were calculated. Results The sample included N = 3404 primary care patients (60% female; mean age, 52,2; standard deviation 19.2) The analysis indicated no deviations of the GAD-7 scale from unidimensionality and a decent fit of a graded response model. The commonly suggested ultra-brief measure consisting of the first two items, the GAD-2, was supported by item information analysis. The first four items discriminated better than the last three items with respect to latent anxiety. Conclusion The information provided by the first four items should be weighted more heavily. Moreover, estimates corresponding to low to moderate levels of anxiety show greater variability. The psychometric validity of the GAD-2 was supported by our analysis. PMID:28771530

A comparison of item response models for accuracy and speed of item responses with applications to adaptive testing.

PubMed

van Rijn, Peter W; Ali, Usama S

2017-05-01

We compare three modelling frameworks for accuracy and speed of item responses in the context of adaptive testing. The first framework is based on modelling scores that result from a scoring rule that incorporates both accuracy and speed. The second framework is the hierarchical modelling approach developed by van der Linden (2007, Psychometrika, 72, 287) in which a regular item response model is specified for accuracy and a log-normal model for speed. The third framework is the diffusion framework in which the response is assumed to be the result of a Wiener process. Although the three frameworks differ in the relation between accuracy and speed, one commonality is that the marginal model for accuracy can be simplified to the two-parameter logistic model. We discuss both conditional and marginal estimation of model parameters. Models from all three frameworks were fitted to data from a mathematics and spelling test. Furthermore, we applied a linear and adaptive testing mode to the data off-line in order to determine differences between modelling frameworks. It was found that a model from the scoring rule framework outperformed a hierarchical model in terms of model-based reliability, but the results were mixed with respect to correlations with external measures. © 2017 The British Psychological Society.

Validity of Multiprocess IRT Models for Separating Content and Response Styles

ERIC Educational Resources Information Center

Plieninger, Hansjörg; Meiser, Thorsten

2014-01-01

Response styles, the tendency to respond to Likert-type items irrespective of content, are a widely known threat to the reliability and validity of self-report measures. However, it is still debated how to measure and control for response styles such as extreme responding. Recently, multiprocess item response theory models have been proposed that…

An Item Response Theory Model for Test Bias.

ERIC Educational Resources Information Center

Shealy, Robin; Stout, William

This paper presents a conceptualization of test bias for standardized ability tests which is based on multidimensional, non-parametric, item response theory. An explanation of how individually-biased items can combine through a test score to produce test bias is provided. It is contended that bias, although expressed at the item level, should be…

Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

NASA Astrophysics Data System (ADS)

Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

2016-12-01

This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC) that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test's distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

A Generalized Partial Credit Model: Application of an EM Algorithm.

ERIC Educational Resources Information Center

Muraki, Eiji

1992-01-01

The partial credit model with a varying slope parameter is developed and called the generalized partial credit model (GPCM). Analysis results for simulated data by this and other polytomous item-response models demonstrate that the rating formulation of the GPCM is adaptable to the analysis of polytomous item responses. (SLD)

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.

2010-01-01

Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…

Analyzing Multiple-Choice Questions by Model Analysis and Item Response Curves

NASA Astrophysics Data System (ADS)

Wattanakasiwich, P.; Ananta, S.

2010-07-01

In physics education research, the main goal is to improve physics teaching so that most students understand physics conceptually and be able to apply concepts in solving problems. Therefore many multiple-choice instruments were developed to probe students' conceptual understanding in various topics. Two techniques including model analysis and item response curves were used to analyze students' responses from Force and Motion Conceptual Evaluation (FMCE). For this study FMCE data from more than 1000 students at Chiang Mai University were collected over the past three years. With model analysis, we can obtain students' alternative knowledge and the probabilities for students to use such knowledge in a range of equivalent contexts. The model analysis consists of two algorithms—concentration factor and model estimation. This paper only presents results from using the model estimation algorithm to obtain a model plot. The plot helps to identify a class model state whether it is in the misconception region or not. Item response curve (IRC) derived from item response theory is a plot between percentages of students selecting a particular choice versus their total score. Pros and cons of both techniques are compared and discussed.

A Multidimensional Item Response Model: Constrained Latent Class Analysis Using the Gibbs Sampler and Posterior Predictive Checks.

ERIC Educational Resources Information Center

Hoijtink, Herbert; Molenaar, Ivo W.

1997-01-01

This paper shows that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. Parameters of this latent class model are estimated using an application of the Gibbs sampler, and model fit is investigated using posterior predictive checks. (SLD)

Assessing the Utility of Item Response Theory Models: Differential Item Functioning.

ERIC Educational Resources Information Center

Scheuneman, Janice Dowd

The current status of item response theory (IRT) is discussed. Several IRT methods exist for assessing whether an item is biased. Focus is on methods proposed by L. M. Rudner (1975), F. M. Lord (1977), D. Thissen et al. (1988) and R. L. Linn and D. Harnisch (1981). Rudner suggested a measure of the area lying between the two item characteristic…

Simulation-based Bayesian inference for latent traits of item response models: Introduction to the ltbayes package for R.

PubMed

Johnson, Timothy R; Kuhn, Kristine M

2015-12-01

This paper introduces the ltbayes package for R. This package includes a suite of functions for investigating the posterior distribution of latent traits of item response models. These include functions for simulating realizations from the posterior distribution, profiling the posterior density or likelihood function, calculation of posterior modes or means, Fisher information functions and observed information, and profile likelihood confidence intervals. Inferences can be based on individual response patterns or sets of response patterns such as sum scores. Functions are included for several common binary and polytomous item response models, but the package can also be used with user-specified models. This paper introduces some background and motivation for the package, and includes several detailed examples of its use.

Estimating a Noncompensatory IRT Model Using Metropolis within Gibbs Sampling

ERIC Educational Resources Information Center

Babcock, Ben

2011-01-01

Relatively little research has been conducted with the noncompensatory class of multidimensional item response theory (MIRT) models. A Monte Carlo simulation study was conducted exploring the estimation of a two-parameter noncompensatory item response theory (IRT) model. The estimation method used was a Metropolis-Hastings within Gibbs algorithm…

Order-Constrained Bayes Inference for Dichotomous Models of Unidimensional Nonparametric IRT

ERIC Educational Resources Information Center

Karabatsos, George; Sheu, Ching-Fan

2004-01-01

This study introduces an order-constrained Bayes inference framework useful for analyzing data containing dichotomous scored item responses, under the assumptions of either the monotone homogeneity model or the double monotonicity model of nonparametric item response theory (NIRT). The framework involves the implementation of Gibbs sampling to…

The Performance of IRT Model Selection Methods with Mixed-Format Tests

ERIC Educational Resources Information Center

Whittaker, Tiffany A.; Chang, Wanchen; Dodd, Barbara G.

2012-01-01

When tests consist of multiple-choice and constructed-response items, researchers are confronted with the question of which item response theory (IRT) model combination will appropriately represent the data collected from these mixed-format tests. This simulation study examined the performance of six model selection criteria, including the…

Assessment of health surveys: fitting a multidimensional graded response model.

PubMed

Depaoli, Sarah; Tiemensma, Jitske; Felt, John M

The multidimensional graded response model, an item response theory (IRT) model, can be used to improve the assessment of surveys, even when sample sizes are restricted. Typically, health-based survey development utilizes classical statistical techniques (e.g. reliability and factor analysis). In a review of four prominent journals within the field of Health Psychology, we found that IRT-based models were used in less than 10% of the studies examining scale development or assessment. However, implementing IRT-based methods can provide more details about individual survey items, which is useful when determining the final item content of surveys. An example using a quality of life survey for Cushing's syndrome (CushingQoL) highlights the main components for implementing the multidimensional graded response model. Patients with Cushing's syndrome (n = 397) completed the CushingQoL. Results from the multidimensional graded response model supported a 2-subscale scoring process for the survey. All items were deemed as worthy contributors to the survey. The graded response model can accommodate unidimensional or multidimensional scales, be used with relatively lower sample sizes, and is implemented in free software (example code provided in online Appendix). Use of this model can help to improve the quality of health-based scales being developed within the Health Sciences.

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions.

PubMed

Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

2016-01-01

This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability.

Investigating the Impact of Item Parameter Drift for Item Response Theory Models with Mixture Distributions

PubMed Central

Park, Yoon Soo; Lee, Young-Sun; Xing, Kuan

2016-01-01

This study investigates the impact of item parameter drift (IPD) on parameter and ability estimation when the underlying measurement model fits a mixture distribution, thereby violating the item invariance property of unidimensional item response theory (IRT) models. An empirical study was conducted to demonstrate the occurrence of both IPD and an underlying mixture distribution using real-world data. Twenty-one trended anchor items from the 1999, 2003, and 2007 administrations of Trends in International Mathematics and Science Study (TIMSS) were analyzed using unidimensional and mixture IRT models. TIMSS treats trended anchor items as invariant over testing administrations and uses pre-calibrated item parameters based on unidimensional IRT. However, empirical results showed evidence of two latent subgroups with IPD. Results also showed changes in the distribution of examinee ability between latent classes over the three administrations. A simulation study was conducted to examine the impact of IPD on the estimation of ability and item parameters, when data have underlying mixture distributions. Simulations used data generated from a mixture IRT model and estimated using unidimensional IRT. Results showed that data reflecting IPD using mixture IRT model led to IPD in the unidimensional IRT model. Changes in the distribution of examinee ability also affected item parameters. Moreover, drift with respect to item discrimination and distribution of examinee ability affected estimates of examinee ability. These findings demonstrate the need to caution and evaluate IPD using a mixture IRT framework to understand its effects on item parameters and examinee ability. PMID:26941699

A Combined IRT and SEM Approach for Individual-Level Assessment in Test-Retest Studies

ERIC Educational Resources Information Center

Ferrando, Pere J.

2015-01-01

The standard two-wave multiple-indicator model (2WMIM) commonly used to analyze test-retest data provides information at both the group and item level. Furthermore, when applied to binary and graded item responses, it is related to well-known item response theory (IRT) models. In this article the IRT-2WMIM relations are used to obtain additional…

On an Extension of the Rasch Model to the Case of Polychotomously Scored Items.

ERIC Educational Resources Information Center

Vogt, Dorothee K.

The Rasch model for the probability of a person's response to an item is extended to the case where this response depends on a set of scoring or category weights, in addition to person and item parameters. The maximum likelihood approach introduced by Wright for the dichotomous case is applicable here also, and it is shown to yield a unique…

Effect of Differential Item Functioning on Test Equating

ERIC Educational Resources Information Center

Kabasakal, Kübra Atalay; Kelecioglu, Hülya

2015-01-01

This study examines the effect of differential item functioning (DIF) items on test equating through multilevel item response models (MIRMs) and traditional IRMs. The performances of three different equating models were investigated under 24 different simulation conditions, and the variables whose effects were examined included sample size, test…

Equal Area Logistic Estimation for Item Response Theory

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching; Wang, Kuo-Chang; Chang, Hsin-Li

2009-08-01

Item response theory (IRT) models use logistic functions exclusively as item response functions (IRFs). Applications of IRT models require obtaining the set of values for logistic function parameters that best fit an empirical data set. However, success in obtaining such set of values does not guarantee that the constructs they represent actually exist, for the adequacy of a model is not sustained by the possibility of estimating parameters. In this study, an equal area based two-parameter logistic model estimation algorithm is proposed. Two theorems are given to prove that the results of the algorithm are equivalent to the results of fitting data by logistic model. Numerical results are presented to show the stability and accuracy of the algorithm.

A model for incomplete longitudinal multivariate ordinal data.

PubMed

Liu, Li C

2008-12-30

In studies where multiple outcome items are repeatedly measured over time, missing data often occur. A longitudinal item response theory model is proposed for analysis of multivariate ordinal outcomes that are repeatedly measured. Under the MAR assumption, this model accommodates missing data at any level (missing item at any time point and/or missing time point). It allows for multiple random subject effects and the estimation of item discrimination parameters for the multiple outcome items. The covariates in the model can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is described utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher-scoring solution, which provides standard errors for all model parameters, is used. A data set from a longitudinal prevention study is used to motivate the application of the proposed model. In this study, multiple ordinal items of health behavior are repeatedly measured over time. Because of a planned missing design, subjects answered only two-third of all items at a given point. Copyright 2008 John Wiley & Sons, Ltd.

Better assessment of physical function: item improvement is neglected but essential

PubMed Central

2009-01-01

Introduction Physical function is a key component of patient-reported outcome (PRO) assessment in rheumatology. Modern psychometric methods, such as Item Response Theory (IRT) and Computerized Adaptive Testing, can materially improve measurement precision at the item level. We present the qualitative and quantitative item-evaluation process for developing the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function item bank. Methods The process was stepwise: we searched extensively to identify extant Physical Function items and then classified and selectively reduced the item pool. We evaluated retained items for content, clarity, relevance and comprehension, reading level, and translation ease by experts and patient surveys, focus groups, and cognitive interviews. We then assessed items by using classic test theory and IRT, used confirmatory factor analyses to estimate item parameters, and graded response modeling for parameter estimation. We retained the 20 Legacy (original) Health Assessment Questionnaire Disability Index (HAQ-DI) and the 10 SF-36's PF-10 items for comparison. Subjects were from rheumatoid arthritis, osteoarthritis, and healthy aging cohorts (n = 1,100) and a national Internet sample of 21,133 subjects. Results We identified 1,860 items. After qualitative and quantitative evaluation, 124 newly developed PROMIS items composed the PROMIS item bank, which included revised Legacy items with good fit that met IRT model assumptions. Results showed that the clearest and best-understood items were simple, in the present tense, and straightforward. Basic tasks (like dressing) were more relevant and important versus complex ones (like dancing). Revised HAQ-DI and PF-10 items with five response options had higher item-information content than did comparable original Legacy items with fewer response options. IRT analyses showed that the Physical Function domain satisfied general criteria for unidimensionality with one-, two-, three-, and four-factor models having comparable model fits. Correlations between factors in the test data sets were > 0.90. Conclusions Item improvement must underlie attempts to improve outcome assessment. The clear, personally important and relevant, ability-framed items in the PROMIS Physical Function item bank perform well in PRO assessment. They will benefit from further study and application in a wider variety of rheumatic diseases in diverse clinical groups, including those at the extremes of physical functioning, and in different administration modes. PMID:20015354

Better assessment of physical function: item improvement is neglected but essential.

PubMed

Bruce, Bonnie; Fries, James F; Ambrosini, Debbie; Lingala, Bharathi; Gandek, Barbara; Rose, Matthias; Ware, John E

2009-01-01

Physical function is a key component of patient-reported outcome (PRO) assessment in rheumatology. Modern psychometric methods, such as Item Response Theory (IRT) and Computerized Adaptive Testing, can materially improve measurement precision at the item level. We present the qualitative and quantitative item-evaluation process for developing the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function item bank. The process was stepwise: we searched extensively to identify extant Physical Function items and then classified and selectively reduced the item pool. We evaluated retained items for content, clarity, relevance and comprehension, reading level, and translation ease by experts and patient surveys, focus groups, and cognitive interviews. We then assessed items by using classic test theory and IRT, used confirmatory factor analyses to estimate item parameters, and graded response modeling for parameter estimation. We retained the 20 Legacy (original) Health Assessment Questionnaire Disability Index (HAQ-DI) and the 10 SF-36's PF-10 items for comparison. Subjects were from rheumatoid arthritis, osteoarthritis, and healthy aging cohorts (n = 1,100) and a national Internet sample of 21,133 subjects. We identified 1,860 items. After qualitative and quantitative evaluation, 124 newly developed PROMIS items composed the PROMIS item bank, which included revised Legacy items with good fit that met IRT model assumptions. Results showed that the clearest and best-understood items were simple, in the present tense, and straightforward. Basic tasks (like dressing) were more relevant and important versus complex ones (like dancing). Revised HAQ-DI and PF-10 items with five response options had higher item-information content than did comparable original Legacy items with fewer response options. IRT analyses showed that the Physical Function domain satisfied general criteria for unidimensionality with one-, two-, three-, and four-factor models having comparable model fits. Correlations between factors in the test data sets were > 0.90. Item improvement must underlie attempts to improve outcome assessment. The clear, personally important and relevant, ability-framed items in the PROMIS Physical Function item bank perform well in PRO assessment. They will benefit from further study and application in a wider variety of rheumatic diseases in diverse clinical groups, including those at the extremes of physical functioning, and in different administration modes.

Differential item functioning magnitude and impact measures from item response theory models.

PubMed

Kleinman, Marjorie; Teresi, Jeanne A

2016-01-01

Measures of magnitude and impact of differential item functioning (DIF) at the item and scale level, respectively are presented and reviewed in this paper. Most measures are based on item response theory models. Magnitude refers to item level effect sizes, whereas impact refers to differences between groups at the scale score level. Reviewed are magnitude measures based on group differences in the expected item scores and impact measures based on differences in the expected scale scores. The similarities among these indices are demonstrated. Various software packages are described that provide magnitude and impact measures, and new software presented that computes all of the available statistics conveniently in one program with explanations of their relationships to one another.

Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory

ERIC Educational Resources Information Center

Bergner, Yoav; Droschler, Stefan; Kortemeyer, Gerd; Rayyan, Saif; Seaton, Daniel; Pritchard, David E.

2012-01-01

We apply collaborative filtering (CF) to dichotomously scored student response data (right, wrong, or no interaction), finding optimal parameters for each student and item based on cross-validated prediction accuracy. The approach is naturally suited to comparing different models, both unidimensional and multidimensional in ability, including a…

Applying the Nominal Response Model within a Longitudinal Framework to Construct the Positive Family Relationships Scale

ERIC Educational Resources Information Center

Preston, Kathleen Suzanne Johnson; Parral, Skye N.; Gottfried, Allen W.; Oliver, Pamella H.; Gottfried, Adele Eskeles; Ibrahim, Sirena M.; Delany, Danielle

2015-01-01

A psychometric analysis was conducted using the nominal response model under the item response theory framework to construct the Positive Family Relationships scale. Using data from the Fullerton Longitudinal Study, this scale was constructed within a long-term longitudinal framework spanning middle childhood through adolescence. Items tapping…

A new item response theory model to adjust data allowing examinee choice

PubMed Central

Costa, Marcelo Azevedo; Braga Oliveira, Rivert Paulo

2018-01-01

In a typical questionnaire testing situation, examinees are not allowed to choose which items they answer because of a technical issue in obtaining satisfactory statistical estimates of examinee ability and item difficulty. This paper introduces a new item response theory (IRT) model that incorporates information from a novel representation of questionnaire data using network analysis. Three scenarios in which examinees select a subset of items were simulated. In the first scenario, the assumptions required to apply the standard Rasch model are met, thus establishing a reference for parameter accuracy. The second and third scenarios include five increasing levels of violating those assumptions. The results show substantial improvements over the standard model in item parameter recovery. Furthermore, the accuracy was closer to the reference in almost every evaluated scenario. To the best of our knowledge, this is the first proposal to obtain satisfactory IRT statistical estimates in the last two scenarios. PMID:29389996

Generalized IRT Models for Extreme Response Style

ERIC Educational Resources Information Center

Jin, Kuan-Yu; Wang, Wen-Chung

2014-01-01

Extreme response style (ERS) is a systematic tendency for a person to endorse extreme options (e.g., strongly disagree, strongly agree) on Likert-type or rating-scale items. In this study, we develop a new class of item response theory (IRT) models to account for ERS so that the target latent trait is free from the response style and the tendency…

The effect of response modality on immediate serial recall in dementia of the Alzheimer type.

PubMed

Macé, Anne-Laure; Ergis, Anne-Marie; Caza, Nicole

2012-09-01

Contrary to traditional models of verbal short-term memory (STM), psycholinguistic accounts assume that temporary retention of verbal materials is an intrinsic property of word processing. Therefore, memory performance will depend on the nature of the STM tasks, which vary according to the linguistic representations they engage. The aim of this study was to explore the effect of response modality on verbal STM performance in individuals with dementia of the Alzheimer Type (DAT), and its relationship with the patients' word-processing deficits. Twenty individuals with mild DAT and 20 controls were tested on an immediate serial recall (ISR) task using the same items across two response modalities (oral and picture pointing) and completed a detailed language assessment. When scoring of ISR performance was based on item memory regardless of item order, a response modality effect was found for all participants, indicating that they recalled more items with picture pointing than with oral response. However, this effect was less marked in patients than in controls, resulting in an interaction. Interestingly, when recall of both item and order was considered, results indicated similar performance between response modalities in controls, whereas performance was worse for pointing than for oral response in patients. Picture-naming performance was also reduced in patients relative to controls. However, in the word-to-picture matching task, a similar pattern of responses was found between groups for incorrectly named pictures of the same items. The finding of a response modality effect in item memory for all participants is compatible with the assumption that semantic influences are greater in picture pointing than in oral response, as predicted by psycholinguistic models. Furthermore, patients' performance was modulated by their word-processing deficits, showing a reduced advantage relative to controls. Overall, the response modality effect observed in this study for item memory suggests that verbal STM performance is intrinsically linked with word processing capacities in both healthy controls and individuals with mild DAT, supporting psycholinguistic models of STM.

Bayesian Modal Estimation of the Four-Parameter Item Response Model in Real, Realistic, and Idealized Data Sets.

PubMed

Waller, Niels G; Feuerstahler, Leah

2017-01-01

In this study, we explored item and person parameter recovery of the four-parameter model (4PM) in over 24,000 real, realistic, and idealized data sets. In the first analyses, we fit the 4PM and three alternative models to data from three Minnesota Multiphasic Personality Inventory-Adolescent form factor scales using Bayesian modal estimation (BME). Our results indicated that the 4PM fits these scales better than simpler item Response Theory (IRT) models. Next, using the parameter estimates from these real data analyses, we estimated 4PM item parameters in 6,000 realistic data sets to establish minimum sample size requirements for accurate item and person parameter recovery. Using a factorial design that crossed discrete levels of item parameters, sample size, and test length, we also fit the 4PM to an additional 18,000 idealized data sets to extend our parameter recovery findings. Our combined results demonstrated that 4PM item parameters and parameter functions (e.g., item response functions) can be accurately estimated using BME in moderate to large samples (N ⩾ 5, 000) and person parameters can be accurately estimated in smaller samples (N ⩾ 1, 000). In the supplemental files, we report annotated [Formula: see text] code that shows how to estimate 4PM item and person parameters in [Formula: see text] (Chalmers, 2012 ).

The Robustness of LOGIST and BILOG IRT Estimation Programs to Violations of Local Independence.

ERIC Educational Resources Information Center

Ackerman, Terry A.

One of the important underlying assumptions of all item response theory (IRT) models is that of local independence. This assumption requires that the response to an item on a test not be influenced by the response to any other items. This assumption is often taken for granted, with little or no scrutiny of the response process required to answer…

How Often Is the Misfit of Item Response Theory Models Practically Significant?

ERIC Educational Resources Information Center

Sinharay, Sandip; Haberman, Shelby J.

2014-01-01

Standard 3.9 of the Standards for Educational and Psychological Testing ([, 1999]) demands evidence of model fit when item response theory (IRT) models are employed to data from tests. Hambleton and Han ([Hambleton, R. K., 2005]) and Sinharay ([Sinharay, S., 2005]) recommended the assessment of practical significance of misfit of IRT models, but…

Evaluation of the Multiple Sclerosis Walking Scale-12 (MSWS-12) in a Dutch sample: Application of item response theory.

PubMed

Mokkink, Lidwine Brigitta; Galindo-Garre, Francisca; Uitdehaag, Bernard Mj

2016-12-01

The Multiple Sclerosis Walking Scale-12 (MSWS-12) measures walking ability from the patients' perspective. We examined the quality of the MSWS-12 using an item response theory model, the graded response model (GRM). A total of 625 unique Dutch multiple sclerosis (MS) patients were included. After testing for unidimensionality, monotonicity, and absence of local dependence, a GRM was fit and item characteristics were assessed. Differential item functioning (DIF) for the variables gender, age, duration of MS, type of MS and severity of MS, reliability, total test information, and standard error of the trait level (θ) were investigated. Confirmatory factor analysis showed a unidimensional structure of the 12 items of the scale, explaining 88% of the variance. Item 2 did not fit into the GRM model. Reliability was 0.93. Items 8 and 9 (of the 11 and 12 item version respectively) showed DIF on the variable severity, based on the Expanded Disability Status Scale (EDSS). However, the EDSS is strongly related to the content of both items. Our results confirm the good quality of the MSWS-12. The trait level (θ) scores and item parameters of both the 12- and 11-item versions were highly comparable, although we do not suggest to change the content of the MSWS-12. © The Author(s), 2016.

A new course and textbook on Physical Models of Living Systems, for science and engineering undergraduates

NASA Astrophysics Data System (ADS)

Nelson, Philip

2015-03-01

I'll describe an intermediate-level course on ``Physical Models of Living Systems.'' The only prerequisite is first-year university physics and calculus. The course is a response to rapidly growing interest among undergraduates in a broad range of science and engineering majors. Students acquire several research skills that are often not addressed in traditional courses: Basic modeling skills Probabilistic modeling skills Data analysis methods Computer programming using a general-purpose platform like MATLAB or Python Dynamical systems, particularly feedback control. These basic skills, which are relevant to nearly any field of science or engineering, are presented in the context of case studies from living systems, including: Virus dynamics Bacterial genetics and evolution of drug resistance Statistical inference Superresolution microscopy Synthetic biology Naturally evolved cellular circuits. Work supported by NSF Grants EF-0928048 and DMR-0832802.

A Comparison of Measurement Equivalence Methods Based on Confirmatory Factor Analysis and Item Response Theory.

ERIC Educational Resources Information Center

Flowers, Claudia P.; Raju, Nambury S.; Oshima, T. C.

Current interest in the assessment of measurement equivalence emphasizes two methods of analysis, linear, and nonlinear procedures. This study simulated data using the graded response model to examine the performance of linear (confirmatory factor analysis or CFA) and nonlinear (item-response-theory-based differential item function or IRT-Based…

The Role of Psychometric Modeling in Test Validation: An Application of Multidimensional Item Response Theory

ERIC Educational Resources Information Center

Schilling, Stephen G.

2007-01-01

In this paper the author examines the role of item response theory (IRT), particularly multidimensional item response theory (MIRT) in test validation from a validity argument perspective. The author provides justification for several structural assumptions and interpretations, taking care to describe the role he believes they should play in any…

Exploring the Robustness of a Unidimensional Item Response Theory Model with Empirically Multidimensional Data

ERIC Educational Resources Information Center

Anderson, Daniel; Kahn, Joshua D.; Tindal, Gerald

2017-01-01

Unidimensionality and local independence are two common assumptions of item response theory. The former implies that all items measure a common latent trait, while the latter implies that responses are independent, conditional on respondents' location on the latent trait. Yet, few tests are truly unidimensional. Unmodeled dimensions may result in…

Using Rasch rating scale model to reassess the psychometric properties of the Persian version of the PedsQLTM 4.0 Generic Core Scales in school children

PubMed Central

2012-01-01

Background Item response theory (IRT) is extensively used to develop adaptive instruments of health-related quality of life (HRQoL). However, each IRT model has its own function to estimate item and category parameters, and hence different results may be found using the same response categories with different IRT models. The present study used the Rasch rating scale model (RSM) to examine and reassess the psychometric properties of the Persian version of the PedsQLTM 4.0 Generic Core Scales. Methods The PedsQLTM 4.0 Generic Core Scales was completed by 938 Iranian school children and their parents. Convergent, discriminant and construct validity of the instrument were assessed by classical test theory (CTT). The RSM was applied to investigate person and item reliability, item statistics and ordering of response categories. Results The CTT method showed that the scaling success rate for convergent and discriminant validity were 100% in all domains with the exception of physical health in the child self-report. Moreover, confirmatory factor analysis supported a four-factor model similar to its original version. The RSM showed that 22 out of 23 items had acceptable infit and outfit statistics (<1.4, >0.6), person reliabilities were low, item reliabilities were high, and item difficulty ranged from -1.01 to 0.71 and -0.68 to 0.43 for child self-report and parent proxy-report, respectively. Also the RSM showed that successive response categories for all items were not located in the expected order. Conclusions This study revealed that, in all domains, the five response categories did not perform adequately. It is not known whether this problem is a function of the meaning of the response choices in the Persian language or an artifact of a mostly healthy population that did not use the full range of the response categories. The response categories should be evaluated in further validation studies, especially in large samples of chronically ill patients. PMID:22414135

A Framework for Dimensionality Assessment for Multidimensional Item Response Models

ERIC Educational Resources Information Center

Svetina, Dubravka; Levy, Roy

2014-01-01

A framework is introduced for considering dimensionality assessment procedures for multidimensional item response models. The framework characterizes procedures in terms of their confirmatory or exploratory approach, parametric or nonparametric assumptions, and applicability to dichotomous, polytomous, and missing data. Popular and emerging…

Fitting Item Response Theory Models to Two Personality Inventories: Issues and Insights.

PubMed

Chernyshenko, O S; Stark, S; Chan, K Y; Drasgow, F; Williams, B

2001-10-01

The present study compared the fit of several IRT models to two personality assessment instruments. Data from 13,059 individuals responding to the US-English version of the Fifth Edition of the Sixteen Personality Factor Questionnaire (16PF) and 1,770 individuals responding to Goldberg's 50 item Big Five Personality measure were analyzed. Various issues pertaining to the fit of the IRT models to personality data were considered. We examined two of the most popular parametric models designed for dichotomously scored items (i.e., the two- and three-parameter logistic models) and a parametric model for polytomous items (Samejima's graded response model). Also examined were Levine's nonparametric maximum likelihood formula scoring models for dichotomous and polytomous data, which were previously found to provide good fits to several cognitive ability tests (Drasgow, Levine, Tsien, Williams, & Mead, 1995). The two- and three-parameter logistic models fit some scales reasonably well but not others; the graded response model generally did not fit well. The nonparametric formula scoring models provided the best fit of the models considered. Several implications of these findings for personality measurement and personnel selection were described.

An Application of Unfolding and Cumulative Item Response Theory Models for Noncognitive Scaling: Examining the Assumptions and Applicability of the Generalized Graded Unfolding Model

ERIC Educational Resources Information Center

Sgammato, Adrienne N.

2009-01-01

This study examined the applicability of a relatively new unidimensional, unfolding item response theory (IRT) model called the generalized graded unfolding model (GGUM; Roberts, Donoghue, & Laughlin, 2000). A total of four scaling methods were applied. Two commonly used cumulative IRT models for polytomous data, the Partial Credit Model and…

Assessing Goodness of Fit in Item Response Theory with Nonparametric Models: A Comparison of Posterior Probabilities and Kernel-Smoothing Approaches

ERIC Educational Resources Information Center

Sueiro, Manuel J.; Abad, Francisco J.

2011-01-01

The distance between nonparametric and parametric item characteristic curves has been proposed as an index of goodness of fit in item response theory in the form of a root integrated squared error index. This article proposes to use the posterior distribution of the latent trait as the nonparametric model and compares the performance of an index…

Goodness-of-Fit Assessment of Item Response Theory Models

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto

2013-01-01

The article provides an overview of goodness-of-fit assessment methods for item response theory (IRT) models. It is now possible to obtain accurate "p"-values of the overall fit of the model if bivariate information statistics are used. Several alternative approaches are described. As the validity of inferences drawn on the fitted model…

Separability of Item and Person Parameters in Response Time Models.

ERIC Educational Resources Information Center

Van Breukelen, Gerard J. P.

1997-01-01

Discusses two forms of separability of item and person parameters in the context of response time models. The first is "separate sufficiency," and the second is "ranking independence." For each form a theorem stating sufficient conditions is proved. The two forms are shown to include several cases of models from psychometric…

The Asymptotic Distribution of Ability Estimates: Beyond Dichotomous Items and Unidimensional IRT Models

ERIC Educational Resources Information Center

Sinharay, Sandip

2015-01-01

The maximum likelihood estimate (MLE) of the ability parameter of an item response theory model with known item parameters was proved to be asymptotically normally distributed under a set of regularity conditions for tests involving dichotomous items and a unidimensional ability parameter (Klauer, 1990; Lord, 1983). This article first considers…

Item Vector Plots for the Multidimensional Three-Parameter Logistic Model

ERIC Educational Resources Information Center

Bryant, Damon; Davis, Larry

2011-01-01

This brief technical note describes how to construct item vector plots for dichotomously scored items fitting the multidimensional three-parameter logistic model (M3PLM). As multidimensional item response theory (MIRT) shows promise of being a very useful framework in the test development life cycle, graphical tools that facilitate understanding…

Item response theory analysis of Centers for Disease Control and Prevention Health-Related Quality of Life (CDC HRQOL) items in adults with arthritis.

PubMed

Mielenz, Thelma J; Callahan, Leigh F; Edwards, Michael C

2016-03-12

Examine the feasibility of performing an item response theory (IRT) analysis on two of the Centers for Disease Control and Prevention health-related quality of life (CDC HRQOL) modules - the 4-item Healthy Days Core Module (HDCM) and the 5-item Healthy days Symptoms Module (HDSM). Previous principal components analyses confirm that the two scales both assess a mix of mental (CDC-MH) and physical health (CDC-PH). The purpose is to conduct item response theory (IRT) analysis on the CDC-MH and CDC-PH scales separately. 2182 patients with self-reported or physician-diagnosed arthritis completed a cross-sectional survey including HDCM and HDSM items. Besides global health, the other 8 items ask the number of days that some statement was true; we chose to recode the data into 8 categories based on observed clustering. The IRT assumptions were assessed using confirmatory factor analysis and the data could be modeled using an unidimensional IRT model. The graded response model was used for IRT analyses and CDC-MH and CDC-PH scales were analyzed separately in flexMIRT. The IRT parameter estimates for the five-item CDC-PH all appeared reasonable. The three-item CDC-MH did not have reasonable parameter estimates. The CDC-PH scale is amenable to IRT analysis but the existing The CDC-MH scale is not. We suggest either using the 4-item Healthy Days Core Module (HDCM) and the 5-item Healthy days Symptoms Module (HDSM) as they currently stand or the CDC-PH scale alone if the primary goal is to measure physical health related HRQOL.

Generalized Full-Information Item Bifactor Analysis

PubMed Central

Cai, Li; Yang, Ji Seung; Hansen, Mark

2011-01-01

Full-information item bifactor analysis is an important statistical method in psychological and educational measurement. Current methods are limited to single group analysis and inflexible in the types of item response models supported. We propose a flexible multiple-group item bifactor analysis framework that supports a variety of multidimensional item response theory models for an arbitrary mixing of dichotomous, ordinal, and nominal items. The extended item bifactor model also enables the estimation of latent variable means and variances when data from more than one group are present. Generalized user-defined parameter restrictions are permitted within or across groups. We derive an efficient full-information maximum marginal likelihood estimator. Our estimation method achieves substantial computational savings by extending Gibbons and Hedeker’s (1992) bifactor dimension reduction method so that the optimization of the marginal log-likelihood only requires two-dimensional integration regardless of the dimensionality of the latent variables. We use simulation studies to demonstrate the flexibility and accuracy of the proposed methods. We apply the model to study cross-country differences, including differential item functioning, using data from a large international education survey on mathematics literacy. PMID:21534682

Item selection via Bayesian IRT models.

PubMed

Arima, Serena

2015-02-10

With reference to a questionnaire that aimed to assess the quality of life for dysarthric speakers, we investigate the usefulness of a model-based procedure for reducing the number of items. We propose a mixed cumulative logit model, which is known in the psychometrics literature as the graded response model: responses to different items are modelled as a function of individual latent traits and as a function of item characteristics, such as their difficulty and their discrimination power. We jointly model the discrimination and the difficulty parameters by using a k-component mixture of normal distributions. Mixture components correspond to disjoint groups of items. Items that belong to the same groups can be considered equivalent in terms of both difficulty and discrimination power. According to decision criteria, we select a subset of items such that the reduced questionnaire is able to provide the same information that the complete questionnaire provides. The model is estimated by using a Bayesian approach, and the choice of the number of mixture components is justified according to information criteria. We illustrate the proposed approach on the basis of data that are collected for 104 dysarthric patients by local health authorities in Lecce and in Milan. Copyright © 2014 John Wiley & Sons, Ltd.

Assessing the Evaluative Content of Personality Questionnaires Using Bifactor Models.

PubMed

Biderman, Michael D; McAbee, Samuel T; Job Chen, Zhuo; Hendy, Nhung T

2018-01-01

Exploratory bifactor models with keying factors were applied to item response data for the NEO-FFI-3 and HEXACO-PI-R questionnaires. Loadings on a general factor and positive and negative keying factors correlated with independent estimates of item valence, suggesting that item valence influences responses to these questionnaires. Correlations between personality domain scores and measures of self-esteem, depression, and positive and negative affect were all reduced significantly when the influence of evaluative content represented by the general and keying factors was removed. Findings support the need to model personality inventories in ways that capture reactions to evaluative item content.

A Third-Order Item Response Theory Model for Modeling the Effects of Domains and Subdomains in Large-Scale Educational Assessment Surveys

ERIC Educational Resources Information Center

Rijmen, Frank; Jeon, Minjeong; von Davier, Matthias; Rabe-Hesketh, Sophia

2014-01-01

Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…

Evaluation of Linking Methods for Placing Three-Parameter Logistic Item Parameter Estimates onto a One-Parameter Scale

ERIC Educational Resources Information Center

Karkee, Thakur B.; Wright, Karen R.

2004-01-01

Different item response theory (IRT) models may be employed for item calibration. Change of testing vendors, for example, may result in the adoption of a different model than that previously used with a testing program. To provide scale continuity and preserve cut score integrity, item parameter estimates from the new model must be linked to the…

Performance of the Generalized S-X[Superscript 2] Item Fit Index for Polytomous IRT Models

ERIC Educational Resources Information Center

Kang, Taehoon; Chen, Troy T.

2008-01-01

Orlando and Thissen's S-X[superscript 2] item fit index has performed better than traditional item fit statistics such as Yen' s Q[subscript 1] and McKinley and Mill' s G[superscript 2] for dichotomous item response theory (IRT) models. This study extends the utility of S-X[superscript 2] to polytomous IRT models, including the generalized partial…

A Multivariate Multilevel Approach to the Modeling of Accuracy and Speed of Test Takers

ERIC Educational Resources Information Center

Klein Entink, R. H.; Fox, J. P.; van der Linden, W. J.

2009-01-01

Response times on test items are easily collected in modern computerized testing. When collecting both (binary) responses and (continuous) response times on test items, it is possible to measure the accuracy and speed of test takers. To study the relationships between these two constructs, the model is extended with a multivariate multilevel…

A Study of General Education Astronomy Students' Understandings of Cosmology. Part III. Evaluating Four Conceptual Cosmology Surveys: An Item Response Theory Approach

ERIC Educational Resources Information Center

Wallace, Colin S.; Prather, Edward E.; Duncan, Douglas K.

2012-01-01

This is the third of five papers detailing our national study of general education astronomy students' conceptual and reasoning difficulties with cosmology. In this paper, we use item response theory to analyze students' responses to three out of the four conceptual cosmology surveys we developed. The specific item response theory model we use is…

Comparing the Fit of Item Response Theory and Factor Analysis Models

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto; Cai, Li; Hernandez, Adolfo

2011-01-01

Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be…

The linear transformation model with frailties for the analysis of item response times.

PubMed

Wang, Chun; Chang, Hua-Hua; Douglas, Jeffrey A

2013-02-01

The item response times (RTs) collected from computerized testing represent an underutilized source of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. In this paper, we propose a semi-parametric model for RTs, the linear transformation model with a latent speed covariate, which combines the flexibility of non-parametric modelling and the brevity as well as interpretability of parametric modelling. In this new model, the RTs, after some non-parametric monotone transformation, become a linear model with latent speed as covariate plus an error term. The distribution of the error term implicitly defines the relationship between the RT and examinees' latent speeds; whereas the non-parametric transformation is able to describe various shapes of RT distributions. The linear transformation model represents a rich family of models that includes the Cox proportional hazards model, the Box-Cox normal model, and many other models as special cases. This new model is embedded in a hierarchical framework so that both RTs and responses are modelled simultaneously. A two-stage estimation method is proposed. In the first stage, the Markov chain Monte Carlo method is employed to estimate the parametric part of the model. In the second stage, an estimating equation method with a recursive algorithm is adopted to estimate the non-parametric transformation. Applicability of the new model is demonstrated with a simulation study and a real data application. Finally, methods to evaluate the model fit are suggested. © 2012 The British Psychological Society.

Person Response Functions and the Definition of Units in the Social Sciences

ERIC Educational Resources Information Center

Engelhard, George, Jr.; Perkins, Aminah F.

2011-01-01

Humphry (this issue) has written a thought-provoking piece on the interpretation of item discrimination parameters as scale units in item response theory. One of the key features of his work is the description of an item response theory (IRT) model that he calls the logistic measurement function that combines aspects of two traditions in IRT that…

Bayesian Analysis of Item Response Curves. Research Report 84-1. Mathematical Sciences Technical Report No. 132.

ERIC Educational Resources Information Center

Tsutakawa, Robert K.; Lin, Hsin Ying

Item response curves for a set of binary responses are studied from a Bayesian viewpoint of estimating the item parameters. For the two-parameter logistic model with normally distributed ability, restricted bivariate beta priors are used to illustrate the computation of the posterior mode via the EM algorithm. The procedure is illustrated by data…

PROC IRT: A SAS Procedure for Item Response Theory

PubMed Central

Matlock Cole, Ki; Paek, Insu

2017-01-01

This article reviews the procedure for item response theory (PROC IRT) procedure in SAS/STAT 14.1 to conduct item response theory (IRT) analyses of dichotomous and polytomous datasets that are unidimensional or multidimensional. The review provides an overview of available features, including models, estimation procedures, interfacing, input, and output files. A small-scale simulation study evaluates the IRT model parameter recovery of the PROC IRT procedure. The use of the IRT procedure in Statistical Analysis Software (SAS) may be useful for researchers who frequently utilize SAS for analyses, research, and teaching.

Modified Likelihood-Based Item Fit Statistics for the Generalized Graded Unfolding Model

ERIC Educational Resources Information Center

Roberts, James S.

2008-01-01

Orlando and Thissen (2000) developed an item fit statistic for binary item response theory (IRT) models known as S-X[superscript 2]. This article generalizes their statistic to polytomous unfolding models. Four alternative formulations of S-X[superscript 2] are developed for the generalized graded unfolding model (GGUM). The GGUM is a…

Computerized Adaptive Testing with Item Clones. Research Report.

ERIC Educational Resources Information Center

Glas, Cees A. W.; van der Linden, Wim J.

To reduce the cost of item writing and to enhance the flexibility of item presentation, items can be generated by item-cloning techniques. An important consequence of cloning is that it may cause variability on the item parameters. Therefore, a multilevel item response model is presented in which it is assumed that the item parameters of a…

Quantifying traditional Chinese medicine patterns using modern test theory: an example of functional constipation.

PubMed

Shen, Minxue; Cui, Yuanwu; Hu, Ming; Xu, Linyong

2017-01-13

The study aimed to validate a scale to assess the severity of "Yin deficiency, intestine heat" pattern of functional constipation based on the modern test theory. Pooled longitudinal data of 237 patients with "Yin deficiency, intestine heat" pattern of constipation from a prospective cohort study were used to validate the scale. Exploratory factor analysis was used to examine the common factors of items. A multidimensional item response model was used to assess the scale with the presence of multidimensionality. The Cronbach's alpha ranged from 0.79 to 0.89, and the split-half reliability ranged from 0.67 to 0.79 at different measurements. Exploratory factor analysis identified two common factors, and all items had cross factor loadings. Bidimensional model had better goodness of fit than the unidimensional model. Multidimensional item response model showed that the all items had moderate to high discrimination parameters. Parameters indicated that the first latent trait signified intestine heat, while the second trait characterized Yin deficiency. Information function showed that items demonstrated highest discrimination power among patients with moderate to high level of disease severity. Multidimensional item response theory provides a useful and rational approach in validating scales for assessing the severity of patterns in traditional Chinese medicine.

Item response theory analysis of the Pain Self-Efficacy Questionnaire.

PubMed

Costa, Daniel S J; Asghari, Ali; Nicholas, Michael K

2017-01-01

The Pain Self-Efficacy Questionnaire (PSEQ) is a 10-item instrument designed to assess the extent to which a person in pain believes s/he is able to accomplish various activities despite their pain. There is strong evidence for the validity and reliability of both the full-length PSEQ and a 2-item version. The purpose of this study is to further examine the properties of the PSEQ using an item response theory (IRT) approach. We used the two-parameter graded response model to examine the category probability curves, and location and discrimination parameters of the 10 PSEQ items. In item response theory, responses to a set of items are assumed to be probabilistically determined by a latent (unobserved) variable. In the graded-response model specifically, item response threshold (the value of the latent variable for which adjacent response categories are equally likely) and discrimination parameters are estimated for each item. Participants were 1511 mixed, chronic pain patients attending for initial assessment at a tertiary pain management centre. All items except item 7 ('I can cope with my pain without medication') performed well in IRT analysis, and the category probability curves suggested that participants used the 7-point response scale consistently. Items 6 ('I can still do many of the things I enjoy doing, such as hobbies or leisure activity, despite pain'), 8 ('I can still accomplish most of my goals in life, despite the pain') and 9 ('I can live a normal lifestyle, despite the pain') captured higher levels of the latent variable with greater precision. The results from this IRT analysis add to the body of evidence based on classical test theory illustrating the strong psychometric properties of the PSEQ. Despite the relatively poor performance of Item 7, its clinical utility warrants its retention in the questionnaire. The strong psychometric properties of the PSEQ support its use as an effective tool for assessing self-efficacy in people with pain. Copyright © 2016 Scandinavian Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Practical Guide to Conducting an Item Response Theory Analysis

ERIC Educational Resources Information Center

Toland, Michael D.

2014-01-01

Item response theory (IRT) is a psychometric technique used in the development, evaluation, improvement, and scoring of multi-item scales. This pedagogical article provides the necessary information needed to understand how to conduct, interpret, and report results from two commonly used ordered polytomous IRT models (Samejima's graded…

Analyzing Longitudinal Item Response Data via the Pairwise Fitting Method

ERIC Educational Resources Information Center

Fu, Zhi-Hui; Tao, Jian; Shi, Ning-Zhong; Zhang, Ming; Lin, Nan

2011-01-01

Multidimensional item response theory (MIRT) models can be applied to longitudinal educational surveys where a group of individuals are administered different tests over time with some common items. However, computational problems typically arise as the dimension of the latent variables increases. This is especially true when the latent variable…

Item Construction and Psychometric Models Appropriate for Constructed Responses

DTIC Science & Technology

1991-08-01

which involve only one attribute per item. This is especially true when we are dealing with constructed-response items, we have to measure much more...Service University of Ilinois Educacional Testing Service Rosedal Road Capign. IL 61801 Princeton. K3 08541 Princeton. N3 08541 Dr. Charles LeiS Dr

Classification Consistency and Accuracy for Complex Assessments Using Item Response Theory

ERIC Educational Resources Information Center

Lee, Won-Chan

2010-01-01

In this article, procedures are described for estimating single-administration classification consistency and accuracy indices for complex assessments using item response theory (IRT). This IRT approach was applied to real test data comprising dichotomous and polytomous items. Several different IRT model combinations were considered. Comparisons…

Item Banking. ERIC/AE Digest.

ERIC Educational Resources Information Center

Rudner, Lawrence

This digest discusses the advantages and disadvantages of using item banks, and it provides useful information for those who are considering implementing an item banking project in their school districts. The primary advantage of item banking is in test development. Using an item response theory method, such as the Rasch model, items from multiple…

Taking the Missing Propensity into Account When Estimating Competence Scores: Evaluation of Item Response Theory Models for Nonignorable Omissions

ERIC Educational Resources Information Center

Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H.

2015-01-01

When competence tests are administered, subjects frequently omit items. These missing responses pose a threat to correctly estimating the proficiency level. Newer model-based approaches aim to take nonignorable missing data processes into account by incorporating a latent missing propensity into the measurement model. Two assumptions are typically…

Computing Maximum Likelihood Estimates of Loglinear Models from Marginal Sums with Special Attention to Loglinear Item Response Theory.

ERIC Educational Resources Information Center

Kelderman, Henk

1992-01-01

Describes algorithms used in the computer program LOGIMO for obtaining maximum likelihood estimates of the parameters in loglinear models. These algorithms are also useful for the analysis of loglinear item-response theory models. Presents modified versions of the iterative proportional fitting and Newton-Raphson algorithms. Simulated data…

Investigation of a Nonparametric Procedure for Assessing Goodness-of-Fit in Item Response Theory

ERIC Educational Resources Information Center

Wells, Craig S.; Bolt, Daniel M.

2008-01-01

Tests of model misfit are often performed to validate the use of a particular model in item response theory. Douglas and Cohen (2001) introduced a general nonparametric approach for detecting misfit under the two-parameter logistic model. However, the statistical properties of their approach, and empirical comparisons to other methods, have not…

An Introduction to Item Response Theory and Rasch Models for Speech-Language Pathologists

ERIC Educational Resources Information Center

Baylor, Carolyn; Hula, William; Donovan, Neila J.; Doyle, Patrick J.; Kendall, Diane; Yorkston, Kathryn

2011-01-01

Purpose: To present a primarily conceptual introduction to item response theory (IRT) and Rasch models for speech-language pathologists (SLPs). Method: This tutorial introduces SLPs to basic concepts and terminology related to IRT as well as the most common IRT models. The article then continues with an overview of how instruments are developed…

Detecting DIF in Polytomous Items Using MACS, IRT and Ordinal Logistic Regression

ERIC Educational Resources Information Center

Elosua, Paula; Wells, Craig

2013-01-01

The purpose of the present study was to compare the Type I error rate and power of two model-based procedures, the mean and covariance structure model (MACS) and the item response theory (IRT), and an observed-score based procedure, ordinal logistic regression, for detecting differential item functioning (DIF) in polytomous items. A simulation…

A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

ERIC Educational Resources Information Center

Edwards, Michael C.

2010-01-01

Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…

Confirming Testlet Effects

ERIC Educational Resources Information Center

DeMars, Christine E.

2012-01-01

A testlet is a cluster of items that share a common passage, scenario, or other context. These items might measure something in common beyond the trait measured by the test as a whole; if so, the model for the item responses should allow for this testlet trait. But modeling testlet effects that are negligible makes the model unnecessarily…

A Two-Parameter Latent Trait Model. Methodology Project.

ERIC Educational Resources Information Center

Choppin, Bruce

On well-constructed multiple-choice tests, the most serious threat to measurement is not variation in item discrimination, but the guessing behavior that may be adopted by some students. Ways of ameliorating the effects of guessing are discussed, especially for problems in latent trait models. A new item response model, including an item parameter…

IRT-ZIP Modeling for Multivariate Zero-Inflated Count Data

ERIC Educational Resources Information Center

Wang, Lijuan

2010-01-01

This study introduces an item response theory-zero-inflated Poisson (IRT-ZIP) model to investigate psychometric properties of multiple items and predict individuals' latent trait scores for multivariate zero-inflated count data. In the model, two link functions are used to capture two processes of the zero-inflated count data. Item parameters are…

A modular approach for item response theory modeling with the R package flirt.

PubMed

Jeon, Minjeong; Rijmen, Frank

2016-06-01

The new R package flirt is introduced for flexible item response theory (IRT) modeling of psychological, educational, and behavior assessment data. flirt integrates a generalized linear and nonlinear mixed modeling framework with graphical model theory. The graphical model framework allows for efficient maximum likelihood estimation. The key feature of flirt is its modular approach to facilitate convenient and flexible model specifications. Researchers can construct customized IRT models by simply selecting various modeling modules, such as parametric forms, number of dimensions, item and person covariates, person groups, link functions, etc. In this paper, we describe major features of flirt and provide examples to illustrate how flirt works in practice.

Measuring ability to assess claims about treatment effects: a latent trait analysis of items from the 'Claim Evaluation Tools' database using Rasch modelling.

PubMed

Austvoll-Dahlgren, Astrid; Guttersrud, Øystein; Nsangi, Allen; Semakula, Daniel; Oxman, Andrew D

2017-05-25

The Claim Evaluation Tools database contains multiple-choice items for measuring people's ability to apply the key concepts they need to know to be able to assess treatment claims. We assessed items from the database using Rasch analysis to develop an outcome measure to be used in two randomised trials in Uganda. Rasch analysis is a form of psychometric testing relying on Item Response Theory. It is a dynamic way of developing outcome measures that are valid and reliable. To assess the validity, reliability and responsiveness of 88 items addressing 22 key concepts using Rasch analysis. We administrated four sets of multiple-choice items in English to 1114 people in Uganda and Norway, of which 685 were children and 429 were adults (including 171 health professionals). We scored all items dichotomously. We explored summary and individual fit statistics using the RUMM2030 analysis package. We used SPSS to perform distractor analysis. Most items conformed well to the Rasch model, but some items needed revision. Overall, the four item sets had satisfactory reliability. We did not identify significant response dependence between any pairs of items and, overall, the magnitude of multidimensionality in the data was acceptable. The items had a high level of difficulty. Most of the items conformed well to the Rasch model's expectations. Following revision of some items, we concluded that most of the items were suitable for use in an outcome measure for evaluating the ability of children or adults to assess treatment claims. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Assessing items on the SF-8 Japanese version for health-related quality of life: a psychometric analysis based on the nominal categories model of item response theory.

PubMed

Tokuda, Yasuharu; Okubo, Tomoya; Ohde, Sachiko; Jacobs, Joshua; Takahashi, Osamu; Omata, Fumio; Yanai, Haruo; Hinohara, Shigeaki; Fukui, Tsuguya

2009-06-01

The Short Form-8 (SF-8) questionnaire is a commonly used 8-item instrument of health-related quality of life (QOL) and provides a health profile of eight subdimensions. Our aim was to examine the psychometric properties of the Japanese version of the SF-8 instrument using methodology based on nominal categories model. Using data from an adjusted random sample from a nationally representative panel, the nominal categories modeling was applied to SF-8 items to characterize coverage of the latent trait (theta). Probabilities for response choices were described as functions on the latent trait. Information functions were generated based on the estimated item parameters. A total of 3344 participants (53%, women; median age, 35 years) provided responses. One factor was retained (eigenvalue, 4.65; variance proportion of 0.58) and used as theta. All item response category characteristic curves satisfied the monotonicity assumption in accurate order with corresponding ordinal responses. Four items (general health, bodily pain, vitality, and mental health) cover most of the spectrum of theta, while the other four items (physical function, role physical [role limitations because of physical health], social functioning, and role emotional [role limitations because of emotional problems] ) cover most of the negative range of theta. Information function for all items combined peaked at -0.7 of theta (information = 18.5) and decreased with increasing theta. The SF-8 instrument performs well among those with poor QOL across the continuum of the latent trait and thus can recognize more effectively persons with relatively poorer QOL than those with relatively better QOL.

The Relationship of Item-Level Response Times with Test-Taker and Item Variables in an Operational CAT Environment. LSAC Research Report Series.

ERIC Educational Resources Information Center

Swygert, Kimberly A.

In this study, data from an operational computerized adaptive test (CAT) were examined in order to gather information concerning item response times in a CAT environment. The CAT under study included multiple-choice items measuring verbal, quantitative, and analytical reasoning. The analyses included the fitting of regression models describing the…

Cross-Cultural Validation of the Quality of Life in Hand Eczema Questionnaire (QOLHEQ).

PubMed

Ofenloch, Robert F; Oosterhaven, Jart A F; Susitaival, Päivikki; Svensson, Åke; Weisshaar, Elke; Minamoto, Keiko; Onder, Meltem; Schuttelaar, Marie Louise A; Bulbul Baskan, Emel; Diepgen, Thomas L; Apfelbacher, Christian

2017-07-01

The Quality of Life in Hand Eczema Questionnaire (QOLHEQ) is the only instrument assessing disease-specific health-related quality of life in patients with hand eczema. It is available in eight language versions. In this study we assessed if the items of different language versions of the QOLHEQ yield comparable values across countries. An international multicenter study was conducted with participating centers in Finland, Germany, Japan, The Netherlands, Sweden, and Turkey. Methods of item response theory were applied to each subscale to assess differential item functioning for items among countries. Overall, 662 hand eczema patients were recruited into the study. Single items were removed or split according to the item response theory model by country to resolve differential item functioning. After this adjustment, none of the four subscales of the QOLHEQ showed significant misfit to the item response theory model (P < 0.01), and a Person Separation Index of greater than 0.7 showed good internal consistency for each subscale. By adapting the scoring of the QOLHEQ using the methods of item response theory, it was possible to obtain QOLHEQ values that are comparable across countries. Cross-cultural variations in the interpretation of single items were resolved. The QOLHEQ is now ready to be used in international studies assessing the health-related quality of life impact of hand eczema. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

"A violation of the conditional independence assumption in the two-high-threshold Model of recognition memory": Correction to Chen, Starns, and Rotello (2015).

PubMed

2016-01-01

Reports an error in "A violation of the conditional independence assumption in the two-high-threshold model of recognition memory" by Tina Chen, Jeffrey J. Starns and Caren M. Rotello (Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015[Jul], Vol 41[4], 1215-1222). In the article, Chen et al. compared three models: a continuous signal detection model (SDT), a standard two-high-threshold discrete-state model in which detect states always led to correct responses (2HT), and a full-mapping version of the 2HT model in which detect states could lead to either correct or incorrect responses. After publication, Rani Moran (personal communication, April 21, 2015) identified two errors that impact the reported fit statistics for the Bayesian information criterion (BIC) metric of all models as well as the Akaike information criterion (AIC) results for the full-mapping model. The errors are described in the erratum. (The following abstract of the original article appeared in record 2014-56216-001.) The 2-high-threshold (2HT) model of recognition memory assumes that test items result in distinct internal states: they are either detected or not, and the probability of responding at a particular confidence level that an item is "old" or "new" depends on the state-response mapping parameters. The mapping parameters are independent of the probability that an item yields a particular state (e.g., both strong and weak items that are detected as old have the same probability of producing a highest-confidence "old" response). We tested this conditional independence assumption by presenting nouns 1, 2, or 4 times. To maximize the strength of some items, "superstrong" items were repeated 4 times and encoded in conjunction with pleasantness, imageability, anagram, and survival processing tasks. The 2HT model failed to simultaneously capture the response rate data for all item classes, demonstrating that the data violated the conditional independence assumption. In contrast, a Gaussian signal detection model, which posits that the level of confidence that an item is "old" or "new" is a function of its continuous strength value, provided a good account of the data. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Multilevel Higher-Order Item Response Theory Models

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2014-01-01

In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

Development of new physical activity and sedentary behavior change self-efficacy questionnaires using item response modeling

USDA-ARS?s Scientific Manuscript database

Theoretically, increased levels of physical activity self-efficacy (PASE) should lead to increased physical activity, but few studies have reported this effect among youth. This failure may be at least partially attributable to measurement limitations. In this study, Item Response Modeling (IRM) was...

Item Response Theory for Peer Assessment

ERIC Educational Resources Information Center

Uto, Masaki; Ueno, Maomi

2016-01-01

As an assessment method based on a constructivist approach, peer assessment has become popular in recent years. However, in peer assessment, a problem remains that reliability depends on the rater characteristics. For this reason, some item response models that incorporate rater parameters have been proposed. Those models are expected to improve…

Item Response Theory Analyses of the Cambridge Face Memory Test (CFMT)

PubMed Central

Cho, Sun-Joo; Wilmer, Jeremy; Herzmann, Grit; McGugin, Rankin; Fiset, Daniel; Van Gulick, Ana E.; Ryan, Katie; Gauthier, Isabel

2014-01-01

We evaluated the psychometric properties of the Cambridge face memory test (CFMT; Duchaine & Nakayama, 2006). First, we assessed the dimensionality of the test with a bi-factor exploratory factor analysis (EFA). This EFA analysis revealed a general factor and three specific factors clustered by targets of CFMT. However, the three specific factors appeared to be minor factors that can be ignored. Second, we fit a unidimensional item response model. This item response model showed that the CFMT items could discriminate individuals at different ability levels and covered a wide range of the ability continuum. We found the CFMT to be particularly precise for a wide range of ability levels. Third, we implemented item response theory (IRT) differential item functioning (DIF) analyses for each gender group and two age groups (Age ≤ 20 versus Age > 21). This DIF analysis suggested little evidence of consequential differential functioning on the CFMT for these groups, supporting the use of the test to compare older to younger, or male to female, individuals. Fourth, we tested for a gender difference on the latent facial recognition ability with an explanatory item response model. We found a significant but small gender difference on the latent ability for face recognition, which was higher for women than men by 0.184, at age mean 23.2, controlling for linear and quadratic age effects. Finally, we discuss the practical considerations of the use of total scores versus IRT scale scores in applications of the CFMT. PMID:25642930

HIV/AIDS knowledge among men who have sex with men: applying the item response theory.

PubMed

Gomes, Raquel Regina de Freitas Magalhães; Batista, José Rodrigues; Ceccato, Maria das Graças Braga; Kerr, Lígia Regina Franco Sansigolo; Guimarães, Mark Drew Crosland

2014-04-01

To evaluate the level of HIV/AIDS knowledge among men who have sex with men in Brazil using the latent trait model estimated by Item Response Theory. Multicenter, cross-sectional study, carried out in ten Brazilian cities between 2008 and 2009. Adult men who have sex with men were recruited (n = 3,746) through Respondent Driven Sampling. HIV/AIDS knowledge was ascertained through ten statements by face-to-face interview and latent scores were obtained through two-parameter logistic modeling (difficulty and discrimination) using Item Response Theory. Differential item functioning was used to examine each item characteristic curve by age and schooling. Overall, the HIV/AIDS knowledge scores using Item Response Theory did not exceed 6.0 (scale 0-10), with mean and median values of 5.0 (SD = 0.9) and 5.3, respectively, with 40.7% of the sample with knowledge levels below the average. Some beliefs still exist in this population regarding the transmission of the virus by insect bites, by using public restrooms, and by sharing utensils during meals. With regard to the difficulty and discrimination parameters, eight items were located below the mean of the scale and were considered very easy, and four items presented very low discrimination parameter (< 0.34). The absence of difficult items contributed to the inaccuracy of the measurement of knowledge among those with median level and above. Item Response Theory analysis, which focuses on the individual properties of each item, allows measures to be obtained that do not vary or depend on the questionnaire, which provides better ascertainment and accuracy of knowledge scores. Valid and reliable scales are essential for monitoring HIV/AIDS knowledge among the men who have sex with men population over time and in different geographic regions, and this psychometric model brings this advantage.

Assessing Model Data Fit of Unidimensional Item Response Theory Models in Simulated Data

ERIC Educational Resources Information Center

Kose, Ibrahim Alper

2014-01-01

The purpose of this paper is to give an example of how to assess the model-data fit of unidimensional IRT models in simulated data. Also, the present research aims to explain the importance of fit and the consequences of misfit by using simulated data sets. Responses of 1000 examinees to a dichotomously scoring 20 item test were simulated with 25…

eHealth literacy in chronic disease patients: An item response theory analysis of the eHealth literacy scale (eHEALS).

PubMed

Paige, Samantha R; Krieger, Janice L; Stellefson, Michael; Alber, Julia M

2017-02-01

Chronic disease patients are affected by low computer and health literacy, which negatively affects their ability to benefit from access to online health information. To estimate reliability and confirm model specifications for eHealth Literacy Scale (eHEALS) scores among chronic disease patients using Classical Test (CTT) and Item Response Theory techniques. A stratified sample of Black/African American (N=341) and Caucasian (N=343) adults with chronic disease completed an online survey including the eHEALS. Item discrimination was explored using bi-variate correlations and Cronbach's alpha for internal consistency. A categorical confirmatory factor analysis tested a one-factor structure of eHEALS scores. Item characteristic curves, in-fit/outfit statistics, omega coefficient, and item reliability and separation estimates were computed. A 1-factor structure of eHEALS was confirmed by statistically significant standardized item loadings, acceptable model fit indices (CFI/TLI>0.90), and 70% variance explained by the model. Item response categories increased with higher theta levels, and there was evidence of acceptable reliability (ω=0.94; item reliability=89; item separation=8.54). eHEALS scores are a valid and reliable measure of self-reported eHealth literacy among Internet-using chronic disease patients. Providers can use eHEALS to help identify patients' eHealth literacy skills. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Cultural Consensus Theory: Aggregating Continuous Responses in a Finite Interval

NASA Astrophysics Data System (ADS)

Batchelder, William H.; Strashny, Alex; Romney, A. Kimball

Cultural consensus theory (CCT) consists of cognitive models for aggregating responses of "informants" to test items about some domain of their shared cultural knowledge. This paper develops a CCT model for items requiring bounded numerical responses, e.g. probability estimates, confidence judgments, or similarity judgments. The model assumes that each item generates a latent random representation in each informant, with mean equal to the consensus answer and variance depending jointly on the informant and the location of the consensus answer. The manifest responses may reflect biases of the informants. Markov Chain Monte Carlo (MCMC) methods were used to estimate the model, and simulation studies validated the approach. The model was applied to an existing cross-cultural dataset involving native Japanese and English speakers judging the similarity of emotion terms. The results sharpened earlier studies that showed that both cultures appear to have very similar cognitive representations of emotion terms.

Development of a PROMIS item bank to measure pain interference.

PubMed

Amtmann, Dagmar; Cook, Karon F; Jensen, Mark P; Chen, Wen-Hung; Choi, Seung; Revicki, Dennis; Cella, David; Rothrock, Nan; Keefe, Francis; Callahan, Leigh; Lai, Jin-Shei

2010-07-01

This paper describes the psychometric properties of the PROMIS-pain interference (PROMIS-PI) bank. An initial candidate item pool (n=644) was developed and evaluated based on the review of existing instruments, interviews with patients, and consultation with pain experts. From this pool, a candidate item bank of 56 items was selected and responses to the items were collected from large community and clinical samples. A total of 14,848 participants responded to all or a subset of candidate items. The responses were calibrated using an item response theory (IRT) model. A final 41-item bank was evaluated with respect to IRT assumptions, model fit, differential item function (DIF), precision, and construct and concurrent validity. Items of the revised bank had good fit to the IRT model (CFI and NNFI/TLI ranged from 0.974 to 0.997), and the data were strongly unidimensional (e.g., ratio of first and second eigenvalue=35). Nine items exhibited statistically significant DIF. However, adjusting for DIF had little practical impact on score estimates and the items were retained without modifying scoring. Scores provided substantial information across levels of pain; for scores in the T-score range 50-80, the reliability was equivalent to 0.96-0.99. Patterns of correlations with other health outcomes supported the construct validity of the item bank. The scores discriminated among persons with different numbers of chronic conditions, disabling conditions, levels of self-reported health, and pain intensity (p<0.0001). The results indicated that the PROMIS-PI items constitute a psychometrically sound bank. Computerized adaptive testing and short forms are available. Copyright 2010 International Association for the Study of Pain. All rights reserved.

Effects of Aging and IQ on Item and Associative Memory

ERIC Educational Resources Information Center

Ratcliff, Roger; Thapar, Anjali; McKoon, Gail

2011-01-01

The effects of aging and IQ on performance were examined in 4 memory tasks: item recognition, associative recognition, cued recall, and free recall. For item and associative recognition, accuracy and the response time (RT) distributions for correct and error responses were explained by Ratcliff's (1978) diffusion model at the level of individual…

Empirical Histograms in Item Response Theory with Ordinal Data

ERIC Educational Resources Information Center

Woods, Carol M.

2007-01-01

The purpose of this research is to describe, test, and illustrate a new implementation of the empirical histogram (EH) method for ordinal items. The EH method involves the estimation of item response model parameters simultaneously with the approximation of the distribution of the random latent variable (theta) as a histogram. Software for the EH…

Anchor Selection Strategies for DIF Analysis: Review, Assessment, and New Approaches

ERIC Educational Resources Information Center

Kopf, Julia; Zeileis, Achim; Strobl, Carolin

2015-01-01

Differential item functioning (DIF) indicates the violation of the invariance assumption, for instance, in models based on item response theory (IRT). For item-wise DIF analysis using IRT, a common metric for the item parameters of the groups that are to be compared (e.g., for the reference and the focal group) is necessary. In the Rasch model,…

Using a Model of Analysts' Judgments to Augment an Item Calibration Process

ERIC Educational Resources Information Center

Hauser, Carl; Thum, Yeow Meng; He, Wei; Ma, Lingling

2015-01-01

When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…

Accuracy and Variability of Item Parameter Estimates from Marginal Maximum a Posteriori Estimation and Bayesian Inference via Gibbs Samplers

ERIC Educational Resources Information Center

Wu, Yi-Fang

2015-01-01

Item response theory (IRT) uses a family of statistical models for estimating stable characteristics of items and examinees and defining how these characteristics interact in describing item and test performance. With a focus on the three-parameter logistic IRT (Birnbaum, 1968; Lord, 1980) model, the current study examines the accuracy and…

Fit of Item Response Theory Models: A Survey of Data from Several Operational Tests. Research Report. ETS RR-11-29

ERIC Educational Resources Information Center

Sinharay, Sandip; Haberman, Shelby J.; Jia, Helena

2011-01-01

Standard 3.9 of the "Standards for Educational and Psychological Testing" (American Educational Research Association, American Psychological Association, & National Council for Measurement in Education, 1999) demands evidence of model fit when an item response theory (IRT) model is used to make inferences from a data set. We applied two recently…

Reweighting Data in the Spirit of Tukey: Using Bayesian Posterior Probabilities as Rasch Residuals for Studying Misfit

ERIC Educational Resources Information Center

Dardick, William R.; Mislevy, Robert J.

2016-01-01

A new variant of the iterative "data = fit + residual" data-analytical approach described by Mosteller and Tukey is proposed and implemented in the context of item response theory psychometric models. Posterior probabilities from a Bayesian mixture model of a Rasch item response theory model and an unscalable latent class are expressed…

An Assessment of the Nonparametric Approach for Evaluating the Fit of Item Response Models

ERIC Educational Resources Information Center

Liang, Tie; Wells, Craig S.; Hambleton, Ronald K.

2014-01-01

As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…

Maximizing the Information and Validity of a Linear Composite in the Factor Analysis Model for Continuous Item Responses

ERIC Educational Resources Information Center

Ferrando, Pere J.

2008-01-01

This paper develops results and procedures for obtaining linear composites of factor scores that maximize: (a) test information, and (b) validity with respect to external variables in the multiple factor analysis (FA) model. I treat FA as a multidimensional item response theory model, and use Ackerman's multidimensional information approach based…

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

ERIC Educational Resources Information Center

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

Assessment of Differential Item Functioning under Cognitive Diagnosis Models: The DINA Model Example

ERIC Educational Resources Information Center

Li, Xiaomin; Wang, Wen-Chung

2015-01-01

The assessment of differential item functioning (DIF) is routinely conducted to ensure test fairness and validity. Although many DIF assessment methods have been developed in the context of classical test theory and item response theory, they are not applicable for cognitive diagnosis models (CDMs), as the underlying latent attributes of CDMs are…

A Study of Bayesian Estimation and Comparison of Response Time Models in Item Response Theory

ERIC Educational Resources Information Center

Suh, Hongwook

2010-01-01

Response time has been regarded as an important source for investigating the relationship between human performance and response speed. It is important to examine the relationship between response time and item characteristics, especially in the perspective of the relationship between response time and various factors that affect examinee's…

Calibrating the Medical Council of Canada's Qualifying Examination Part I using an integrated item response theory framework: a comparison of models and designs.

PubMed

De Champlain, Andre F; Boulais, Andre-Philippe; Dallas, Andrew

2016-01-01

The aim of this research was to compare different methods of calibrating multiple choice question (MCQ) and clinical decision making (CDM) components for the Medical Council of Canada's Qualifying Examination Part I (MCCQEI) based on item response theory. Our data consisted of test results from 8,213 first time applicants to MCCQEI in spring and fall 2010 and 2011 test administrations. The data set contained several thousand multiple choice items and several hundred CDM cases. Four dichotomous calibrations were run using BILOG-MG 3.0. All 3 mixed item format (dichotomous MCQ responses and polytomous CDM case scores) calibrations were conducted using PARSCALE 4. The 2-PL model had identical numbers of items with chi-square values at or below a Type I error rate of 0.01 (83/3,499 or 0.02). In all 3 polytomous models, whether the MCQs were either anchored or concurrently run with the CDM cases, results suggest very poor fit. All IRT abilities estimated from dichotomous calibration designs correlated very highly with each other. IRT-based pass-fail rates were extremely similar, not only across calibration designs and methods, but also with regard to the actual reported decision to candidates. The largest difference noted in pass rates was 4.78%, which occurred between the mixed format concurrent 2-PL graded response model (pass rate= 80.43%) and the dichotomous anchored 1-PL calibrations (pass rate= 85.21%). Simpler calibration designs with dichotomized items should be implemented. The dichotomous calibrations provided better fit of the item response matrix than more complex, polytomous calibrations.

The Heteroscedastic Graded Response Model with a Skewed Latent Trait: Testing Statistical and Substantive Hypotheses Related to Skewed Item Category Functions

ERIC Educational Resources Information Center

Molenaar, Dylan; Dolan, Conor V.; de Boeck, Paul

2012-01-01

The Graded Response Model (GRM; Samejima, "Estimation of ability using a response pattern of graded scores," Psychometric Monograph No. 17, Richmond, VA: The Psychometric Society, 1969) can be derived by assuming a linear regression of a continuous variable, Z, on the trait, [theta], to underlie the ordinal item scores (Takane & de Leeuw in…

Item response theory analysis of the Utrecht Work Engagement Scale for Students (UWES-S) using a sample of Japanese university and college students majoring medical science, nursing, and natural science.

PubMed

Tsubakita, Takashi; Shimazaki, Kazuyo; Ito, Hiroshi; Kawazoe, Nobuo

2017-10-30

The Utrecht Work Engagement Scale for Students has been used internationally to assess students' academic engagement, but it has not been analyzed via item response theory. The purpose of this study was to conduct an item response theory analysis of the Japanese version of the Utrecht Work Engagement Scale for Students translated by authors. Using a two-parameter model and Samejima's graded response model, difficulty and discrimination parameters were estimated after confirming the factor structure of the scale. The 14 items on the scale were analyzed with a sample of 3214 university and college students majoring medical science, nursing, or natural science in Japan. The preliminary parameter estimation was conducted with the two parameter model, and indicated that three items should be removed because there were outlier parameters. Final parameter estimation was conducted using the survived 11 items, and indicated that all difficulty and discrimination parameters were acceptable. The test information curve suggested that the scale better assesses higher engagement than average engagement. The estimated parameters provide a basis for future comparative studies. The results also suggested that a 7-point Likert scale is too broad; thus, the scaling should be modified to fewer graded scaling structure.

Measuring Integration of Information and Communication Technology in Education: An Item Response Modeling Approach

ERIC Educational Resources Information Center

Peeraer, Jef; Van Petegem, Peter

2012-01-01

This research describes the development and validation of an instrument to measure integration of Information and Communication Technology (ICT) in education. After literature research on definitions of integration of ICT in education, a comparison is made between the classical test theory and the item response modeling approach for the…

Firestar-"D": Computerized Adaptive Testing Simulation Program for Dichotomous Item Response Theory Models

ERIC Educational Resources Information Center

Choi, Seung W.; Podrabsky, Tracy; McKinney, Natalie

2012-01-01

Computerized adaptive testing (CAT) enables efficient and flexible measurement of latent constructs. The majority of educational and cognitive measurement constructs are based on dichotomous item response theory (IRT) models. An integral part of developing various components of a CAT system is conducting simulations using both known and empirical…

Bi-Factor Multidimensional Item Response Theory Modeling for Subscores Estimation, Reliability, and Classification

ERIC Educational Resources Information Center

Md Desa, Zairul Nor Deana

2012-01-01

In recent years, there has been increasing interest in estimating and improving subscore reliability. In this study, the multidimensional item response theory (MIRT) and the bi-factor model were combined to estimate subscores, to obtain subscores reliability, and subscores classification. Both the compensatory and partially compensatory MIRT…

Invariance Properties for General Diagnostic Classification Models

ERIC Educational Resources Information Center

Bradshaw, Laine P.; Madison, Matthew J.

2016-01-01

In item response theory (IRT), the invariance property states that item parameter estimates are independent of the examinee sample, and examinee ability estimates are independent of the test items. While this property has long been established and understood by the measurement community for IRT models, the same cannot be said for diagnostic…

Effects of Anchor Item Methods on the Detection of Differential Item Functioning within the Family of Rasch Models

ERIC Educational Resources Information Center

Wang, Wen-Chung

2004-01-01

Scale indeterminacy in analysis of differential item functioning (DIF) within the framework of item response theory can be resolved by imposing 3 anchor item methods: the equal-mean-difficulty method, the all-other anchor item method, and the constant anchor item method. In this article, applicability and limitations of these 3 methods are…

Rasch validation of the Arabic version of the lower extremity functional scale.

PubMed

Alnahdi, Ali H

2018-02-01

The purpose of this study was to examine the internal construct validity of the Arabic version of the Lower Extremity Functional Scale (20-item Arabic LEFS) using Rasch analysis. Patients (n = 170) with lower extremity musculoskeletal dysfunction were recruited. Rasch analysis of 20-item Arabic LEFS was performed. Once the initial Rasch analysis indicated that the 20-item Arabic LEFS did not fit the Rasch model, follow-up analyses were conducted to improve the fit of the scale to the Rasch measurement model. These modifications included removing misfitting individuals, changing item scoring structure, removing misfitting items, addressing bias caused by response dependency between items and differential item functioning (DIF). Initial analysis indicated deviation of the 20-item Arabic LEFS from the Rasch model. Disordered thresholds in eight items and response dependency between six items were detected with the scale as a whole did not meet the requirement of unidimensionality. Refinements led to a 15-item Arabic LEFS that demonstrated excellent internal consistency (person separation index [PSI] = 0.92) and satisfied all the requirement of the Rasch model. Rasch analysis did not support the 20-item Arabic LEFS as a unidimensional measure of lower extremity function. The refined 15-item Arabic LEFS met all the requirement of the Rasch model and hence is a valid objective measure of lower extremity function. The Rasch-validated 15-item Arabic LEFS needs to be further tested in an independent sample to confirm its fit to the Rasch measurement model. Implications for Rehabilitation The validity of the 20-item Arabic Lower Extremity Functional Scale to measure lower extremity function is not supported. The 15-item Arabic version of the LEFS is a valid measure of lower extremity function and can be used to quantify lower extremity function in patients with lower extremity musculoskeletal disorders.

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

Using Patient Health Questionnaire-9 item parameters of a common metric resulted in similar depression scores compared to independent item response theory model reestimation.

PubMed

Liegl, Gregor; Wahl, Inka; Berghöfer, Anne; Nolte, Sandra; Pieh, Christoph; Rose, Matthias; Fischer, Felix

2016-03-01

To investigate the validity of a common depression metric in independent samples. We applied a common metrics approach based on item-response theory for measuring depression to four German-speaking samples that completed the Patient Health Questionnaire (PHQ-9). We compared the PHQ item parameters reported for this common metric to reestimated item parameters that derived from fitting a generalized partial credit model solely to the PHQ-9 items. We calibrated the new model on the same scale as the common metric using two approaches (estimation with shifted prior and Stocking-Lord linking). By fitting a mixed-effects model and using Bland-Altman plots, we investigated the agreement between latent depression scores resulting from the different estimation models. We found different item parameters across samples and estimation methods. Although differences in latent depression scores between different estimation methods were statistically significant, these were clinically irrelevant. Our findings provide evidence that it is possible to estimate latent depression scores by using the item parameters from a common metric instead of reestimating and linking a model. The use of common metric parameters is simple, for example, using a Web application (http://www.common-metrics.org) and offers a long-term perspective to improve the comparability of patient-reported outcome measures. Copyright © 2016 Elsevier Inc. All rights reserved.

Global, Local, and Graphical Person-Fit Analysis Using Person-Response Functions

ERIC Educational Resources Information Center

Emons, Wilco H. M.; Sijtsma, Klaas; Meijer, Rob R.

2005-01-01

Person-fit statistics test whether the likelihood of a respondent's complete vector of item scores on a test is low given the hypothesized item response theory model. This binary information may be insufficient for diagnosing the cause of a misfitting item-score vector. The authors propose a comprehensive methodology for person-fit analysis in the…

A Note on the Reliability Coefficients for Item Response Model-Based Ability Estimates

ERIC Educational Resources Information Center

Kim, Seonghoon

2012-01-01

Assuming item parameters on a test are known constants, the reliability coefficient for item response theory (IRT) ability estimates is defined for a population of examinees in two different ways: as (a) the product-moment correlation between ability estimates on two parallel forms of a test and (b) the squared correlation between the true…

An Explanatory Item Response Theory Approach for a Computer-Based Case Simulation Test

ERIC Educational Resources Information Center

Kahraman, Nilüfer

2014-01-01

Problem: Practitioners working with multiple-choice tests have long utilized Item Response Theory (IRT) models to evaluate the performance of test items for quality assurance. The use of similar applications for performance tests, however, is often encumbered due to the challenges encountered in working with complicated data sets in which local…

Performance of the Generalized S-X[squared] Item Fit Index for the Graded Response Model

ERIC Educational Resources Information Center

Kang, Taehoon; Chen, Troy T.

2011-01-01

The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having…

Probing the Relative Importance of Different Attributes in L2 Reading and Listening Comprehension Items: An Application of Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Yi, Yeon-Sook

2017-01-01

The present study examines the relative importance of attributes within and across items by applying four cognitive diagnostic assessment models. The current study utilizes the function of the models that can indicate inter-attribute relationships that reflect the response behaviors of examinees to analyze scored test-taker responses to four forms…

The Effects of Rater Severity and Rater Distribution on Examinees' Ability Estimation for Constructed-Response Items. Research Report. ETS RR-13-23

ERIC Educational Resources Information Center

Wang, Zhen; Yao, Lihua

2013-01-01

The current study used simulated data to investigate the properties of a newly proposed method (Yao's rater model) for modeling rater severity and its distribution under different conditions. Our study examined the effects of rater severity, distributions of rater severity, the difference between item response theory (IRT) models with rater effect…

An Analysis of Cross Racial Identity Scale Scores Using Classical Test Theory and Rasch Item Response Models

ERIC Educational Resources Information Center

Sussman, Joshua; Beaujean, A. Alexander; Worrell, Frank C.; Watson, Stevie

2013-01-01

Item response models (IRMs) were used to analyze Cross Racial Identity Scale (CRIS) scores. Rasch analysis scores were compared with classical test theory (CTT) scores. The partial credit model demonstrated a high goodness of fit and correlations between Rasch and CTT scores ranged from 0.91 to 0.99. CRIS scores are supported by both methods.…

Modeling Local Item Dependence Due to Common Test Format with a Multidimensional Rasch Model

ERIC Educational Resources Information Center

Baghaei, Purya; Aryadoust, Vahid

2015-01-01

Research shows that test method can exert a significant impact on test takers' performance and thereby contaminate test scores. We argue that common test method can exert the same effect as common stimuli and violate the conditional independence assumption of item response theory models because, in general, subsets of items which have a shared…

Measuring pain phenomena after spinal cord injury: Development and psychometric properties of the SCI-QOL Pain Interference and Pain Behavior assessment tools.

PubMed

Cohen, Matthew L; Kisala, Pamela A; Dyson-Hudson, Trevor A; Tulsky, David S

2018-05-01

To develop modern patient-reported outcome measures that assess pain interference and pain behavior after spinal cord injury (SCI). Grounded-theory based qualitative item development; large-scale item calibration field-testing; confirmatory factor analyses; graded response model item response theory analyses; statistical linking techniques to transform scores to the Patient Reported Outcome Measurement Information System (PROMIS) metric. Five SCI Model Systems centers and one Department of Veterans Affairs medical center in the United States. Adults with traumatic SCI. N/A. Spinal Cord Injury - Quality of Life (SCI-QOL) Pain Interference item bank, SCI-QOL Pain Interference short form, and SCI-QOL Pain Behavior scale. Seven hundred fifty-seven individuals with traumatic SCI completed 58 items addressing various aspects of pain. Items were then separated by whether they assessed pain interference or pain behavior, and poorly functioning items were removed. Confirmatory factor analyses confirmed that each set of items was unidimensional, and item response theory analyses were used to estimate slopes and thresholds for the items. Ultimately, 7 items (4 from PROMIS) comprised the Pain Behavior scale and 25 items (18 from PROMIS) comprised the Pain Interference item bank. Ten of these 25 items were selected to form the Pain Interference short form. The SCI-QOL Pain Interference item bank and the SCI-QOL Pain Behavior scale demonstrated robust psychometric properties. The Pain Interference item bank is available as a computer adaptive test or short form for research and clinical applications, and scores are transformed to the PROMIS metric.

Differential item functioning analysis of the Vanderbilt Expertise Test for cars.

PubMed

Lee, Woo-Yeol; Cho, Sun-Joo; McGugin, Rankin W; Van Gulick, Ana Beth; Gauthier, Isabel

2015-01-01

The Vanderbilt Expertise Test for cars (VETcar) is a test of visual learning for contemporary car models. We used item response theory to assess the VETcar and in particular used differential item functioning (DIF) analysis to ask if the test functions the same way in laboratory versus online settings and for different groups based on age and gender. An exploratory factor analysis found evidence of multidimensionality in the VETcar, although a single dimension was deemed sufficient to capture the recognition ability measured by the test. We selected a unidimensional three-parameter logistic item response model to examine item characteristics and subject abilities. The VETcar had satisfactory internal consistency. A substantial number of items showed DIF at a medium effect size for test setting and for age group, whereas gender DIF was negligible. Because online subjects were on average older than those tested in the lab, we focused on the age groups to conduct a multigroup item response theory analysis. This revealed that most items on the test favored the younger group. DIF could be more the rule than the exception when measuring performance with familiar object categories, therefore posing a challenge for the measurement of either domain-general visual abilities or category-specific knowledge.

An evaluation of computerized adaptive testing for general psychological distress: combining GHQ-12 and Affectometer-2 in an item bank for public mental health research.

PubMed

Stochl, Jan; Böhnke, Jan R; Pickett, Kate E; Croudace, Tim J

2016-05-20

Recent developments in psychometric modeling and technology allow pooling well-validated items from existing instruments into larger item banks and their deployment through methods of computerized adaptive testing (CAT). Use of item response theory-based bifactor methods and integrative data analysis overcomes barriers in cross-instrument comparison. This paper presents the joint calibration of an item bank for researchers keen to investigate population variations in general psychological distress (GPD). Multidimensional item response theory was used on existing health survey data from the Scottish Health Education Population Survey (n = 766) to calibrate an item bank consisting of pooled items from the short common mental disorder screen (GHQ-12) and the Affectometer-2 (a measure of "general happiness"). Computer simulation was used to evaluate usefulness and efficacy of its adaptive administration. A bifactor model capturing variation across a continuum of population distress (while controlling for artefacts due to item wording) was supported. The numbers of items for different required reliabilities in adaptive administration demonstrated promising efficacy of the proposed item bank. Psychometric modeling of the common dimension captured by more than one instrument offers the potential of adaptive testing for GPD using individually sequenced combinations of existing survey items. The potential for linking other item sets with alternative candidate measures of positive mental health is discussed since an optimal item bank may require even more items than these.

Item Response Theory and Health Outcomes Measurement in the 21st Century

PubMed Central

Hays, Ron D.; Morales, Leo S.; Reise, Steve P.

2006-01-01

Item response theory (IRT) has a number of potential advantages over classical test theory in assessing self-reported health outcomes. IRT models yield invariant item and latent trait estimates (within a linear transformation), standard errors conditional on trait level, and trait estimates anchored to item content. IRT also facilitates evaluation of differential item functioning, inclusion of items with different response formats in the same scale, and assessment of person fit and is ideally suited for implementing computer adaptive testing. Finally, IRT methods can be helpful in developing better health outcome measures and in assessing change over time. These issues are reviewed, along with a discussion of some of the methodological and practical challenges in applying IRT methods. PMID:10982088

Hidden Markov Item Response Theory Models for Responses and Response Times.

PubMed

Molenaar, Dylan; Oberski, Daniel; Vermunt, Jeroen; De Boeck, Paul

2016-01-01

Current approaches to model responses and response times to psychometric tests solely focus on between-subject differences in speed and ability. Within subjects, speed and ability are assumed to be constants. Violations of this assumption are generally absorbed in the residual of the model. As a result, within-subject departures from the between-subject speed and ability level remain undetected. These departures may be of interest to the researcher as they reflect differences in the response processes adopted on the items of a test. In this article, we propose a dynamic approach for responses and response times based on hidden Markov modeling to account for within-subject differences in responses and response times. A simulation study is conducted to demonstrate acceptable parameter recovery and acceptable performance of various fit indices in distinguishing between different models. In addition, both a confirmatory and an exploratory application are presented to demonstrate the practical value of the modeling approach.

Checking Dimensionality in Item Response Models with Principal Component Analysis on Standardized Residuals

ERIC Educational Resources Information Center

Chou, Yeh-Tai; Wang, Wen-Chung

2010-01-01

Dimensionality is an important assumption in item response theory (IRT). Principal component analysis on standardized residuals has been used to check dimensionality, especially under the family of Rasch models. It has been suggested that an eigenvalue greater than 1.5 for the first eigenvalue signifies a violation of unidimensionality when there…

Optimal and Most Exact Confidence Intervals for Person Parameters in Item Response Theory Models

ERIC Educational Resources Information Center

Doebler, Anna; Doebler, Philipp; Holling, Heinz

2013-01-01

The common way to calculate confidence intervals for item response theory models is to assume that the standardized maximum likelihood estimator for the person parameter [theta] is normally distributed. However, this approximation is often inadequate for short and medium test lengths. As a result, the coverage probabilities fall below the given…

How Can Multivariate Item Response Theory Be Used in Reporting of Susbcores? Research Report. ETS RR-10-09

ERIC Educational Resources Information Center

Haberman, Shelby J.; Sinharay, Sandip

2010-01-01

Recently, there has been increasing interest in reporting diagnostic scores. This paper examines reporting of subscores using multidimensional item response theory (MIRT) models. An MIRT model is fitted using a stabilized Newton-Raphson algorithm (Haberman, 1974, 1988) with adaptive Gauss-Hermite quadrature (Haberman, von Davier, & Lee, 2008).…

A Mixture Rasch Model with a Covariate: A Simulation Study via Bayesian Markov Chain Monte Carlo Estimation

ERIC Educational Resources Information Center

Dai, Yunyun

2013-01-01

Mixtures of item response theory (IRT) models have been proposed as a technique to explore response patterns in test data related to cognitive strategies, instructional sensitivity, and differential item functioning (DIF). Estimation proves challenging due to difficulties in identification and questions of effect size needed to recover underlying…

Assessment of Teacher Perceived Skill in Classroom Assessment Practices Using IRT Models

ERIC Educational Resources Information Center

Koloi-Keaikitse, Setlhomo

2017-01-01

The purpose of this study was to assess teacher perceived skill in classroom assessment practices. Data were collected from a sample of (N = 691) teachers selected from government primary, junior secondary, and senior secondary schools in Botswana. Item response theory models were used to identify teacher response on items that measured their…

Linking Outcomes from Peabody Picture Vocabulary Test Forms Using Item Response Models

ERIC Educational Resources Information Center

Hoffman, Lesa; Templin, Jonathan; Rice, Mabel L.

2012-01-01

Purpose: The present work describes how vocabulary ability as assessed by 3 different forms of the Peabody Picture Vocabulary Test (PPVT; Dunn & Dunn, 1997) can be placed on a common latent metric through item response theory (IRT) modeling, by which valid comparisons of ability between samples or over time can then be made. Method: Responses…

Using SAS PROC MCMC for Item Response Theory Models

ERIC Educational Resources Information Center

Ames, Allison J.; Samonte, Kelli

2015-01-01

Interest in using Bayesian methods for estimating item response theory models has grown at a remarkable rate in recent years. This attentiveness to Bayesian estimation has also inspired a growth in available software such as WinBUGS, R packages, BMIRT, MPLUS, and SAS PROC MCMC. This article intends to provide an accessible overview of Bayesian…

Higher Order Testlet Response Models for Hierarchical Latent Traits and Testlet-Based Items

ERIC Educational Resources Information Center

Huang, Hung-Yu; Wang, Wen-Chung

2013-01-01

Both testlet design and hierarchical latent traits are fairly common in educational and psychological measurements. This study aimed to develop a new class of higher order testlet response models that consider both local item dependence within testlets and a hierarchy of latent traits. Due to high dimensionality, the authors adopted the Bayesian…

Modeling Skipped and Not-Reached Items Using IRTrees

ERIC Educational Resources Information Center

Debeer, Dries; Janssen, Rianne; De Boeck, Paul

2017-01-01

When dealing with missing responses, two types of omissions can be discerned: items can be skipped or not reached by the test taker. When the occurrence of these omissions is related to the proficiency process the missingness is nonignorable. The purpose of this article is to present a tree-based IRT framework for modeling responses and omissions…

Multivariate Generalizations of Student's t-Distribution. ONR Technical Report. [Biometric Lab Report No. 90-3.

ERIC Educational Resources Information Center

Gibbons, Robert D.; And Others

In the process of developing a conditionally-dependent item response theory (IRT) model, the problem arose of modeling an underlying multivariate normal (MVN) response process with general correlation among the items. Without the assumption of conditional independence, for which the underlying MVN cdf takes on comparatively simple forms and can be…

Direct Estimation of Correlation as a Measure of Association Strength Using Multidimensional Item Response Models

ERIC Educational Resources Information Center

Wang, Wen-Chung

2004-01-01

The Pearson correlation is used to depict effect sizes in the context of item response theory. Amultidimensional Rasch model is used to directly estimate the correlation between latent traits. Monte Carlo simulations were conducted to investigate whether the population correlation could be accurately estimated and whether the bootstrap method…

Measuring ability to assess claims about treatment effects: a latent trait analysis of items from the ‘Claim Evaluation Tools’ database using Rasch modelling

PubMed Central

Austvoll-Dahlgren, Astrid; Guttersrud, Øystein; Nsangi, Allen; Semakula, Daniel; Oxman, Andrew D

2017-01-01

Background The Claim Evaluation Tools database contains multiple-choice items for measuring people’s ability to apply the key concepts they need to know to be able to assess treatment claims. We assessed items from the database using Rasch analysis to develop an outcome measure to be used in two randomised trials in Uganda. Rasch analysis is a form of psychometric testing relying on Item Response Theory. It is a dynamic way of developing outcome measures that are valid and reliable. Objectives To assess the validity, reliability and responsiveness of 88 items addressing 22 key concepts using Rasch analysis. Participants We administrated four sets of multiple-choice items in English to 1114 people in Uganda and Norway, of which 685 were children and 429 were adults (including 171 health professionals). We scored all items dichotomously. We explored summary and individual fit statistics using the RUMM2030 analysis package. We used SPSS to perform distractor analysis. Results Most items conformed well to the Rasch model, but some items needed revision. Overall, the four item sets had satisfactory reliability. We did not identify significant response dependence between any pairs of items and, overall, the magnitude of multidimensionality in the data was acceptable. The items had a high level of difficulty. Conclusion Most of the items conformed well to the Rasch model’s expectations. Following revision of some items, we concluded that most of the items were suitable for use in an outcome measure for evaluating the ability of children or adults to assess treatment claims. PMID:28550019

Effect Size Measures for Differential Item Functioning in a Multidimensional IRT Model

ERIC Educational Resources Information Center

Suh, Youngsuk

2016-01-01

This study adapted an effect size measure used for studying differential item functioning (DIF) in unidimensional tests and extended the measure to multidimensional tests. Two effect size measures were considered in a multidimensional item response theory model: signed weighted P-difference and unsigned weighted P-difference. The performance of…

The Comparative Performance of Conditional Independence Indices

ERIC Educational Resources Information Center

Kim, Doyoung; De Ayala, R. J.; Ferdous, Abdullah A.; Nering, Michael L.

2011-01-01

To realize the benefits of item response theory (IRT), one must have model-data fit. One facet of a model-data fit investigation involves assessing the tenability of the conditional item independence (CII) assumption. In this Monte Carlo study, the comparative performance of 10 indices for identifying conditional item dependence is assessed. The…

A Multilevel Testlet Model for Dual Local Dependence

ERIC Educational Resources Information Center

Jiao, Hong; Kamata, Akihito; Wang, Shudong; Jin, Ying

2012-01-01

The applications of item response theory (IRT) models assume local item independence and that examinees are independent of each other. When a representative sample for psychometric analysis is selected using a cluster sampling method in a testlet-based assessment, both local item dependence and local person dependence are likely to be induced.…

Developing an African youth psychosocial assessment: an application of item response theory.

PubMed

Betancourt, Theresa S; Yang, Frances; Bolton, Paul; Normand, Sharon-Lise

2014-06-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. Copyright © 2014 John Wiley & Sons, Ltd.

Developing an African youth psychosocial assessment: an application of item response theory

PubMed Central

BETANCOURT, THERESA S.; YANG, FRANCES; BOLTON, PAUL; NORMAND, SHARON-LISE

2014-01-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. PMID:24478113

Measuring the quality of life in hypertension according to Item Response Theory

PubMed Central

Borges, José Wicto Pereira; Moreira, Thereza Maria Magalhães; Schmitt, Jeovani; de Andrade, Dalton Francisco; Barbetta, Pedro Alberto; de Souza, Ana Célia Caetano; Lima, Daniele Braz da Silva; Carvalho, Irialda Saboia

2017-01-01

ABSTRACT OBJECTIVE To analyze the Miniquestionário de Qualidade de Vida em Hipertensão Arterial (MINICHAL – Mini-questionnaire of Quality of Life in Hypertension) using the Item Response Theory. METHODS This is an analytical study conducted with 712 persons with hypertension treated in thirteen primary health care units of Fortaleza, State of Ceará, Brazil, in 2015. The steps of the analysis by the Item Response Theory were: evaluation of dimensionality, estimation of parameters of items, and construction of scale. The study of dimensionality was carried out on the polychoric correlation matrix and confirmatory factor analysis. To estimate the item parameters, we used the Gradual Response Model of Samejima. The analyses were conducted using the free software R with the aid of psych and mirt. RESULTS The analysis has allowed the visualization of item parameters and their individual contributions in the measurement of the latent trait, generating more information and allowing the construction of a scale with an interpretative model that demonstrates the evolution of the worsening of the quality of life in five levels. Regarding the item parameters, the items related to the somatic state have had a good performance, as they have presented better power to discriminate individuals with worse quality of life. The items related to mental state have been those which contributed with less psychometric data in the MINICHAL. CONCLUSIONS We conclude that the instrument is suitable for the identification of the worsening of the quality of life in hypertension. The analysis of the MINICHAL using the Item Response Theory has allowed us to identify new sides of this instrument that have not yet been addressed in previous studies. PMID:28492764

Robust Measurement via A Fused Latent and Graphical Item Response Theory Model.

PubMed

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-03-12

Item response theory (IRT) plays an important role in psychological and educational measurement. Unlike the classical testing theory, IRT models aggregate the item level information, yielding more accurate measurements. Most IRT models assume local independence, an assumption not likely to be satisfied in practice, especially when the number of items is large. Results in the literature and simulation studies in this paper reveal that misspecifying the local independence assumption may result in inaccurate measurements and differential item functioning. To provide more robust measurements, we propose an integrated approach by adding a graphical component to a multidimensional IRT model that can offset the effect of unknown local dependence. The new model contains a confirmatory latent variable component, which measures the targeted latent traits, and a graphical component, which captures the local dependence. An efficient proximal algorithm is proposed for the parameter estimation and structure learning of the local dependence. This approach can substantially improve the measurement, given no prior information on the local dependence structure. The model can be applied to measure both a unidimensional latent trait and multidimensional latent traits.

Item response theory analyses of the Delis-Kaplan Executive Function System card sorting subtest.

PubMed

Spencer, Mercedes; Cho, Sun-Joo; Cutting, Laurie E

2018-02-02

In the current study, we examined the dimensionality of the 16-item Card Sorting subtest of the Delis-Kaplan Executive Functioning System assessment in a sample of 264 native English-speaking children between the ages of 9 and 15 years. We also tested for measurement invariance for these items across age and gender groups using item response theory (IRT). Results of the exploratory factor analysis indicated that a two-factor model that distinguished between verbal and perceptual items provided the best fit to the data. Although the items demonstrated measurement invariance across age groups, measurement invariance was violated for gender groups, with two items demonstrating differential item functioning for males and females. Multigroup analysis using all 16 items indicated that the items were more effective for individuals whose IRT scale scores were relatively high. A single-group explanatory IRT model using 14 non-differential item functioning items showed that for perceptual ability, females scored higher than males and that scores increased with age for both males and females; for verbal ability, the observed increase in scores across age differed for males and females. The implications of these findings are discussed.

Item Response Theory to Quantify Longitudinal Placebo and Paliperidone Effects on PANSS Scores in Schizophrenia.

PubMed

Krekels, Ehj; Novakovic, A M; Vermeulen, A M; Friberg, L E; Karlsson, M O

2017-08-01

As biomarkers are lacking, multi-item questionnaire-based tools like the Positive and Negative Syndrome Scale (PANSS) are used to quantify disease severity in schizophrenia. Analyzing composite PANSS scores as continuous data discards information and violates the numerical nature of the scale. Here a longitudinal analysis based on Item Response Theory is presented using PANSS data from phase III clinical trials. Latent disease severity variables were derived from item-level data on the positive, negative, and general PANSS subscales each. On all subscales, the time course of placebo responses were best described with Weibull models, and dose-independent functions with exponential models to describe the onset of the full effect were used to describe paliperidone's effect. Placebo and drug effect were most pronounced on the positive subscale. The final model successfully describes the time course of treatment effects on the individual PANSS item-levels, on all PANSS subscale levels, and on the total score level. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Relationships among Classical Test Theory and Item Response Theory Frameworks via Factor Analytic Models

ERIC Educational Resources Information Center

Kohli, Nidhi; Koran, Jennifer; Henn, Lisa

2015-01-01

There are well-defined theoretical differences between the classical test theory (CTT) and item response theory (IRT) frameworks. It is understood that in the CTT framework, person and item statistics are test- and sample-dependent. This is not the perception with IRT. For this reason, the IRT framework is considered to be theoretically superior…

Applying Item Response Theory to the Development of a Screening Adaptation of the Goldman-Fristoe Test of Articulation-Second Edition

ERIC Educational Resources Information Center

Brackenbury, Tim; Zickar, Michael J.; Munson, Benjamin; Storkel, Holly L.

2017-01-01

Purpose: Item response theory (IRT) is a psychometric approach to measurement that uses latent trait abilities (e.g., speech sound production skills) to model performance on individual items that vary by difficulty and discrimination. An IRT analysis was applied to preschoolers' productions of the words on the Goldman-Fristoe Test of…

Item Response Theory Analysis of the Psychopathic Personality Inventory-Revised.

PubMed

Eichenbaum, Alexander E; Marcus, David K; French, Brian F

2017-06-01

This study examined item and scale functioning in the Psychopathic Personality Inventory-Revised (PPI-R) using an item response theory analysis. PPI-R protocols from 1,052 college student participants (348 male, 704 female) were analyzed. Analyses were conducted on the 131 self-report items comprising the PPI-R's eight content scales, using a graded response model. Scales collected a majority of their information about respondents possessing higher than average levels of the traits being measured. Each scale contained at least some items that evidenced limited ability to differentiate between respondents with differing levels of the trait being measured. Moreover, 80 items (61.1%) yielded significantly different responses between men and women presumably possessing similar levels of the trait being measured. Item performance was also influenced by the scoring format (directly scored vs. reverse-scored) of the items. Overall, the results suggest that the PPI-R, despite identifying psychopathic personality traits in individuals possessing high levels of those traits, may not identify these traits equally well for men and women, and scores are likely influenced by the scoring format of the individual item and scale.

Introduction to bifactor polytomous item response theory analysis.

PubMed

Toland, Michael D; Sulis, Isabella; Giambona, Francesca; Porcu, Mariano; Campbell, Jonathan M

2017-02-01

A bifactor item response theory model can be used to aid in the interpretation of the dimensionality of a multifaceted questionnaire that assumes continuous latent variables underlying the propensity to respond to items. This model can be used to describe the locations of people on a general continuous latent variable as well as on continuous orthogonal specific traits that characterize responses to groups of items. The bifactor graded response (bifac-GR) model is presented in contrast to a correlated traits (or multidimensional GR model) and unidimensional GR model. Bifac-GR model specification, assumptions, estimation, and interpretation are demonstrated with a reanalysis of data (Campbell, 2008) on the Shared Activities Questionnaire. We also show the importance of marginalizing the slopes for interpretation purposes and we extend the concept to the interpretation of the information function. To go along with the illustrative example analyses, we have made available supplementary files that include command file (syntax) examples and outputs from flexMIRT, IRTPRO, R, Mplus, and STATA. Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.jsp.2016.11.001. Data needed to reproduce analyses in this article are available as supplemental materials (online only) in the Appendix of this article. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Non-ignorable missingness item response theory models for choice effects in examinee-selected items.

PubMed

Liu, Chen-Wei; Wang, Wen-Chung

2017-11-01

Examinee-selected item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set, always yields incomplete data (i.e., when only the selected items are answered, data are missing for the others) that are likely non-ignorable in likelihood inference. Standard item response theory (IRT) models become infeasible when ESI data are missing not at random (MNAR). To solve this problem, the authors propose a two-dimensional IRT model that posits one unidimensional IRT model for observed data and another for nominal selection patterns. The two latent variables are assumed to follow a bivariate normal distribution. In this study, the mirt freeware package was adopted to estimate parameters. The authors conduct an experiment to demonstrate that ESI data are often non-ignorable and to determine how to apply the new model to the data collected. Two follow-up simulation studies are conducted to assess the parameter recovery of the new model and the consequences for parameter estimation of ignoring MNAR data. The results of the two simulation studies indicate good parameter recovery of the new model and poor parameter recovery when non-ignorable missing data were mistakenly treated as ignorable. © 2017 The British Psychological Society.

Generalized Full-Information Item Bifactor Analysis

ERIC Educational Resources Information Center

Cai, Li; Yang, Ji Seung; Hansen, Mark

2011-01-01

Full-information item bifactor analysis is an important statistical method in psychological and educational measurement. Current methods are limited to single-group analysis and inflexible in the types of item response models supported. We propose a flexible multiple-group item bifactor analysis framework that supports a variety of…

Support for an auto-associative model of spoken cued recall: evidence from fMRI.

PubMed

de Zubicaray, Greig; McMahon, Katie; Eastburn, Mathew; Pringle, Alan J; Lorenz, Lina; Humphreys, Michael S

2007-03-02

Cued recall and item recognition are considered the standard episodic memory retrieval tasks. However, only the neural correlates of the latter have been studied in detail with fMRI. Using an event-related fMRI experimental design that permits spoken responses, we tested hypotheses from an auto-associative model of cued recall and item recognition [Chappell, M., & Humphreys, M. S. (1994). An auto-associative neural network for sparse representations: Analysis and application to models of recognition and cued recall. Psychological Review, 101, 103-128]. In brief, the model assumes that cues elicit a network of phonological short term memory (STM) and semantic long term memory (LTM) representations distributed throughout the neocortex as patterns of sparse activations. This information is transferred to the hippocampus which converges upon the item closest to a stored pattern and outputs a response. Word pairs were learned from a study list, with one member of the pair serving as the cue at test. Unstudied words were also intermingled at test in order to provide an analogue of yes/no recognition tasks. Compared to incorrectly rejected studied items (misses) and correctly rejected (CR) unstudied items, correctly recalled items (hits) elicited increased responses in the left hippocampus and neocortical regions including the left inferior prefrontal cortex (LIPC), left mid lateral temporal cortex and inferior parietal cortex, consistent with predictions from the model. This network was very similar to that observed in yes/no recognition studies, supporting proposals that cued recall and item recognition involve common rather than separate mechanisms.

Application of Item Response Theory to Modeling of Expanded Disability Status Scale in Multiple Sclerosis.

PubMed

Novakovic, A M; Krekels, E H J; Munafo, A; Ueckert, S; Karlsson, M O

2017-01-01

In this study, we report the development of the first item response theory (IRT) model within a pharmacometrics framework to characterize the disease progression in multiple sclerosis (MS), as measured by Expanded Disability Status Score (EDSS). Data were collected quarterly from a 96-week phase III clinical study by a blinder rater, involving 104,206 item-level observations from 1319 patients with relapsing-remitting MS (RRMS), treated with placebo or cladribine. Observed scores for each EDSS item were modeled describing the probability of a given score as a function of patients' (unobserved) disability using a logistic model. Longitudinal data from placebo arms were used to describe the disease progression over time, and the model was then extended to cladribine arms to characterize the drug effect. Sensitivity with respect to patient disability was calculated as Fisher information for each EDSS item, which were ranked according to the amount of information they contained. The IRT model was able to describe baseline and longitudinal EDSS data on item and total level. The final model suggested that cladribine treatment significantly slows disease-progression rate, with a 20% decrease in disease-progression rate compared to placebo, irrespective of exposure, and effects an additional exposure-dependent reduction in disability progression. Four out of eight items contained 80% of information for the given range of disabilities. This study has illustrated that IRT modeling is specifically suitable for accurate quantification of disease status and description and prediction of disease progression in phase 3 studies on RRMS, by integrating EDSS item-level data in a meaningful manner.

Reliability and validity of a short form household food security scale in a Caribbean community.

PubMed

Gulliford, Martin C; Mahabir, Deepak; Rocke, Brian

2004-06-16

We evaluated the reliability and validity of the short form household food security scale in a different setting from the one in which it was developed. The scale was interview administered to 531 subjects from 286 households in north central Trinidad in Trinidad and Tobago, West Indies. We evaluated the six items by fitting item response theory models to estimate item thresholds, estimating agreement among respondents in the same households and estimating the slope index of income-related inequality (SII) after adjusting for age, sex and ethnicity. Item-score correlations ranged from 0.52 to 0.79 and Cronbach's alpha was 0.87. Item responses gave within-household correlation coefficients ranging from 0.70 to 0.78. Estimated item thresholds (standard errors) from the Rasch model ranged from -2.027 (0.063) for the 'balanced meal' item to 2.251 (0.116) for the 'hungry' item. The 'balanced meal' item had the lowest threshold in each ethnic group even though there was evidence of differential functioning for this item by ethnicity. Relative thresholds of other items were generally consistent with US data. Estimation of the SII, comparing those at the bottom with those at the top of the income scale, gave relative odds for an affirmative response of 3.77 (95% confidence interval 1.40 to 10.2) for the lowest severity item, and 20.8 (2.67 to 162.5) for highest severity item. Food insecurity was associated with reduced consumption of green vegetables after additionally adjusting for income and education (0.52, 0.28 to 0.96). The household food security scale gives reliable and valid responses in this setting. Differing relative item thresholds compared with US data do not require alteration to the cut-points for classification of 'food insecurity without hunger' or 'food insecurity with hunger'. The data provide further evidence that re-evaluation of the 'balanced meal' item is required.

Polytomous Latent Scales for the Investigation of the Ordering of Items

ERIC Educational Resources Information Center

Ligtvoet, Rudy; van der Ark, L. Andries; Bergsma, Wicher P.; Sijtsma, Klaas

2011-01-01

We propose three latent scales within the framework of nonparametric item response theory for polytomously scored items. Latent scales are models that imply an invariant item ordering, meaning that the order of the items is the same for each measurement value on the latent scale. This ordering property may be important in, for example,…

The Impact of Item Position Change on Item Parameters and Common Equating Results under the 3PL Model

ERIC Educational Resources Information Center

Meyers, Jason L.; Murphy, Stephen; Goodman, Joshua; Turhan, Ahmet

2012-01-01

Operational testing programs employing item response theory (IRT) applications benefit from of the property of item parameter invariance whereby item parameter estimates obtained from one sample can be applied to other samples (when the underlying assumptions are satisfied). In theory, this feature allows for applications such as computer-adaptive…

Building an Evaluation Scale using Item Response Theory.

PubMed

Lalor, John P; Wu, Hao; Yu, Hong

2016-11-01

Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption is that all items in a given test set are equal with regards to difficulty and discriminating power. We propose Item Response Theory (IRT) from psychometrics as an alternative means for gold-standard test-set generation and NLP system evaluation. IRT is able to describe characteristics of individual items - their difficulty and discriminating power - and can account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we demonstrate IRT by generating a gold-standard test set for Recognizing Textual Entailment. By collecting a large number of human responses and fitting our IRT model, we show that our IRT model compares NLP systems with the performance in a human population and is able to provide more insight into system performance than standard evaluation metrics. We show that a high accuracy score does not always imply a high IRT score, which depends on the item characteristics and the response pattern.

Building an Evaluation Scale using Item Response Theory

PubMed Central

Lalor, John P.; Wu, Hao; Yu, Hong

2016-01-01

Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption is that all items in a given test set are equal with regards to difficulty and discriminating power. We propose Item Response Theory (IRT) from psychometrics as an alternative means for gold-standard test-set generation and NLP system evaluation. IRT is able to describe characteristics of individual items - their difficulty and discriminating power - and can account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we demonstrate IRT by generating a gold-standard test set for Recognizing Textual Entailment. By collecting a large number of human responses and fitting our IRT model, we show that our IRT model compares NLP systems with the performance in a human population and is able to provide more insight into system performance than standard evaluation metrics. We show that a high accuracy score does not always imply a high IRT score, which depends on the item characteristics and the response pattern.1 PMID:28004039

A Bayesian Approach to Person Fit Analysis in Item Response Theory Models. Research Report.

ERIC Educational Resources Information Center

Glas, Cees A. W.; Meijer, Rob R.

A Bayesian approach to the evaluation of person fit in item response theory (IRT) models is presented. In a posterior predictive check, the observed value on a discrepancy variable is positioned in its posterior distribution. In a Bayesian framework, a Markov Chain Monte Carlo procedure can be used to generate samples of the posterior distribution…

Parent Ratings of ADHD Symptoms: Generalized Partial Credit Model Analysis of Differential Item Functioning across Gender

ERIC Educational Resources Information Center

Gomez, Rapson

2012-01-01

Objective: Generalized partial credit model, which is based on item response theory (IRT), was used to test differential item functioning (DIF) for the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed.), inattention (IA), and hyperactivity/impulsivity (HI) symptoms across boys and girls. Method: To accomplish this, parents completed…

Asymptotic Standard Errors of Observed-Score Equating with Polytomous IRT Models

ERIC Educational Resources Information Center

Andersson, Björn

2016-01-01

In observed-score equipercentile equating, the goal is to make scores on two scales or tests measuring the same construct comparable by matching the percentiles of the respective score distributions. If the tests consist of different items with multiple categories for each item, a suitable model for the responses is a polytomous item response…

An Investigation of the Performance of the Generalized S-X[superscript 2] Item-Fit Index for Polytomous IRT Models. ACT Research Report Series, 2007-1

ERIC Educational Resources Information Center

Kang, Taehoon; Chen, Troy T.

2007-01-01

Orlando and Thissen (2000, 2003) proposed an item-fit index, S-X[superscript 2], for dichotomous item response theory (IRT) models, which has performed better than traditional item-fit statistics such as Yen's (1981) Q[subscript 1] and McKinley and Mill's (1985) G[superscript 2]. This study extends the utility of S-X[superscript 2] to polytomous…

Rasch measurement: the Arm Activity measure (ArmA) passive function sub-scale.

PubMed

Ashford, Stephen; Siegert, Richard J; Alexandrescu, Roxana

2016-01-01

To evaluate the conformity of the Arm Activity measure (ArmA) passive function sub-scale to the Rasch model. A consecutive cohort of patients (n = 92) undergoing rehabilitation, including upper limb rehabilitation and spasticity management, at two specialist rehabilitation units were included. Rasch analysis was used to examine scaling and conformity to the model. Responses were analysed using Rasch unidimensional measurement models (RUMM 2030). The following aspects were considered: overall model and individual item fit statistics and fit residuals, internal reliability, item response threshold ordering, item bias, local dependency and unidimensionality. ArmA contains both active and passive function sub-scales, but in this analysis only the passive function sub-scale was considered. Four of the seven items in the ArmA passive function sub-scale initially had disordered thresholds. These items were rescored to four response options, which resulted in ordered thresholds for all items. Once the items with disordered thresholds had been rescored, item bias was not identified for age, global disability level or diagnosis, but with a small difference in difficulty between males and females for one item of the scale. Local dependency was not observed and the unidimensionality of the sub-scale was supported and good fit to the Rasch model was identified. The person separation index (PSI) was 0.95 indicating that the scale is able to reliably differentiate at least two groups of patients. The ArmA passive function sub-scale was shown in this evaluation to conform to the Rasch model once disordered thresholds had been addressed. Using the logit scores produced by the Rasch model it was possible to convert this back to the original scale range. Implications for Rehabilitation The ArmA passive function sub-scale was shown, in this evaluation, to conform to the Rasch model once disordered thresholds had been addressed and therefore to be a clinically applicable and potentially useful hierarchical measure. Using Rasch logit scores it has be possible to convert back to the original ordinal scale range and provide an indication of real change to enable evaluation of clinical outcome of importance to patients and clinicians.

Psychometric properties of the Chinese version of resilience scale specific to cancer: an item response theory analysis.

PubMed

Ye, Zeng Jie; Liang, Mu Zi; Zhang, Hao Wei; Li, Peng Fei; Ouyang, Xue Ren; Yu, Yuan Liang; Liu, Mei Ling; Qiu, Hong Zhong

2018-06-01

Classic theory test has been used to develop and validate the 25-item Resilience Scale Specific to Cancer (RS-SC) in Chinese patients with cancer. This study was designed to provide additional information about the discriminative value of the individual items tested with an item response theory analysis. A two-parameter graded response model was performed to examine whether any of the items of the RS-SC exhibited problems with the ordering and steps of thresholds, as well as the ability of items to discriminate patients with different resilience levels using item characteristic curves. A sample of 214 Chinese patients with cancer diagnosis was analyzed. The established three-dimension structure of the RS-SC was confirmed. Several items showed problematic thresholds or discrimination ability and require further revision. Some problematic items should be refined and a short-form of RS-SC maybe feasible in clinical settings in order to reduce burden on patients. However, the generalizability of these findings warrants further investigations.

Item response theory analysis of the mechanics baseline test

NASA Astrophysics Data System (ADS)

Cardamone, Caroline N.; Abbott, Jonathan E.; Rayyan, Saif; Seaton, Daniel T.; Pawl, Andrew; Pritchard, David E.

2012-02-01

Item response theory is useful in both the development and evaluation of assessments and in computing standardized measures of student performance. In item response theory, individual parameters (difficulty, discrimination) for each item or question are fit by item response models. These parameters provide a means for evaluating a test and offer a better measure of student skill than a raw test score, because each skill calculation considers not only the number of questions answered correctly, but the individual properties of all questions answered. Here, we present the results from an analysis of the Mechanics Baseline Test given at MIT during 2005-2010. Using the item parameters, we identify questions on the Mechanics Baseline Test that are not effective in discriminating between MIT students of different abilities. We show that a limited subset of the highest quality questions on the Mechanics Baseline Test returns accurate measures of student skill. We compare student skills as determined by item response theory to the more traditional measurement of the raw score and show that a comparable measure of learning gain can be computed.

Measuring anxiety after spinal cord injury: Development and psychometric characteristics of the SCI-QOL Anxiety item bank and linkage with GAD-7.

PubMed

Kisala, Pamela A; Tulsky, David S; Kalpakjian, Claire Z; Heinemann, Allen W; Pohlig, Ryan T; Carle, Adam; Choi, Seung W

2015-05-01

To develop a calibrated item bank and computer adaptive test to assess anxiety symptoms in individuals with spinal cord injury (SCI), transform scores to the Patient Reported Outcomes Measurement Information System (PROMIS) metric, and create a statistical linkage with the Generalized Anxiety Disorder (GAD)-7, a widely used anxiety measure. Grounded-theory based qualitative item development methods; large-scale item calibration field testing; confirmatory factor analysis; graded response model item response theory analyses; statistical linking techniques to transform scores to a PROMIS metric; and linkage with the GAD-7. Setting Five SCI Model System centers and one Department of Veterans Affairs medical center in the United States. Participants Adults with traumatic SCI. Spinal Cord Injury-Quality of Life (SCI-QOL) Anxiety Item Bank Seven hundred sixteen individuals with traumatic SCI completed 38 items assessing anxiety, 17 of which were PROMIS items. After 13 items (including 2 PROMIS items) were removed, factor analyses confirmed unidimensionality. Item response theory analyses were used to estimate slopes and thresholds for the final 25 items (15 from PROMIS). The observed Pearson correlation between the SCI-QOL Anxiety and GAD-7 scores was 0.67. The SCI-QOL Anxiety item bank demonstrates excellent psychometric properties and is available as a computer adaptive test or short form for research and clinical applications. SCI-QOL Anxiety scores have been transformed to the PROMIS metric and we provide a method to link SCI-QOL Anxiety scores with those of the GAD-7.

Measuring stigma after spinal cord injury: Development and psychometric characteristics of the SCI-QOL Stigma item bank and short form.

PubMed

Kisala, Pamela A; Tulsky, David S; Pace, Natalie; Victorson, David; Choi, Seung W; Heinemann, Allen W

2015-05-01

To develop a calibrated item bank and computer adaptive test (CAT) to assess the effects of stigma on health-related quality of life in individuals with spinal cord injury (SCI). Grounded-theory based qualitative item development methods, large-scale item calibration field testing, confirmatory factor analysis, and item response theory (IRT)-based psychometric analyses. Five SCI Model System centers and one Department of Veterans Affairs medical center in the United States. Adults with traumatic SCI. SCI-QOL Stigma Item Bank A sample of 611 individuals with traumatic SCI completed 30 items assessing SCI-related stigma. After 7 items were iteratively removed, factor analyses confirmed a unidimensional pool of items. Graded Response Model IRT analyses were used to estimate slopes and thresholds for the final 23 items. The SCI-QOL Stigma item bank is unique not only in the assessment of SCI-related stigma but also in the inclusion of individuals with SCI in all phases of its development. Use of confirmatory factor analytic and IRT methods provide flexibility and precision of measurement. The item bank may be administered as a CAT or as a 10-item fixed-length short form and can be used for research and clinical applications.

Measuring stigma after spinal cord injury: Development and psychometric characteristics of the SCI-QOL Stigma item bank and short form

PubMed Central

Kisala, Pamela A.; Tulsky, David S.; Pace, Natalie; Victorson, David; Choi, Seung W.; Heinemann, Allen W.

2015-01-01

Objective To develop a calibrated item bank and computer adaptive test (CAT) to assess the effects of stigma on health-related quality of life in individuals with spinal cord injury (SCI). Design Grounded-theory based qualitative item development methods, large-scale item calibration field testing, confirmatory factor analysis, and item response theory (IRT)-based psychometric analyses. Setting Five SCI Model System centers and one Department of Veterans Affairs medical center in the United States. Participants Adults with traumatic SCI. Main Outcome Measures SCI-QOL Stigma Item Bank Results A sample of 611 individuals with traumatic SCI completed 30 items assessing SCI-related stigma. After 7 items were iteratively removed, factor analyses confirmed a unidimensional pool of items. Graded Response Model IRT analyses were used to estimate slopes and thresholds for the final 23 items. Conclusions The SCI-QOL Stigma item bank is unique not only in the assessment of SCI-related stigma but also in the inclusion of individuals with SCI in all phases of its development. Use of confirmatory factor analytic and IRT methods provide flexibility and precision of measurement. The item bank may be administered as a CAT or as a 10-item fixed-length short form and can be used for research and clinical applications. PMID:26010973

A Multilevel Multidimensional Item Response Theory Model to Address the Role of Response Style on Measurement of Attitudes in PISA 2006

ERIC Educational Resources Information Center

Lu, Yi

2012-01-01

Cross-national comparisons of responses to survey items are often affected by response style, particularly extreme response style (ERS). ERS varies across cultures, and has the potential to bias inferences in cross-national comparisons. For example, in both PISA and TIMSS assessments, it has been documented that when examined within countries,…

Construct Validity Evidence for Single-Response Items to Estimate Physical Activity Levels in Large Sample Studies

ERIC Educational Resources Information Center

Jackson, Allen W.; Morrow, James R., Jr.; Bowles, Heather R.; FitzGerald, Shannon J.; Blair, Steven N.

2007-01-01

Valid measurement of physical activity is important for studying the risks for morbidity and mortality. The purpose of this study was to examine evidence of construct validity of two similar single-response items assessing physical activity via self-report. Both items are based on the stages of change model. The sample was 687 participants (men =…

Update on the Child's Challenging Behaviour Scale following evaluation using Rasch analysis.

PubMed

Bourke-Taylor, H M; Pallant, J F; Law, M

2014-03-01

The Child's Challenging Behaviour Scale (CCBS) was designed to measure a mother's rating of her child's challenging behaviours. The CCBS was initially developed for mothers of school-aged children with developmental disability and has previously been shown to have good psychometric properties using classical test theory techniques. The aim of this study was to use Rasch analysis to fully evaluate all aspects of the scale, including response format, item fit, dimensionality and targeting. The sample consisted of 152 mothers of a school-aged child (aged 5-18 years) with a disability. Mothers were recruited via websites and mail-out newsletters through not-for-profit organizations that supported families with disabilities. Respondents completed a survey which included the 11 items of the CCBS. Rasch analysis was conducted on these responses using the RUMM2030 package. Rasch analysis of the CCBS revealed serious threshold disordering for nine of the 11 items, suggesting problems with the 5-point response format used for the scale. The neutral midpoint of the response format was subsequently removed to create a 4-point scale. High levels of local dependency were detected among two pairs of items, resulting in the removal of two items (item 7 and item 1). The final nine-item version of the scale (CCBS Version 2) was unidimensional, well targeted, showed good fit to the Rasch model, and strong internal consistency. To achieve fit to the Rasch model it was necessary to make two modifications to the CCBS scale. The resulting nine-item scale with a 4-point response format showed excellent psychometric properties, supporting its internal validity. © 2013 John Wiley & Sons Ltd.

Bayesian Estimation of the Logistic Positive Exponent IRT Model

ERIC Educational Resources Information Center

Bolfarine, Heleno; Bazan, Jorge Luis

2010-01-01

A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric…

Differential item functioning analysis of the Vanderbilt Expertise Test for cars

PubMed Central

Lee, Woo-Yeol; Cho, Sun-Joo; McGugin, Rankin W.; Van Gulick, Ana Beth; Gauthier, Isabel

2015-01-01

The Vanderbilt Expertise Test for cars (VETcar) is a test of visual learning for contemporary car models. We used item response theory to assess the VETcar and in particular used differential item functioning (DIF) analysis to ask if the test functions the same way in laboratory versus online settings and for different groups based on age and gender. An exploratory factor analysis found evidence of multidimensionality in the VETcar, although a single dimension was deemed sufficient to capture the recognition ability measured by the test. We selected a unidimensional three-parameter logistic item response model to examine item characteristics and subject abilities. The VETcar had satisfactory internal consistency. A substantial number of items showed DIF at a medium effect size for test setting and for age group, whereas gender DIF was negligible. Because online subjects were on average older than those tested in the lab, we focused on the age groups to conduct a multigroup item response theory analysis. This revealed that most items on the test favored the younger group. DIF could be more the rule than the exception when measuring performance with familiar object categories, therefore posing a challenge for the measurement of either domain-general visual abilities or category-specific knowledge. PMID:26418499

Modeling the dynamics of recognition memory testing with an integrated model of retrieval and decision making.

PubMed

Osth, Adam F; Jansson, Anna; Dennis, Simon; Heathcote, Andrew

2018-08-01

A robust finding in recognition memory is that performance declines monotonically across test trials. Despite the prevalence of this decline, there is a lack of consensus on the mechanism responsible. Three hypotheses have been put forward: (1) interference is caused by learning of test items (2) the test items cause a shift in the context representation used to cue memory and (3) participants change their speed-accuracy thresholds through the course of testing. We implemented all three possibilities in a combined model of recognition memory and decision making, which inherits the memory retrieval elements of the Osth and Dennis (2015) model and uses the diffusion decision model (DDM: Ratcliff, 1978) to generate choice and response times. We applied the model to four datasets that represent three challenges, the findings that: (1) the number of test items plays a larger role in determining performance than the number of studied items, (2) performance decreases less for strong items than weak items in pure lists but not in mixed lists, and (3) lexical decision trials interspersed between recognition test trials do not increase the rate at which performance declines. Analysis of the model's parameter estimates suggests that item interference plays a weak role in explaining the effects of recognition testing, while context drift plays a very large role. These results are consistent with prior work showing a weak role for item noise in recognition memory and that retrieval is a strong cause of context change in episodic memory. Copyright © 2018 Elsevier Inc. All rights reserved.

Thirty Years of Nonparametric Item Response Theory.

ERIC Educational Resources Information Center

Molenaar, Ivo W.

2001-01-01

Discusses relationships between a mathematical measurement model and its real-world applications. Makes a distinction between large-scale data matrices commonly found in educational measurement and smaller matrices found in attitude and personality measurement. Also evaluates nonparametric methods for estimating item response functions and…

Students' proficiency scores within multitrait item response theory

NASA Astrophysics Data System (ADS)

Scott, Terry F.; Schumayer, Daniel

2015-12-01

In this paper we present a series of item response models of data collected using the Force Concept Inventory. The Force Concept Inventory (FCI) was designed to poll the Newtonian conception of force viewed as a multidimensional concept, that is, as a complex of distinguishable conceptual dimensions. Several previous studies have developed single-trait item response models of FCI data; however, we feel that multidimensional models are also appropriate given the explicitly multidimensional design of the inventory. The models employed in the research reported here vary in both the number of fitting parameters and the number of underlying latent traits assumed. We calculate several model information statistics to ensure adequate model fit and to determine which of the models provides the optimal balance of information and parsimony. Our analysis indicates that all item response models tested, from the single-trait Rasch model through to a model with ten latent traits, satisfy the standard requirements of fit. However, analysis of model information criteria indicates that the five-trait model is optimal. We note that an earlier factor analysis of the same FCI data also led to a five-factor model. Furthermore the factors in our previous study and the traits identified in the current work match each other well. The optimal five-trait model assigns proficiency scores to all respondents for each of the five traits. We construct a correlation matrix between the proficiencies in each of these traits. This correlation matrix shows strong correlations between some proficiencies, and strong anticorrelations between others. We present an interpretation of this correlation matrix.

Do Adaptive Representations of the Item-Position Effect in APM Improve Model Fit? A Simulation Study

ERIC Educational Resources Information Center

Zeller, Florian; Krampen, Dorothea; Reiß, Siegbert; Schweizer, Karl

2017-01-01

The item-position effect describes how an item's position within a test, that is, the number of previous completed items, affects the response to this item. Previously, this effect was represented by constraints reflecting simple courses, for example, a linear increase. Due to the inflexibility of these representations our aim was to examine…

An Investigation of Item Fit Statistics for Mixed IRT Models

ERIC Educational Resources Information Center

Chon, Kyong Hee

2009-01-01

The purpose of this study was to investigate procedures for assessing model fit of IRT models for mixed format data. In this study, various IRT model combinations were fitted to data containing both dichotomous and polytomous item responses, and the suitability of the chosen model mixtures was evaluated based on a number of model fit procedures.…

A Comparison of Different Psychometric Approaches to Modeling Testlet Structures: An Example with C-Tests

ERIC Educational Resources Information Center

Schroeders, Ulrich; Robitzsch, Alexander; Schipolowski, Stefan

2014-01-01

C-tests are a specific variant of cloze tests that are considered time-efficient, valid indicators of general language proficiency. They are commonly analyzed with models of item response theory assuming local item independence. In this article we estimated local interdependencies for 12 C-tests and compared the changes in item difficulties,…

Rasch Model Parameter Estimation in the Presence of a Nonnormal Latent Trait Using a Nonparametric Bayesian Approach

ERIC Educational Resources Information Center

Finch, Holmes; Edwards, Julianne M.

2016-01-01

Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…

Improving Measurement in Health Education and Health Behavior Research Using Item Response Modeling: Comparison with the Classical Test Theory Approach

ERIC Educational Resources Information Center

Wilson, Mark; Allen, Diane D.; Li, Jun Corser

2006-01-01

This paper compares the approach and resultant outcomes of item response models (IRMs) and classical test theory (CTT). First, it reviews basic ideas of CTT, and compares them to the ideas about using IRMs introduced in an earlier paper. It then applies a comparison scheme based on the AERA/APA/NCME "Standards for Educational and…

The Divergent Meanings of Life Satisfaction: Item Response Modeling of the Satisfaction with Life Scale in Greenland and Norway

ERIC Educational Resources Information Center

Vitterso, Joar; Biswas-Diener, Robert; Diener, Ed

2005-01-01

Cultural differences in response to the Satisfaction With Life Scale (SWLS) items is investigated. Data were fit to a mixed Rasch model in order to identify latent classes of participants in a combined sample of Norwegians (N = 461) and Greenlanders (N = 180). Initial analyses showed no mean difference in life satisfaction between the two…

A Note on Explaining Away and Paradoxical Results in Multidimensional Item Response Theory. Research Report. ETS RR-12-13

ERIC Educational Resources Information Center

van Rijn, Peter W.; Rijmen, Frank

2012-01-01

Hooker and colleagues addressed a paradoxical situation that can arise in the application of multidimensional item response theory (MIRT) models to educational test data. We demonstrate that this MIRT paradox is an instance of the explaining-away phenomenon in Bayesian networks, and we attempt to enhance the understanding of MIRT models by placing…

Adjusting the Adjusted X[superscript 2]/df Ratio Statistic for Dichotomous Item Response Theory Analyses: Does the Model Fit?

ERIC Educational Resources Information Center

Tay, Louis; Drasgow, Fritz

2012-01-01

Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…

Validation of the brief version of the Recovery Self-Assessment (RSA-B) using Rasch measurement theory.

PubMed

Barbic, Skye P; Kidd, Sean A; Davidson, Larry; McKenzie, Kwame; O'Connell, Maria J

2015-12-01

In psychiatry, the recovery paradigm is increasingly identified as the overarching framework for service provision. Currently, the Recovery Self-Assessment (RSA), a 36-item rating scale, is commonly used to assess the uptake of a recovery orientation in clinical services. However, the consumer version of the RSA has been found challenging to complete because of length and the reading level required. In response to this feedback, a brief 12-item version of the RSA was developed (RSA-B). This article describes the development of the modified instrument and the application of traditional psychometric analysis and Rasch Measurement Theory to test the psychometrics properties of the RSA-B. Data from a multisite study of adults with serious mental illnesses (n = 1256) who were followed by assertive community treatment teams were examined for reliability, clinical meaning, targeting, response categories, model fit, reliability, dependency, and raw interval-level measurement. Analyses were performed using the Rasch Unidimensional Measurement Model (RUMM 2030). Adequate fit to the Rasch model was observed (χ2 = 112.46, df = 90, p = .06) and internal consistency was good (r = .86). However, Rasch analysis revealed limitations of the 12-item version, with items covering only 39% of the targeted theoretical continuum, 2 misfitting items, and strong evidence for the 5 option response categories not working as intended. This study revealed areas for improvement in the shortened version of the 12-item RSA-B. A revisit of the conceptual model and original 36-item rating scale is encouraged to select items that will help practitioners and researchers measure the full range of recovery orientation. (c) 2015 APA, all rights reserved).

Statistical Indexes for Monitoring Item Behavior under Computer Adaptive Testing Environment.

ERIC Educational Resources Information Center

Zhu, Renbang; Yu, Feng; Liu, Su

A computerized adaptive test (CAT) administration usually requires a large supply of items with accurately estimated psychometric properties, such as item response theory (IRT) parameter estimates, to ensure the precision of examinee ability estimation. However, an estimated IRT model of a given item in any given pool does not always correctly…

Affective Outcomes of Schooling: Full-Information Item Factor Analysis of a Student Questionnaire.

ERIC Educational Resources Information Center

Muraki, Eiji; Engelhard, George, Jr.

Recent developments in dichotomous factor analysis based on multidimensional item response models (Bock and Aitkin, 1981; Muthen, 1978) provide an effective method for exploring the dimensionality of questionnaire items. Implemented in the TESTFACT program, this "full information" item factor analysis accounts not only for the pairwise joint…

ASCAL: A Microcomputer Program for Estimating Logistic IRT Item Parameters.

ERIC Educational Resources Information Center

Vale, C. David; Gialluca, Kathleen A.

ASCAL is a microcomputer-based program for calibrating items according to the three-parameter logistic model of item response theory. It uses a modified multivariate Newton-Raphson procedure for estimating item parameters. This study evaluated this procedure using Monte Carlo Simulation Techniques. The current version of ASCAL was then compared to…

The Social Physique Anxiety Scale: an example of the potential consequence of negatively worded items in factorial validity studies.

PubMed

Motl, R W; Conroy, D E; Horan, P M

2000-01-01

Social physique anxiety (SPA) based on Hart, Leary, and Rejeski's (1989) Social Physique Anxiety Scale (SPAS) was originally conceptualized to be a unidimensional construct. Empirical evidence on the factorial validity of the SPAS has been contradictory, yielding both one- and two-factor models. The two-factor model, which consists of separate factors associated with positively and negatively worded items, has stimulated an ongoing debate about the dimensionality and content of the SPAS. The present study employed confirmatory factor analysis (CFA) to examine whether the two-factor solution to the 12-item SPAS was substantively meaningful or a methodological artifact. Results of the CFAs, which were performed on responses from four different samples (Eklund, Kelley, and Wilson, 1997; Eklund, Mack, and Hart, 1996), supported the existence of a single substantive SPA factor underlying responses to the 12-item SPAS. There were, in addition, method effects associated with the negatively worded items that could be modeled to achieve good fit. Therefore, it was concluded that a single substantive factor and a non-substantive method effect primarily related to the negatively worded items best represented the 12-item SPAS.

Evaluating the validity of the Work Role Functioning Questionnaire (Canadian French version) using classical test theory and item response theory.

PubMed

Hong, Quan Nha; Coutu, Marie-France; Berbiche, Djamal

2017-01-01

The Work Role Functioning Questionnaire (WRFQ) was developed to assess workers' perceived ability to perform job demands and is used to monitor presenteeism. Still few studies on its validity can be found in the literature. The purpose of this study was to assess the items and factorial composition of the Canadian French version of the WRFQ (WRFQ-CF). Two measurement approaches were used to test the WRFQ-CF: Classical Test Theory (CTT) and non-parametric Item Response Theory (IRT). A total of 352 completed questionnaires were analyzed. A four-factor and three-factor model models were tested and shown respectively good fit with 14 items (Root Mean Square Error of Approximation (RMSEA) = 0.06, Standardized Root Mean Square Residual (SRMR) = 0.04, Bentler Comparative Fit Index (CFI) = 0.98) and with 17 items (RMSEA = 0.059, SRMR = 0.048, CFI = 0.98). Using IRT, 13 problematic items were identified, of which 9 were common with CTT. This study tested different models with fewer problematic items found in a three-factor model. Using a non-parametric IRT and CTT for item purification gave complementary results. IRT is still scarcely used and can be an interesting alternative method to enhance the quality of a measurement instrument. More studies are needed on the WRFQ-CF to refine its items and factorial composition.

Modeling Composite Assessment Data Using Item Response Theory

PubMed Central

Ueckert, Sebastian

2018-01-01

Composite assessments aim to combine different aspects of a disease in a single score and are utilized in a variety of therapeutic areas. The data arising from these evaluations are inherently discrete with distinct statistical properties. This tutorial presents the framework of the item response theory (IRT) for the analysis of this data type in a pharmacometric context. The article considers both conceptual (terms and assumptions) and practical questions (modeling software, data requirements, and model building). PMID:29493119

Linking Parameter Estimates Derived from an Item Response Model through Separate Calibrations. Research Report. ETS RR-09-40

ERIC Educational Resources Information Center

Haberman, Shelby J.

2009-01-01

A regression procedure is developed to link simultaneously a very large number of item response theory (IRT) parameter estimates obtained from a large number of test forms, where each form has been separately calibrated and where forms can be linked on a pairwise basis by means of common items. An application is made to forms in which a…

Do large-scale assessments measure students' ability to integrate scientific knowledge?

NASA Astrophysics Data System (ADS)

Lee, Hee-Sun

2010-03-01

Large-scale assessments are used as means to diagnose the current status of student achievement in science and compare students across schools, states, and countries. For efficiency, multiple-choice items and dichotomously-scored open-ended items are pervasively used in large-scale assessments such as Trends in International Math and Science Study (TIMSS). This study investigated how well these items measure secondary school students' ability to integrate scientific knowledge. This study collected responses of 8400 students to 116 multiple-choice and 84 open-ended items and applied an Item Response Theory analysis based on the Rasch Partial Credit Model. Results indicate that most multiple-choice items and dichotomously-scored open-ended items can be used to determine whether students have normative ideas about science topics, but cannot measure whether students integrate multiple pieces of relevant science ideas. Only when the scoring rubric is redesigned to capture subtle nuances of student open-ended responses, open-ended items become a valid and reliable tool to assess students' knowledge integration ability.

IRT Model Selection Methods for Dichotomous Items

ERIC Educational Resources Information Center

Kang, Taehoon; Cohen, Allan S.

2007-01-01

Fit of the model to the data is important if the benefits of item response theory (IRT) are to be obtained. In this study, the authors compared model selection results using the likelihood ratio test, two information-based criteria, and two Bayesian methods. An example illustrated the potential for inconsistency in model selection depending on…

Testing for Aberrant Behavior in Response Time Modeling

ERIC Educational Resources Information Center

Marianti, Sukaesi; Fox, Jean-Paul; Avetisyan, Marianna; Veldkamp, Bernard P.; Tijmstra, Jesper

2014-01-01

Many standardized tests are now administered via computer rather than paper-and-pencil format. In a computer-based testing environment, it is possible to record not only the test taker's response to each question (item) but also the amount of time spent by the test taker in considering and answering each item. Response times (RTs) provide…

Development and Standardization of the Diagnostic Adaptive Behavior Scale: Application of Item Response Theory to the Assessment of Adaptive Behavior.

PubMed

Tassé, Marc J; Schalock, Robert L; Thissen, David; Balboni, Giulia; Bersani, Henry Hank; Borthwick-Duffy, Sharon A; Spreat, Scott; Widaman, Keith F; Zhang, Dalun; Navas, Patricia

2016-03-01

The Diagnostic Adaptive Behavior Scale (DABS) was developed using item response theory (IRT) methods and was constructed to provide the most precise and valid adaptive behavior information at or near the cutoff point of making a decision regarding a diagnosis of intellectual disability. The DABS initial item pool consisted of 260 items. Using IRT modeling and a nationally representative standardization sample, the item set was reduced to 75 items that provide the most precise adaptive behavior information at the cutoff area determining the presence or not of significant adaptive behavior deficits across conceptual, social, and practical skills. The standardization of the DABS is described and discussed.

What You Don't Know Can Hurt You: Missing Data and Partial Credit Model Estimates

PubMed Central

Thomas, Sarah L.; Schmidt, Karen M.; Erbacher, Monica K.; Bergeman, Cindy S.

2017-01-01

The authors investigated the effect of Missing Completely at Random (MCAR) item responses on partial credit model (PCM) parameter estimates in a longitudinal study of Positive Affect. Participants were 307 adults from the older cohort of the Notre Dame Study of Health and Well-Being (Bergeman and Deboeck, 2014) who completed questionnaires including Positive Affect items for 56 days. Additional missing responses were introduced to the data, randomly replacing 20%, 50%, and 70% of the responses on each item and each day with missing values, in addition to the existing missing data. Results indicated that item locations and person trait level measures diverged from the original estimates as the level of degradation from induced missing data increased. In addition, standard errors of these estimates increased with the level of degradation. Thus, MCAR data does damage the quality and precision of PCM estimates. PMID:26784376

Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes: Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.

PubMed

Finbråten, Hanne Søberg; Pettersen, Kjell Sverre; Wilde-Larsson, Bodil; Nordström, Gun; Trollvik, Anne; Guttersrud, Øystein

2017-11-01

To validate the European Health Literacy Survey Questionnaire (HLS-EU-Q47) in people with type 2 diabetes mellitus. The HLS-EU-Q47 latent variable is outlined in a framework with four cognitive domains integrated in three health domains, implying 12 theoretically defined subscales. Valid and reliable health literacy measurers are crucial to effectively adapt health communication and education to individuals and groups of patients. Cross-sectional study applying confirmatory latent trait analyses. Using a paper-and-pencil self-administered approach, 388 adults responded in March 2015. The data were analysed using the Rasch methodology and confirmatory factor analysis. Response violation (response dependency) and trait violation (multidimensionality) of local independence were identified. Fitting the "multidimensional random coefficients multinomial logit" model, 1-, 3- and 12-dimensional Rasch models were applied and compared. Poor model fit and differential item functioning were present in some items, and several subscales suffered from poor targeting and low reliability. Despite multidimensional data, we did not observe any unordered response categories. Interpreting the domains as distinct but related latent dimensions, the data fit a 12-dimensional Rasch model and a 12-factor confirmatory factor model best. Therefore, the analyses did not support the estimation of one overall "health literacy score." To support the plausibility of claims based on the HLS-EU score(s), we suggest: removing the health care aspect to reduce the magnitude of multidimensionality; rejecting redundant items to avoid response dependency; adding "harder" items and applying a six-point rating scale to improve subscale targeting and reliability; and revising items to improve model fit and avoid bias owing to person factors. © 2017 John Wiley & Sons Ltd.

Measuring Constructs in Family Science: How Can Item Response Theory Improve Precision and Validity?

PubMed Central

Gordon, Rachel A.

2014-01-01

This article provides family scientists with an understanding of contemporary measurement perspectives and the ways in which item response theory (IRT) can be used to develop measures with desired evidence of precision and validity for research uses. The article offers a nontechnical introduction to some key features of IRT, including its orientation toward locating items along an underlying dimension and toward estimating precision of measurement for persons with different levels of that same construct. It also offers a didactic example of how the approach can be used to refine conceptualization and operationalization of constructs in the family sciences, using data from the National Longitudinal Survey of Youth 1979 (n = 2,732). Three basic models are considered: (a) the Rasch and (b) two-parameter logistic models for dichotomous items and (c) the Rating Scale Model for multicategory items. Throughout, the author highlights the potential for researchers to elevate measurement to a level on par with theorizing and testing about relationships among constructs. PMID:25663714

Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods

ERIC Educational Resources Information Center

Rabe-Hesketh, Sophia; Skrondal, Anders

2007-01-01

Composite links and exploded likelihoods are powerful yet simple tools for specifying a wide range of latent variable models. Applications considered include survival or duration models, models for rankings, small area estimation with census information, models for ordinal responses, item response models with guessing, randomized response models,…

Assessing Dimensionality of Noncompensatory Multidimensional Item Response Theory with Complex Structures

ERIC Educational Resources Information Center

Svetina, Dubravka

2013-01-01

The purpose of this study was to investigate the effect of complex structure on dimensionality assessment in noncompensatory multidimensional item response models using dimensionality assessment procedures based on DETECT (dimensionality evaluation to enumerate contributing traits) and NOHARM (normal ogive harmonic analysis robust method). Five…

Rasch analysis of the Chedoke-McMaster Attitudes towards Children with Handicaps scale.

PubMed

Armstrong, Megan; Morris, Christopher; Tarrant, Mark; Abraham, Charles; Horton, Mike C

2017-02-01

Aim To assess whether the Chedoke-McMaster Attitudes towards Children with Handicaps (CATCH) 36-item total scale and subscales fit the unidimensional Rasch model. Method The CATCH was administered to 1881 children, aged 7-16 years in a cross-sectional survey. Data were used from a random sample of 416 for the initial Rasch analysis. The analysis was performed on the 36-item scale and then separately for each subscale. The analysis explored fit to the Rasch model in terms of overall scale fit, individual item fit, item response categories, and unidimensionality. Item bias for gender and school level was also assessed. Revised scales were then tested on an independent second random sample of 415 children. Results Analyses indicated that the 36-item overall scale was not unidimensional and did not fit the Rasch model. Two scales of affective attitudes and behavioural intention were retained after four items were removed from each due to misfit to the Rasch model. Additionally, the scaling was improved when the two most negative response categories were aggregated. There was no item bias by gender or school level on the revised scales. Items assessing cognitive attitudes did not fit the Rasch model and had low internal consistency as a scale. Conclusion Affective attitudes and behavioural intention CATCH sub-scales should be treated separately. Caution should be exercised when using the cognitive subscale. Implications for Rehabilitation The 36-item Chedoke-McMaster Attitudes towards Children with Handicaps (CATCH) scale as a whole did not fit the Rasch model; thus indicating a multi-dimensional scale. Researchers should use two revised eight-item subscales of affective attitudes and behavioural intentions when exploring interventions aiming to improve children's attitudes towards disabled people or factors associated with those attitudes. Researchers should use the cognitive subscale with caution, as it did not create a unidimensional and internally consistent scale. Therefore, conclusions drawn from this scale may not accurately reflect children's attitudes.

A Measurement Model for Likert Responses that Incorporates Response Time

ERIC Educational Resources Information Center

Ferrando, Pere J.; Lorenzo-Seva, Urbano

2007-01-01

This article describes a model for response times that is proposed as a supplement to the usual factor-analytic model for responses to graded or more continuous typical-response items. The use of the proposed model together with the factor model provides additional information about the respondent and can potentially increase the accuracy of the…

Comparing Different Approaches of Bias Correction for Ability Estimation in IRT Models. Research Report. ETS RR-08-13

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; Zhang, Jinming

2008-01-01

The method of maximum-likelihood is typically applied to item response theory (IRT) models when the ability parameter is estimated while conditioning on the true item parameters. In practice, the item parameters are unknown and need to be estimated first from a calibration sample. Lewis (1985) and Zhang and Lu (2007) proposed the expected response…

Looking Closer at the Effects of Framing on Risky Choice: An Item Response Theory Analysis.

PubMed

Sickar; Highhouse

1998-07-01

Item response theory (IRT) methodology allowed an in-depth examination of several issues that would be difficult to explore using traditional methodology. IRT models were estimated for 4 risky-choice items, answered by students under either a gain or loss frame. Results supported the typical framing finding of risk-aversion for gains and risk-seeking for losses but also suggested that a latent construct we label preference for risk was influential in predicting risky choice. Also, the Asian Disease item, most often used in framing research, was found to have anomalous statistical properties when compared to other framing items. Copyright 1998 Academic Press.

Modeling Local Item Dependence in Cloze and Reading Comprehension Test Items Using Testlet Response Theory

ERIC Educational Resources Information Center

Baghaei, Purya; Ravand, Hamdollah

2016-01-01

In this study the magnitudes of local dependence generated by cloze test items and reading comprehension items were compared and their impact on parameter estimates and test precision was investigated. An advanced English as a foreign language reading comprehension test containing three reading passages and a cloze test was analyzed with a…

Ethnic Group Bias in Intelligence Test Items.

ERIC Educational Resources Information Center

Scheuneman, Janice

In previous studies of ethnic group bias in intelligence test items, the question of bias has been confounded with ability differences between the ethnic group samples compared. The present study is based on a conditional probability model in which an unbiased item is defined as one where the probability of a correct response to an item is the…

Application of a Method of Estimating DIF for Polytomous Test Items.

ERIC Educational Resources Information Center

Camilli, Gregory; Congdon, Peter

1999-01-01

Demonstrates a method for studying differential item functioning (DIF) that can be used with dichotomous or polytomous items and that is valid for data that follow a partial credit Item Response Theory model. A simulation study shows that positively biased Type I error rates are in accord with results from previous studies. (SLD)

Comparing and Combining Dichotomous and Polytomous Items with SPRT Procedure in Computerized Classification Testing.

ERIC Educational Resources Information Center

Lau, C. Allen; Wang, Tianyou

The purposes of this study were to: (1) extend the sequential probability ratio testing (SPRT) procedure to polytomous item response theory (IRT) models in computerized classification testing (CCT); (2) compare polytomous items with dichotomous items using the SPRT procedure for their accuracy and efficiency; (3) study a direct approach in…

The Effect of Including or Excluding Students with Testing Accommodations on IRT Calibrations.

ERIC Educational Resources Information Center

Karkee, Thakur; Lewis, Dan M.; Barton, Karen; Haug, Carolyn

This study aimed to determine the degree to which the inclusion of accommodated students with disabilities in the calibration sample affects the characteristics of item parameters and the test results. Investigated were effects on test reliability, item fit to the applicable item response theory (IRT) model, item parameter estimates, and students'…

A Bivariate Generalized Linear Item Response Theory Modeling Framework to the Analysis of Responses and Response Times.

PubMed

Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J

2015-01-01

A generalized linear modeling framework to the analysis of responses and response times is outlined. In this framework, referred to as bivariate generalized linear item response theory (B-GLIRT), separate generalized linear measurement models are specified for the responses and the response times that are subsequently linked by cross-relations. The cross-relations can take various forms. Here, we focus on cross-relations with a linear or interaction term for ability tests, and cross-relations with a curvilinear term for personality tests. In addition, we discuss how popular existing models from the psychometric literature are special cases in the B-GLIRT framework depending on restrictions in the cross-relation. This allows us to compare existing models conceptually and empirically. We discuss various extensions of the traditional models motivated by practical problems. We also illustrate the applicability of our approach using various real data examples, including data on personality and cognitive ability.

Using structural equation modeling to detect response shifts and true change in discrete variables: an application to the items of the SF-36.

PubMed

Verdam, Mathilde G E; Oort, Frans J; Sprangers, Mirjam A G

2016-06-01

The structural equation modeling (SEM) approach for detection of response shift (Oort in Qual Life Res 14:587-598, 2005. doi: 10.1007/s11136-004-0830-y ) is especially suited for continuous data, e.g., questionnaire scales. The present objective is to explain how the SEM approach can be applied to discrete data and to illustrate response shift detection in items measuring health-related quality of life (HRQL) of cancer patients. The SEM approach for discrete data includes two stages: (1) establishing a model of underlying continuous variables that represent the observed discrete variables, (2) using these underlying continuous variables to establish a common factor model for the detection of response shift and to assess true change. The proposed SEM approach was illustrated with data of 485 cancer patients whose HRQL was measured with the SF-36, before and after start of antineoplastic treatment. Response shift effects were detected in items of the subscales mental health, physical functioning, role limitations due to physical health, and bodily pain. Recalibration response shifts indicated that patients experienced relatively fewer limitations with "bathing or dressing yourself" (effect size d = 0.51) and less "nervousness" (d = 0.30), but more "pain" (d = -0.23) and less "happiness" (d = -0.16) after antineoplastic treatment as compared to the other symptoms of the same subscale. Overall, patients' mental health improved, while their physical health, vitality, and social functioning deteriorated. No change was found for the other subscales of the SF-36. The proposed SEM approach to discrete data enables response shift detection at the item level. This will lead to a better understanding of the response shift phenomena at the item level and therefore enhances interpretation of change in the area of HRQL.

Modeling Working Memory Tasks on the Item Level

ERIC Educational Resources Information Center

Luo, Dasen; Chen, Guopeng; Zen, Fanlin; Murray, Bronwyn

2010-01-01

Item responses to Digit Span and Letter-Number Sequencing were analyzed to develop a better-refined model of the two working memory tasks using the finite mixture (FM) modeling method. Models with ordinal latent traits were found to better account for the independent sources of the variability in the tasks than those with continuous traits, and…

A Comparison of Uniform DIF Effect Size Estimators under the MIMIC and Rasch Models

ERIC Educational Resources Information Center

Jin, Ying; Myers, Nicholas D.; Ahn, Soyeon; Penfield, Randall D.

2013-01-01

The Rasch model, a member of a larger group of models within item response theory, is widely used in empirical studies. Detection of uniform differential item functioning (DIF) within the Rasch model typically employs null hypothesis testing with a concomitant consideration of effect size (e.g., signed area [SA]). Parametric equivalence between…

Measuring organizational effectiveness in information and communication technology companies using item response theory.

PubMed

Trierweiller, Andréa Cristina; Peixe, Blênio César Severo; Tezza, Rafael; Pereira, Vera Lúcia Duarte do Valle; Pacheco, Waldemar; Bornia, Antonio Cezar; de Andrade, Dalton Francisco

2012-01-01

The aim of this paper is to measure the effectiveness of the organizations Information and Communication Technology (ICT) from the point of view of the manager, using Item Response Theory (IRT). There is a need to verify the effectiveness of these organizations which are normally associated to complex, dynamic, and competitive environments. In academic literature, there is disagreement surrounding the concept of organizational effectiveness and its measurement. A construct was elaborated based on dimensions of effectiveness towards the construction of the items of the questionnaire which submitted to specialists for evaluation. It demonstrated itself to be viable in measuring organizational effectiveness of ICT companies under the point of view of a manager through using Two-Parameter Logistic Model (2PLM) of the IRT. This modeling permits us to evaluate the quality and property of each item placed within a single scale: items and respondents, which is not possible when using other similar tools.

The Value of Item Response Theory in Clinical Assessment: A Review

ERIC Educational Resources Information Center

Thomas, Michael L.

2011-01-01

Item response theory (IRT) and related latent variable models represent modern psychometric theory, the successor to classical test theory in psychological assessment. Although IRT has become prevalent in the measurement of ability and achievement, its contributions to clinical domains have been less extensive. Applications of IRT to clinical…

Item Response Theory Analyses of the Parent and Teacher Ratings of the DSM-IV ADHD Rating Scale

ERIC Educational Resources Information Center

Gomez, Rapson

2008-01-01

The graded response model (GRM), which is based on item response theory (IRT), was used to evaluate the psychometric properties of the inattention and hyperactivity/impulsivity symptoms in an ADHD rating scale. To accomplish this, parents and teachers completed the DSM-IV ADHD Rating Scale (DARS; Gomez et al., "Journal of Child Psychology and…

An Item Response Unfolding Model for Graphic Rating Scales

ERIC Educational Resources Information Center

Liu, Ying

2009-01-01

The graphic rating scale, a measurement tool used in many areas of psychology, usually takes a form of a fixed-length line segment, with both ends bounded and labeled as extreme responses. The raters mark somewhere on the line, and the length of the line segment from one endpoint to the mark is taken as the measure. An item response unfolding…

An introduction to Item Response Theory and Rasch Analysis of the Eating Assessment Tool (EAT-10).

PubMed

Kean, Jacob; Brodke, Darrel S; Biber, Joshua; Gross, Paul

2018-03-01

Item response theory has its origins in educational measurement and is now commonly applied in health-related measurement of latent traits, such as function and symptoms. This application is due in large part to gains in the precision of measurement attributable to item response theory and corresponding decreases in response burden, study costs, and study duration. The purpose of this paper is twofold: introduce basic concepts of item response theory and demonstrate this analytic approach in a worked example, a Rasch model (1PL) analysis of the Eating Assessment Tool (EAT-10), a commonly used measure for oropharyngeal dysphagia. The results of the analysis were largely concordant with previous studies of the EAT-10 and illustrate for brain impairment clinicians and researchers how IRT analysis can yield greater precision of measurement.

Rewards of bridging the divide between measurement and clinical theory: demonstration of a bifactor model for the Brief Symptom Inventory.

PubMed

Thomas, Michael L

2012-03-01

There is growing evidence that psychiatric disorders maintain hierarchical associations where general and domain-specific factors play prominent roles (see D. Watson, 2005). Standard, unidimensional measurement models can fail to capture the meaningful nuances of such complex latent variable structures. The present study examined the ability of the multidimensional item response theory bifactor model (see R. D. Gibbons & D. R. Hedeker, 1992) to improve construct validity by serving as a bridge between measurement and clinical theories. Archival data consisting of 688 outpatients' psychiatric diagnoses and item-level responses to the Brief Symptom Inventory (BSI; L. R. Derogatis, 1993) were extracted from files at a university mental health clinic. The bifactor model demonstrated superior fit for the internal structure of the BSI and improved overall diagnostic accuracy in the sample (73%) compared with unidimensional (61%) and oblique simple structure (65%) models. Consistent with clinical theory, multiple sources of item variance were drawn from individual test items. Test developers and clinical researchers are encouraged to consider model-based measurement in the assessment of psychiatric distress.

Profile-likelihood Confidence Intervals in Item Response Theory Models.

PubMed

Chalmers, R Philip; Pek, Jolynn; Liu, Yang

2017-01-01

Confidence intervals (CIs) are fundamental inferential devices which quantify the sampling variability of parameter estimates. In item response theory, CIs have been primarily obtained from large-sample Wald-type approaches based on standard error estimates, derived from the observed or expected information matrix, after parameters have been estimated via maximum likelihood. An alternative approach to constructing CIs is to quantify sampling variability directly from the likelihood function with a technique known as profile-likelihood confidence intervals (PL CIs). In this article, we introduce PL CIs for item response theory models, compare PL CIs to classical large-sample Wald-type CIs, and demonstrate important distinctions among these CIs. CIs are then constructed for parameters directly estimated in the specified model and for transformed parameters which are often obtained post-estimation. Monte Carlo simulation results suggest that PL CIs perform consistently better than Wald-type CIs for both non-transformed and transformed parameters.

Detection of Differential Item Functioning with Nonlinear Regression: A Non-IRT Approach Accounting for Guessing

ERIC Educational Resources Information Center

Drabinová, Adéla; Martinková, Patrícia

2017-01-01

In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

Bootstrap Standard Errors for Maximum Likelihood Ability Estimates When Item Parameters Are Unknown

ERIC Educational Resources Information Center

Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi

2014-01-01

When item parameter estimates are used to estimate the ability parameter in item response models, the standard error (SE) of the ability estimate must be corrected to reflect the error carried over from item calibration. For maximum likelihood (ML) ability estimates, a corrected asymptotic SE is available, but it requires a long test and the…

Computerized Adaptive Testing for Polytomous Motivation Items: Administration Mode Effects and a Comparison with Short Forms

ERIC Educational Resources Information Center

Hol, A. Michiel; Vorst, Harrie C. M.; Mellenbergh, Gideon J.

2007-01-01

In a randomized experiment (n = 515), a computerized and a computerized adaptive test (CAT) are compared. The item pool consists of 24 polytomous motivation items. Although items are carefully selected, calibration data show that Samejima's graded response model did not fit the data optimally. A simulation study is done to assess possible…

Is the Factor Observed in Investigations on the Item-Position Effect Actually the Difficulty Factor?

ERIC Educational Resources Information Center

Schweizer, Karl; Troche, Stefan

2018-01-01

In confirmatory factor analysis quite similar models of measurement serve the detection of the difficulty factor and the factor due to the item-position effect. The item-position effect refers to the increasing dependency among the responses to successively presented items of a test whereas the difficulty factor is ascribed to the wide range of…

Calibration of an Item Bank for the Assessment of Basque Language Knowledge

ERIC Educational Resources Information Center

Lopez-Cuadrado, Javier; Perez, Tomas A.; Vadillo, Jose A.; Gutierrez, Julian

2010-01-01

The main requisite for a functional computerized adaptive testing system is the need of a calibrated item bank. This text presents the tasks carried out during the calibration of an item bank for assessing knowledge of Basque language. It has been done in terms of the 3-parameter logistic model provided by the item response theory. Besides, this…

Rate of Learning Models, Mental Models, and Item Response Theory

NASA Astrophysics Data System (ADS)

Pritchard, David E.; Lee, Y.; Bao, L.

2006-12-01

We present three learning models that make different assumptions about how the rate of a student's learning depends on the amount that they know already. These are motivated by the mental models of Tabula Rasa, Constructivist, and Tutoring theories. These models predict the postscore for a given prescore after a given period of instruction. Constructivist models show a close connection with Item Response Theory. Comparison with data from both Hake and MIT shows that the Tabula Rasa models not only fit incomparably better, but fit the MIT data within error across a wide range of pretest scores. We discuss the implications of this finding.

Development of a Microsoft Excel tool for one-parameter Rasch model of continuous items: an application to a safety attitude survey.

PubMed

Chien, Tsair-Wei; Shao, Yang; Kuo, Shu-Chun

2017-01-10

Many continuous item responses (CIRs) are encountered in healthcare settings, but no one uses item response theory's (IRT) probabilistic modeling to present graphical presentations for interpreting CIR results. A computer module that is programmed to deal with CIRs is required. To present a computer module, validate it, and verify its usefulness in dealing with CIR data, and then to apply the model to real healthcare data in order to show how the CIR that can be applied to healthcare settings with an example regarding a safety attitude survey. Using Microsoft Excel VBA (Visual Basic for Applications), we designed a computer module that minimizes the residuals and calculates model's expected scores according to person responses across items. Rasch models based on a Wright map and on KIDMAP were demonstrated to interpret results of the safety attitude survey. The author-made CIR module yielded OUTFIT mean square (MNSQ) and person measures equivalent to those yielded by professional Rasch Winsteps software. The probabilistic modeling of the CIR module provides messages that are much more valuable to users and show the CIR advantage over classic test theory. Because of advances in computer technology, healthcare users who are familiar to MS Excel can easily apply the study CIR module to deal with continuous variables to benefit comparisons of data with a logistic distribution and model fit statistics.

A Comparison of Item Fit Statistics for Mixed IRT Models

ERIC Educational Resources Information Center

Chon, Kyong Hee; Lee, Won-Chan; Dunbar, Stephen B.

2010-01-01

In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G[superscript 2], Orlando and Thissen's S-X[superscript 2] and S-G[superscript 2], and Stone's chi[superscript 2*] and G[superscript 2*]. To investigate the…

Vision and Quality of Life Index: validation of the Indian version using Rasch analysis.

PubMed

Gothwal, Vijaya K; Bagga, Deepak K

2013-07-18

A multi-attribute utility instrument (MAUI) consists of a descriptive system in which the items and responses seek information about a concept of the universe of health-related quality of life (QoL), and responses to these items then are weighted and combined to produce the index. To our knowledge, the 6-item Vision and Quality of Life Index (VisQoL) is the only available vision-related MAUI, developed and validated in Australia, specifically for visually impaired (VI) populations. To our knowledge, the psychometric properties of the VisQoL have not yet been investigated in an Indian VI sample; this was the aim of our study. The Indian VisQoL was administered to 349 VI adults face-to-face by a trained interviewer at the Vision Rehabilitation Centres of a tertiary eye care facility, South India. Rasch analysis was used to assess the psychometric properties. Rescoring was necessary for all except one item before ordered thresholds were obtained. All items fit the Rasch model and unidimensionality was confirmed. Person separation was acceptable (2.01), indicating that the instrument can discriminate among three strata of participants" vision-related QoL (VRQoL). The VisQoL items were targeted substantially to the participants" VRQoL (-0.69 logits). One item ("ability to have friendships") demonstrated large differential item functioning by work status; working participants reported the item to be more difficult (-1.13 logits) relative to other items when compared to the nonworking participants. The 6-item Indian VisQoL satisfies unidimensional Rasch model expectations in VI patients. Disordering of response categories was evident; replication is required before a common rescoring option should be considered.

Item development process and analysis of 50 case-based items for implementation on the Korean Nursing Licensing Examination.

PubMed

Park, In Sook; Suh, Yeon Ok; Park, Hae Sook; Kang, So Young; Kim, Kwang Sung; Kim, Gyung Hee; Choi, Yeon-Hee; Kim, Hyun-Ju

2017-01-01

The purpose of this study was to improve the quality of items on the Korean Nursing Licensing Examination by developing and evaluating case-based items that reflect integrated nursing knowledge. We conducted a cross-sectional observational study to develop new case-based items. The methods for developing test items included expert workshops, brainstorming, and verification of content validity. After a mock examination of undergraduate nursing students using the newly developed case-based items, we evaluated the appropriateness of the items through classical test theory and item response theory. A total of 50 case-based items were developed for the mock examination, and content validity was evaluated. The question items integrated 34 discrete elements of integrated nursing knowledge. The mock examination was taken by 741 baccalaureate students in their fourth year of study at 13 universities. Their average score on the mock examination was 57.4, and the examination showed a reliability of 0.40. According to classical test theory, the average level of item difficulty of the items was 57.4% (80%-100% for 12 items; 60%-80% for 13 items; and less than 60% for 25 items). The mean discrimination index was 0.19, and was above 0.30 for 11 items and 0.20 to 0.29 for 15 items. According to item response theory, the item discrimination parameter (in the logistic model) was none for 10 items (0.00), very low for 20 items (0.01 to 0.34), low for 12 items (0.35 to 0.64), moderate for 6 items (0.65 to 1.34), high for 1 item (1.35 to 1.69), and very high for 1 item (above 1.70). The item difficulty was very easy for 24 items (below -2.0), easy for 8 items (-2.0 to -0.5), medium for 6 items (-0.5 to 0.5), hard for 3 items (0.5 to 2.0), and very hard for 9 items (2.0 or above). The goodness-of-fit test in terms of the 2-parameter item response model between the range of 2.0 to 0.5 revealed that 12 items had an ideal correct answer rate. We surmised that the low reliability of the mock examination was influenced by the timing of the test for the examinees and the inappropriate difficulty of the items. Our study suggested a methodology for the development of future case-based items for the Korean Nursing Licensing Examination.

The Usefulness of Differential Item Functioning Methodology in Longitudinal Intervention Studies

USDA-ARS?s Scientific Manuscript database

Perceived self-efficacy (SE) for engaging in physical activity (PA) is a key variable mediating PA change in interventions. The purpose of this study is to demonstrate the usefulness of item response modeling-based (IRM) differential item functioning (DIF) in the investigation of group differences ...

Detecting Local Item Dependence in Polytomous Adaptive Data

ERIC Educational Resources Information Center

Mislevy, Jessica L.; Rupp, Andre A.; Harring, Jeffrey R.

2012-01-01

A rapidly expanding arena for item response theory (IRT) is in attitudinal and health-outcomes survey applications, often with polytomous items. In particular, there is interest in computer adaptive testing (CAT). Meeting model assumptions is necessary to realize the benefits of IRT in this setting, however. Although initial investigations of…

Using Necessary Information to Identify Item Dependence in Passage-Based Reading Comprehension Tests

ERIC Educational Resources Information Center

Baldonado, Angela Argo; Svetina, Dubravka; Gorin, Joanna

2015-01-01

Applications of traditional unidimensional item response theory models to passage-based reading comprehension assessment data have been criticized based on potential violations of local independence. However, simple rules for determining dependency, such as including all items associated with a particular passage, may overestimate the dependency…

IRT Item Parameter Recovery with Marginal Maximum Likelihood Estimation Using Loglinear Smoothing Models

ERIC Educational Resources Information Center

Casabianca, Jodi M.; Lewis, Charles

2015-01-01

Loglinear smoothing (LLS) estimates the latent trait distribution while making fewer assumptions about its form and maintaining parsimony, thus leading to more precise item response theory (IRT) item parameter estimates than standard marginal maximum likelihood (MML). This article provides the expectation-maximization algorithm for MML estimation…

Likelihood-Ratio DIF Testing: Effects of Nonnormality

ERIC Educational Resources Information Center

Woods, Carol M.

2008-01-01

Differential item functioning (DIF) occurs when an item has different measurement properties for members of one group versus another. Likelihood-ratio (LR) tests for DIF based on item response theory (IRT) involve statistically comparing IRT models that vary with respect to their constraints. A simulation study evaluated how violation of the…

Reporting of Subscores Using Multidimensional Item Response Theory

ERIC Educational Resources Information Center

Haberman, Shelby J.; Sinharay, Sandip

2010-01-01

Recently, there has been increasing interest in reporting subscores. This paper examines reporting of subscores using multidimensional item response theory (MIRT) models (e.g., Reckase in "Appl. Psychol. Meas." 21:25-36, 1997; C.R. Rao and S. Sinharay (Eds), "Handbook of Statistics, vol. 26," pp. 607-642, North-Holland, Amsterdam, 2007; Beguin &…

Testing Manifest Monotonicity Using Order-Constrained Statistical Inference

ERIC Educational Resources Information Center

Tijmstra, Jesper; Hessen, David J.; van der Heijden, Peter G. M.; Sijtsma, Klaas

2013-01-01

Most dichotomous item response models share the assumption of latent monotonicity, which states that the probability of a positive response to an item is a nondecreasing function of a latent variable intended to be measured. Latent monotonicity cannot be evaluated directly, but it implies manifest monotonicity across a variety of observed scores,…

Tools of Robustness for Item Response Theory.

ERIC Educational Resources Information Center

Jones, Douglas H.

This paper briefly demonstrates a few of the possibilities of a systematic application of robustness theory, concentrating on the estimation of ability when the true item response model does and does not fit the data. The definition of the maximum likelihood estimator (MLE) of ability is briefly reviewed. After introducing the notion of…

Item Response Theory with Estimation of the Latent Density Using Davidian Curves

ERIC Educational Resources Information Center

Woods, Carol M.; Lin, Nan

2009-01-01

Davidian-curve item response theory (DC-IRT) is introduced, evaluated with simulations, and illustrated using data from the Schedule for Nonadaptive and Adaptive Personality Entitlement scale. DC-IRT is a method for fitting unidimensional IRT models with maximum marginal likelihood estimation, in which the latent density is estimated,…

An Introduction to Item Response Theory for Health Behavior Researchers

ERIC Educational Resources Information Center

Warne, Russell T.; McKyer, E. J. Lisako; Smith, Matthew L.

2012-01-01

Objective: To introduce item response theory (IRT) to health behavior researchers by contrasting it with classical test theory and providing an example of IRT in health behavior. Method: Demonstrate IRT by fitting the 2PL model to substance-use survey data from the Adolescent Health Risk Behavior questionnaire (n = 1343 adolescents). Results: An…

Students' Proficiency Scores within Multitrait Item Response Theory

ERIC Educational Resources Information Center

Scott, Terry F.; Schumayer, Daniel

2015-01-01

In this paper we present a series of item response models of data collected using the Force Concept Inventory. The Force Concept Inventory (FCI) was designed to poll the Newtonian conception of force viewed as a multidimensional concept, that is, as a complex of distinguishable conceptual dimensions. Several previous studies have developed…

Comparison of Reliability Measures under Factor Analysis and Item Response Theory

ERIC Educational Resources Information Center

Cheng, Ying; Yuan, Ke-Hai; Liu, Cheng

2012-01-01

Reliability of test scores is one of the most pervasive psychometric concepts in measurement. Reliability coefficients based on a unifactor model for continuous indicators include maximal reliability rho and an unweighted sum score-based omega, among many others. With increasing popularity of item response theory, a parallel reliability measure pi…

An Evaluation of Item Response Theory Classification Accuracy and Consistency Indices

ERIC Educational Resources Information Center

Wyse, Adam E.; Hao, Shiqi

2012-01-01

This article introduces two new classification consistency indices that can be used when item response theory (IRT) models have been applied. The new indices are shown to be related to Rudner's classification accuracy index and Guo's classification accuracy index. The Rudner- and Guo-based classification accuracy and consistency indices are…

The Sequential Probability Ratio Test and Binary Item Response Models

ERIC Educational Resources Information Center

Nydick, Steven W.

2014-01-01

The sequential probability ratio test (SPRT) is a common method for terminating item response theory (IRT)-based adaptive classification tests. To decide whether a classification test should stop, the SPRT compares a simple log-likelihood ratio, based on the classification bound separating two categories, to prespecified critical values. As has…

Unidimensional and Multidimensional Models for Item Response Theory.

ERIC Educational Resources Information Center

McDonald, Roderick P.

This paper provides an up-to-date review of the relationship between item response theory (IRT) and (nonlinear) common factor theory and draws out of this relationship some implications for current and future research in IRT. Nonlinear common factor analysis yields a natural embodiment of the weak principle of local independence in appropriate…

Adjusting for cross-cultural differences in computer-adaptive tests of quality of life.

PubMed

Gibbons, C J; Skevington, S M

2018-04-01

Previous studies using the WHOQOL measures have demonstrated that the relationship between individual items and the underlying quality of life (QoL) construct may differ between cultures. If unaccounted for, these differing relationships can lead to measurement bias which, in turn, can undermine the reliability of results. We used item response theory (IRT) to assess differential item functioning (DIF) in WHOQOL data from diverse language versions collected in UK, Zimbabwe, Russia, and India (total N = 1332). Data were fitted to the partial credit 'Rasch' model. We used four item banks previously derived from the WHOQOL-100 measure, which provided excellent measurement for physical, psychological, social, and environmental quality of life domains (40 items overall). Cross-cultural differential item functioning was assessed using analysis of variance for item residuals and post hoc Tukey tests. Simulated computer-adaptive tests (CATs) were conducted to assess the efficiency and precision of the four items banks. Splitting item parameters by DIF results in four linked item banks without DIF or other breaches of IRT model assumptions. Simulated CATs were more precise and efficient than longer paper-based alternatives. Assessing differential item functioning using item response theory can identify measurement invariance between cultures which, if uncontrolled, may undermine accurate comparisons in computer-adaptive testing assessments of QoL. We demonstrate how compensating for DIF using item anchoring allowed data from all four countries to be compared on a common metric, thus facilitating assessments which were both sensitive to cultural nuance and comparable between countries.

Cognitive psychology meets psychometric theory: on the relation between process models for decision making and latent variable models for individual differences.

PubMed

van der Maas, Han L J; Molenaar, Dylan; Maris, Gunter; Kievit, Rogier A; Borsboom, Denny

2011-04-01

This article analyzes latent variable models from a cognitive psychology perspective. We start by discussing work by Tuerlinckx and De Boeck (2005), who proved that a diffusion model for 2-choice response processes entails a 2-parameter logistic item response theory (IRT) model for individual differences in the response data. Following this line of reasoning, we discuss the appropriateness of IRT for measuring abilities and bipolar traits, such as pro versus contra attitudes. Surprisingly, if a diffusion model underlies the response processes, IRT models are appropriate for bipolar traits but not for ability tests. A reconsideration of the concept of ability that is appropriate for such situations leads to a new item response model for accuracy and speed based on the idea that ability has a natural zero point. The model implies fundamentally new ways to think about guessing, response speed, and person fit in IRT. We discuss the relation between this model and existing models as well as implications for psychology and psychometrics. 2011 APA, all rights reserved

A semi-parametric within-subject mixture approach to the analyses of responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria; Vermunt, Jeroen K

2018-05-01

In item response theory, modelling the item response times in addition to the item responses may improve the detection of possible between- and within-subject differences in the process that resulted in the responses. For instance, if respondents rely on rapid guessing on some items but not on all, the joint distribution of the responses and response times will be a multivariate within-subject mixture distribution. Suitable parametric methods to detect these within-subject differences have been proposed. In these approaches, a distribution needs to be assumed for the within-class response times. In this paper, it is demonstrated that these parametric within-subject approaches may produce false positives and biased parameter estimates if the assumption concerning the response time distribution is violated. A semi-parametric approach is proposed which resorts to categorized response times. This approach is shown to hardly produce false positives and parameter bias. In addition, the semi-parametric approach results in approximately the same power as the parametric approach. © 2017 The British Psychological Society.

RhinAsthma patient perspective: A Rasch validation study.

PubMed

Molinengo, Giorgia; Baiardini, Ilaria; Braido, Fulvio; Loera, Barbara

2018-02-01

In daily practice, Health-Related Quality of Life (HRQoL) tools are useful for supplementing clinical data with the patient's perspective. To encourage their use by clinicians, the availability of tools that can quickly provide valid results is crucial. A new HRQoL tool has been proposed for patients with asthma and rhinitis: the RhinAsthma Patient Perspective-RAPP. The aim of this study was to evaluate the psychometric robustness of the RAPP using the Item Response Theory (IRT) approach, to evaluate the scalability of items and test whether or not patients use the items response scale correctly. 155 patients (53.5% women, mean age 39.1, range 16-76) were recruited during a multicenter study. RAPP metric properties were investigated using IRT models. Differential item functioning (DIF) was used for gender, age, and asthma control test (ACT). The RAPP adequately fitted the Rating Scale model, demonstrating the equality of the rating scale structure for all items. All statistics on items were satisfactory. The RAPP had adequate internal reliability and showed good ability to discriminate among different groups of participants. DIF analysis indicated that there were no differential item functioning issues for gender. One item showed a DIF by age and four items by ACT. The psychometric evaluation performed using IRT models demonstrated that the RAPP met all the criteria to be considered a reliable and valid method of measurement. From a clinical perspective, this will allow physicians to confidently interpret scores as good indicators of Quality of Life of patients with asthma.

An in-depth psychometric analysis of the Connor-Davidson Resilience Scale: calibration with Rasch-Andrich model.

PubMed

Arias González, Víctor B; Crespo Sierra, María Teresa; Arias Martínez, Benito; Martínez-Molina, Agustín; Ponce, Fernando P

2015-09-23

The Connor-Davidson Resilience Scale (CD-RISC) is inarguably one of the best-known instruments in the field of resilience assessment. However, the criteria for the psychometric quality of the instrument were based only on classical test theory. The aim of this paper has focused on the calibration of the CD-RISC with a nonclinical sample of 444 adults using the Rasch-Andrich Rating Scale Model, in order to clarify its structure and analyze its psychometric properties at the level of item. Two items showed misfit to the model and were eliminated. The remaining 22 items form basically a unidimensional scale. The CD-RISC has good psychometric properties. The fit of both the items and the persons to the Rasch model was good, and the response categories were functioning properly. Two of the items showed differential item functioning. The CD-RISC has an obvious ceiling effect, which suggests to include more difficult items in future versions of the scale.

Parallel interactive retrieval of item and associative information from event memory.

PubMed

Cox, Gregory E; Criss, Amy H

2017-09-01

Memory contains information about individual events (items) and combinations of events (associations). Despite the fundamental importance of this distinction, it remains unclear exactly how these two kinds of information are stored and whether different processes are used to retrieve them. We use both model-independent qualitative properties of response dynamics and quantitative modeling of individuals to address these issues. Item and associative information are not independent and they are retrieved concurrently via interacting processes. During retrieval, matching item and associative information mutually facilitate one another to yield an amplified holistic signal. Modeling of individuals suggests that this kind of facilitation between item and associative retrieval is a ubiquitous feature of human memory. Copyright © 2017 Elsevier Inc. All rights reserved.

Measurement Invariance and the Five-Factor Model of Personality: Asian International and Euro American Cultural Groups.

PubMed

Rollock, David; Lui, P Priscilla

2016-10-01

This study examined measurement invariance of the NEO Five-Factor Inventory (NEO-FFI), assessing the five-factor model (FFM) of personality among Euro American (N = 290) and Asian international (N = 301) students (47.8% women, Mage = 19.69 years). The full 60-item NEO-FFI data fit the expected five-factor structure for both groups using exploratory structural equation modeling, and achieved configural invariance. Only 37 items significantly loaded onto the FFM-theorized factors for both groups and demonstrated metric invariance. Threshold invariance was not supported with this reduced item set. Groups differed the most in the item-factor relationships for Extraversion and Agreeableness, as well as in response styles. Asian internationals were more likely to use midpoint responses than Euro Americans. While the FFM can characterize broad nomothetic patterns of personality traits, metric invariance with only the subset of NEO-FFI items identified limits direct group comparisons of correlation coefficients among personality domains and with other constructs, and of mean differences on personality domains. © The Author(s) 2015.

Development of a Brief Questionnaire to Assess Contraceptive Intent

PubMed Central

Raine-Bennett, Tina R; Rocca, Corinne H

2015-01-01

Objective We sought to develop and validate an instrument that can enable providers to identify young women who may be at risk of contraceptive non-adherence. Methods Item response theory based methods were used to evaluate the psychometric properties of the Contraceptive Intent Questionnaire, a 15-item self-administered questionnaire, based on theory and prior qualitative and quantitative research. The questionnaire was administered to 200 women aged 15–24 years who were initiating contraceptives. We assessed item fit to the item response model, internal consistency, internal structure validity, and differential item functioning. Results All items fit a one-dimensional model. The separation reliability coefficient was 0.73. Participants’ overall scores covered the full range of the scale (0–15), and items appropriately matched the range of participants’ contraceptive intent. Items met the criteria for internal structure validity and most items functioned similarly between groups of women. Conclusion The Contraceptive Intent Questionnaire appears to be a reliable and valid tool. Future testing is needed to assess predictive ability and clinical utility. Practice Implications The Contraceptive Intent Questionnaire may serve as a valid tool to help providers identify women who may have problems with contraceptive adherence, as well as to pinpoint areas in which counseling may be directed. PMID:26104994

Development and psychometric characteristics of the SCI-QOL Pressure Ulcers scale and short form.

PubMed

Kisala, Pamela A; Tulsky, David S; Choi, Seung W; Kirshblum, Steven C

2015-05-01

To develop a self-reported measure of the subjective impact of pressure ulcers on health-related quality of life (HRQOL) in individuals with spinal cord injury (SCI) as part of the SCI quality of life (SCI-QOL) measurement system. Grounded-theory based qualitative item development methods, large-scale item calibration testing, confirmatory factor analysis (CFA), and item response theory-based psychometric analysis. Five SCI Model System centers and one Department of Veterans Affairs medical center in the United States. Adults with traumatic SCI. SCI-QOL Pressure Ulcers scale. 189 individuals with traumatic SCI who experienced a pressure ulcer within the past 7 days completed 30 items related to pressure ulcers. CFA confirmed a unidimensional pool of items. IRT analyses were conducted. A constrained Graded Response Model with a constant slope parameter was used to estimate item thresholds for the 12 retained items. The 12-item SCI-QOL Pressure Ulcers scale is unique in that it is specifically targeted to individuals with spinal cord injury and at every stage of development has included input from individuals with SCI. Furthermore, use of CFA and IRT methods provide flexibility and precision of measurement. The scale may be administered in its entirety or as a 7-item "short form" and is available for both research and clinical practice.

Development of a brief questionnaire to assess contraceptive intent.

PubMed

Raine-Bennett, Tina R; Rocca, Corinne H

2015-11-01

We sought to develop and validate an instrument that can enable providers to identify young women who may be at risk of contraceptive non-adherence. Item response theory based methods were used to evaluate the psychometric properties of the Contraceptive Intent Questionnaire, a 15-item self-administered questionnaire, based on theory and prior qualitative and quantitative research. The questionnaire was administered to 200 women aged 15-24 years who were initiating contraceptives. We assessed item fit to the item response model, internal consistency, internal structure validity, and differential item functioning. All items fit a one-dimensional model. The separation reliability coefficient was 0.73. Participants' overall scores covered the full range of the scale (0-15), and items appropriately matched the range of participants' contraceptive intent. Items met the criteria for internal structure validity and most items functioned similarly between groups of women. The Contraceptive Intent Questionnaire appears to be a reliable and valid tool. Future testing is needed to assess predictive ability and clinical utility. The Contraceptive Intent Questionnaire may serve as a valid tool to help providers identify women who may have problems with contraceptive adherence, as well as to pinpoint areas in which counseling may be directed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Validation of a condition-specific measure for women having an abnormal screening mammography.

PubMed

Brodersen, John; Thorsen, Hanne; Kreiner, Svend

2007-01-01

The aim of this study is to assess the validity of a new condition-specific instrument measuring psychosocial consequences of abnormal screening mammography (PCQ-DK33). The draft version of the PCQ-DK33 was completed on two occasions by 184 women who had received an abnormal screening mammography and on one occasion by 240 women who had received a normal screening result. Item Response Theories and Classical Test Theories were used to analyze data. Construct validity, concurrent validity, known group validity, objectivity and reliability were established by item analysis examining the fit between item responses and Rasch models. Six dimensions covering anxiety, behavioral impact, sense of dejection, impact on sleep, breast examination, and sexuality were identified. One item belonging to the dejection dimension had uniform differential item functioning. Two items not fitting the Rasch models were retained because of high face validity. A sick leave item added useful information when measuring side effects and socioeconomic consequences of breast cancer screening. Five "poor items" were identified and should be deleted from the final instrument. Preliminary evidence for a valid and reliable condition-specific measure for women having an abnormal screening mammography was established. The measure includes 27 "good" items measuring different attributes of the same overall latent structure-the psychosocial consequences of abnormal screening mammography.

Impact of Diagnosticity on the Adequacy of Models for Cognitive Diagnosis under a Linear Attribute Structure: A Simulation Study

ERIC Educational Resources Information Center

de La Torre, Jimmy; Karelitz, Tzur M.

2009-01-01

Compared to unidimensional item response models (IRMs), cognitive diagnostic models (CDMs) based on latent classes represent examinees' knowledge and item requirements using discrete structures. This study systematically examines the viability of retrofitting CDMs to IRM-based data with a linear attribute structure. The study utilizes a procedure…

Probing Lexical Representations: Simultaneous Modeling of Word and Reader Contributions to Multidimensional Lexical Representations

ERIC Educational Resources Information Center

Goodwin, Amanda P.; Gilbert, Jennifer K.; Cho, Sun-Joo; Kearns, Devin M.

2014-01-01

The current study models reader, item, and word contributions to the lexical representations of 39 morphologically complex words for 172 middle school students using a crossed random-effects item response model with multiple outcomes. We report 3 findings. First, results suggest that lexical representations can be characterized by separate but…

Item response theory scoring and the detection of curvilinear relationships.

PubMed

Carter, Nathan T; Dalal, Dev K; Guan, Li; LoPilato, Alexander C; Withrow, Scott A

2017-03-01

Psychologists are increasingly positing theories of behavior that suggest psychological constructs are curvilinearly related to outcomes. However, results from empirical tests for such curvilinear relations have been mixed. We propose that correctly identifying the response process underlying responses to measures is important for the accuracy of these tests. Indeed, past research has indicated that item responses to many self-report measures follow an ideal point response process-wherein respondents agree only to items that reflect their own standing on the measured variable-as opposed to a dominance process, wherein stronger agreement, regardless of item content, is always indicative of higher standing on the construct. We test whether item response theory (IRT) scoring appropriate for the underlying response process to self-report measures results in more accurate tests for curvilinearity. In 2 simulation studies, we show that, regardless of the underlying response process used to generate the data, using the traditional sum-score generally results in high Type 1 error rates or low power for detecting curvilinearity, depending on the distribution of item locations. With few exceptions, appropriate power and Type 1 error rates are achieved when dominance-based and ideal point-based IRT scoring are correctly used to score dominance and ideal point response data, respectively. We conclude that (a) researchers should be theory-guided when hypothesizing and testing for curvilinear relations; (b) correctly identifying whether responses follow an ideal point versus dominance process, particularly when items are not extreme is critical; and (c) IRT model-based scoring is crucial for accurate tests of curvilinearity. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Graded Response Model Based on the Logistic Positive Exponent Family of Models for Dichotomous Responses

ERIC Educational Resources Information Center

Samejima, Fumiko

2008-01-01

Samejima ("Psychometrika "65:319--335, 2000) proposed the logistic positive exponent family of models (LPEF) for dichotomous responses in the unidimensional latent space. The objective of the present paper is to propose and discuss a graded response model that is expanded from the LPEF, in the context of item response theory (IRT). This…

A New Model for Acquiescence at the Interface of Psychometrics and Cognitive Psychology.

PubMed

Plieninger, Hansjörg; Heck, Daniel W

2018-05-29

When measuring psychological traits, one has to consider that respondents often show content-unrelated response behavior in answering questionnaires. To disentangle the target trait and two such response styles, extreme responding and midpoint responding, Böckenholt ( 2012a ) developed an item response model based on a latent processing tree structure. We propose a theoretically motivated extension of this model to also measure acquiescence, the tendency to agree with both regular and reversed items. Substantively, our approach builds on multinomial processing tree (MPT) models that are used in cognitive psychology to disentangle qualitatively distinct processes. Accordingly, the new model for response styles assumes a mixture distribution of affirmative responses, which are either determined by the underlying target trait or by acquiescence. In order to estimate the model parameters, we rely on Bayesian hierarchical estimation of MPT models. In simulations, we show that the model provides unbiased estimates of response styles and the target trait, and we compare the new model and Böckenholt's model in a recovery study. An empirical example from personality psychology is used for illustrative purposes.

Alternative Matching Scores to Control Type I Error of the Mantel-Haenszel Procedure for DIF in Dichotomously Scored Items Conforming to 3PL IRT and Nonparametric 4PBCB Models

ERIC Educational Resources Information Center

Monahan, Patrick O.; Ankenmann, Robert D.

2010-01-01

When the matching score is either less than perfectly reliable or not a sufficient statistic for determining latent proficiency in data conforming to item response theory (IRT) models, Type I error (TIE) inflation may occur for the Mantel-Haenszel (MH) procedure or any differential item functioning (DIF) procedure that matches on summed-item…

An item-response theory approach to safety climate measurement: The Liberty Mutual Safety Climate Short Scales.

PubMed

Huang, Yueng-Hsiang; Lee, Jin; Chen, Zhuo; Perry, MacKenna; Cheung, Janelle H; Wang, Mo

2017-06-01

Zohar and Luria's (2005) safety climate (SC) scale, measuring organization- and group- level SC each with 16 items, is widely used in research and practice. To improve the utility of the SC scale, we shortened the original full-length SC scales. Item response theory (IRT) analysis was conducted using a sample of 29,179 frontline workers from various industries. Based on graded response models, we shortened the original scales in two ways: (1) selecting items with above-average discriminating ability (i.e. offering more than 6.25% of the original total scale information), resulting in 8-item organization-level and 11-item group-level SC scales; and (2) selecting the most informative items that together retain at least 30% of original scale information, resulting in 4-item organization-level and 4-item group-level SC scales. All four shortened scales had acceptable reliability (≥0.89) and high correlations (≥0.95) with the original scale scores. The shortened scales will be valuable for academic research and practical survey implementation in improving occupational safety. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Rasch Analysis for Binary Data with Nonignorable Nonresponses

ERIC Educational Resources Information Center

Bertoli-Barsotti, Lucio; Punzo, Antonio

2013-01-01

This paper introduces a two-dimensional Item Response Theory (IRT) model to deal with nonignorable nonresponses in tests with dichotomous items. One dimension provides information about the omitting behavior, while the other dimension is related to the person's "ability". The idea of embedding an IRT model for missingness into the measurement…

Cognitive Diagnostic Models for Tests with Multiple-Choice and Constructed-Response Items

ERIC Educational Resources Information Center

Kuo, Bor-Chen; Chen, Chun-Hua; Yang, Chih-Wei; Mok, Magdalena Mo Ching

2016-01-01

Traditionally, teachers evaluate students' abilities via their total test scores. Recently, cognitive diagnostic models (CDMs) have begun to provide information about the presence or absence of students' skills or misconceptions. Nevertheless, CDMs are typically applied to tests with multiple-choice (MC) items, which provide less diagnostic…

An Evaluation of Hierarchical Bayes Estimation for the Two- Parameter Logistic Model.

ERIC Educational Resources Information Center

Kim, Seock-Ho

Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item parameters. Simulated data sets were analyzed using two different Bayes estimation procedures, the two-stage hierarchical Bayes estimation (HB2) and the marginal Bayesian with known hyperparameters (MB), and marginal maximum…

Cognitive Diagnostic Attribute-Level Discrimination Indices

ERIC Educational Resources Information Center

Henson, Robert; Roussos, Louis; Douglas, Jeff; He, Xuming

2008-01-01

Cognitive diagnostic models (CDMs) model the probability of correctly answering an item as a function of an examinee's attribute mastery pattern. Because estimation of the mastery pattern involves more than a continuous measure of ability, reliability concepts introduced by classical test theory and item response theory do not apply. The cognitive…

The Impact of Non-attempted and Dually-Attempted Items on Person Abilities Using Item Response Theory

PubMed Central

Sideridis, Georgios D.; Tsaousis, Ioannis; Al Harbi, Khaleel

2016-01-01

The purpose of the present study was to relate response strategy with person ability estimates. Two behavioral strategies were examined: (a) the strategy to skip items in order to save time on timed tests, and, (b) the strategy to select two responses on an item, with the hope that one of them may be considered correct. Participants were 4,422 individuals who were administered a standardized achievement measure related to math, biology, chemistry, and physics. In the present evaluation, only the physics subscale was employed. Two analyses were conducted: (a) a person-based one to identify differences between groups and potential correlates of those differences, and, (b) a measure-based analysis in order to identify the parts of the measure that were responsible for potential group differentiation. For (a) person abilities the 2-PL model was employed and later the 3-PL and 4-PL models in order to estimate upper and lower asymptotes of person abilities. For (b) differential item functioning, differential test functioning, and differential distractor functioning were investigated. Results indicated that there were significant differences between groups with completers having the highest ability compared to both non-attempters and dual responders. There were no significant differences between no-attempters and dual responders. The present findings have implications for response strategy efficacy and measure evaluation, revision, and construction. PMID:27790174

The Impact of Non-attempted and Dually-Attempted Items on Person Abilities Using Item Response Theory.

PubMed

Sideridis, Georgios D; Tsaousis, Ioannis; Al Harbi, Khaleel

2016-01-01

The purpose of the present study was to relate response strategy with person ability estimates. Two behavioral strategies were examined: (a) the strategy to skip items in order to save time on timed tests, and, (b) the strategy to select two responses on an item, with the hope that one of them may be considered correct. Participants were 4,422 individuals who were administered a standardized achievement measure related to math, biology, chemistry, and physics. In the present evaluation, only the physics subscale was employed. Two analyses were conducted: (a) a person-based one to identify differences between groups and potential correlates of those differences, and, (b) a measure-based analysis in order to identify the parts of the measure that were responsible for potential group differentiation. For (a) person abilities the 2-PL model was employed and later the 3-PL and 4-PL models in order to estimate upper and lower asymptotes of person abilities. For (b) differential item functioning, differential test functioning, and differential distractor functioning were investigated. Results indicated that there were significant differences between groups with completers having the highest ability compared to both non-attempters and dual responders. There were no significant differences between no-attempters and dual responders. The present findings have implications for response strategy efficacy and measure evaluation, revision, and construction.

Evaluation of psychometric properties and differential item functioning of 8-item Child Perceptions Questionnaires using item response theory.

PubMed

Yau, David T W; Wong, May C M; Lam, K F; McGrath, Colman

2015-08-19

Four-factor structure of the two 8-item short forms of Child Perceptions Questionnaire CPQ11-14 (RSF:8 and ISF:8) has been confirmed. However, the sum scores are typically reported in practice as a proxy of Oral health-related Quality of Life (OHRQoL), which implied a unidimensional structure. This study first assessed the unidimensionality of 8-item short forms of CPQ11-14. Item response theory (IRT) was employed to offer an alternative and complementary approach of validation and to overcome the limitations of classical test theory assumptions. A random sample of 649 12-year-old school children in Hong Kong was analyzed. Unidimensionality of the scale was tested by confirmatory factor analysis (CFA), principle component analysis (PCA) and local dependency (LD) statistic. Graded response model was fitted to the data. Contribution of each item to the scale was assessed by item information function (IIF). Reliability of the scale was assessed by test information function (TIF). Differential item functioning (DIF) across gender was identified by Wald test and expected score functions. Both CPQ11-14 RSF:8 and ISF:8 did not deviate much from the unidimensionality assumption. Results from CFA indicated acceptable fit of the one-factor model. PCA indicated that the first principle component explained >30 % of the total variation with high factor loadings for both RSF:8 and ISF:8. Almost all LD statistic <10 indicated the absence of local dependency. Flat and low IIFs were observed in the oral symptoms items suggesting little contribution of information to the scale and item removal caused little practical impact. Comparing the TIFs, RSF:8 showed slightly better information than ISF:8. In addition to oral symptoms items, the item "Concerned with what other people think" demonstrated a uniform DIF (p < 0.001). The expected score functions were not much different between boys and girls. Items related to oral symptoms were not informative to OHRQoL and deletion of these items is suggested. The impact of DIF across gender on the overall score was minimal. CPQ11-14 RSF:8 performed slightly better than ISF:8 in measurement precision. The 6-item short forms suggested by IRT validation should be further investigated to ensure their robustness, responsiveness and discriminative performance.

An item response theory analysis of the narcissistic personality inventory.

PubMed

Ackerman, Robert A; Donnellan, M Brent; Robins, Richard W

2012-01-01

This research uses item response theory methods to evaluate the Narcissistic Personality Inventory (NPI; Raskin & Terry, 1988). Analyses using the 2-parameter logistic model were conducted on the total score and the Corry, Merritt, Mrug, and Pamp (2008) and Ackerman et al. (2011) subscales for the NPI. In addition to offering precise information about the psychometric properties of the NPI item pool, these analyses generated insights that can be used to develop new measures of the personality constructs embedded within this frequently used inventory.

Development of a tool to assess adherence to a model of the division of responsibility in feeding young children: using response mapping to capacitate validation measures.

PubMed

Lohse, Barbara; Satter, Ellyn; Arnold, Kristen

2014-04-01

Accurate early assessment and targeted intervention with problematic parent/child feeding dynamics is critical for the prevention and treatment of child obesity. The division of responsibility in feeding (sDOR), articulated by the Satter Feeding Dynamics Model (fdSatter), has been demonstrated clinically as an effective approach to reduce child feeding problems, including those leading to obesity. Lack of a tested instrument to examine adherence to fdSatter stimulated initial construction of the Satter Feeding Dynamics Inventory (fdSI). The aim of this project was to refine the item pool to establish translational validity, making the fdSI suitable for advanced psychometric analysis. Cognitive interviews (n = 80) with caregivers of varied socioeconomic strata informed revisions that demonstrated face and content validity. fdSI responses were mapped to interviews using an iterative, multi-phase thematic approach to provide an instrument ready for construct validation. fdSI development required five interview phases over 32 months: Foundational; Refinement; Transitional; Assurance; and Launching. Each phase was associated with item reduction and revision. Thirteen items were removed from the 38-item Foundational phase and seven were revised in the Refinement phase. Revisions, deletions, and additions prompted by Transitional and Assurance phase interviews resulted in the 15-item Launching phase fdSI. Only one Foundational phase item was carried through all development phases, emphasizing the need to test for item comprehension and interpretation before psychometric analyses. Psychometric studies of item pools without encrypted meanings will facilitate progress toward a tool that accurately detects adherence to sDOR. Ability to measure sDOR will facilitate focus on feeding behaviors associated with reduced risk of childhood obesity.

Measuring grief and loss after spinal cord injury: Development, validation and psychometric characteristics of the SCI-QOL Grief and Loss item bank and short form

PubMed Central

Kalpakjian, Claire Z.; Tulsky, David S.; Kisala, Pamela A.; Bombardier, Charles H.

2015-01-01

Objective To develop an item response theory (IRT) calibrated Grief and Loss item bank as part of the Spinal Cord Injury – Quality of Life (SCI-QOL) measurement system. Design A literature review guided framework development of grief/loss. New items were created from focus groups. Items were revised based on expert review and patient feedback and were then field tested. Analyses included confirmatory factor analysis (CFA), graded response IRT modeling and evaluation of differential item functioning (DIF). Setting We tested a 20-item pool at several rehabilitation centers across the United States, including the University of Michigan, Kessler Foundation, Rehabilitation Institute of Chicago, the University of Washington, Craig Hospital and the James J. Peters/Bronx Department of Veterans Affairs hospital. Participants A total of 717 individuals with SCI answered the grief and loss questions. Results The final calibrated item bank resulted in 17 retained items. A unidimensional model was observed (CFI = 0.976; RMSEA = 0.078) and measurement precision was good (theta range between −1.48 to 2.48). Ten items were flagged for DIF, however, after examination of effect sizes found this to be negligible with little practical impact on score estimates. Conclusions This study indicates that the SCI-QOL Grief and Loss item bank represents a psychometrically robust measurement tool. Short form items are also suggested and computer adaptive tests are available. PMID:26010969

A Comparison of Graded Response and Rasch Partial Credit Models with Subjective Well-Being.

ERIC Educational Resources Information Center

Baker, John G.; Rounds, James B.; Zevon, Michael A.

2000-01-01

Compared two multiple category item response theory models using a data set of 52 mood terms with 713 undergraduate psychology students. Comparative model fit for the Samejima (F. Samejima, 1966) logistic model for graded responses and the Masters (G. Masters, 1982) partial credit model favored the former model for this data set. (SLD)

Evaluation properties of the French version of the OUT-PATSAT35 satisfaction with care questionnaire according to classical and item response theory analyses.

PubMed

Panouillères, M; Anota, A; Nguyen, T V; Brédart, A; Bosset, J F; Monnier, A; Mercier, M; Hardouin, J B

2014-09-01

The present study investigates the properties of the French version of the OUT-PATSAT35 questionnaire, which evaluates the outpatients' satisfaction with care in oncology using classical analysis (CTT) and item response theory (IRT). This cross-sectional multicenter study includes 692 patients who completed the questionnaire at the end of their ambulatory treatment. CTT analyses tested the main psychometric properties (convergent and divergent validity, and internal consistency). IRT analyses were conducted separately for each OUT-PATSAT35 domain (the doctors, the nurses or the radiation therapists and the services/organization) by models from the Rasch family. We examined the fit of the data to the model expectations and tested whether the model assumptions of unidimensionality, monotonicity and local independence were respected. A total of 605 (87.4%) respondents were analyzed with a mean age of 64 years (range 29-88). Internal consistency for all scales separately and for the three main domains was good (Cronbach's α 0.74-0.98). IRT analyses were performed with the partial credit model. No disordered thresholds of polytomous items were found. Each domain showed high reliability but fitted poorly to the Rasch models. Three items in particular, the item about "promptness" in the doctors' domain and the items about "accessibility" and "environment" in the services/organization domain, presented the highest default of fit. A correct fit of the Rasch model can be obtained by dropping these items. Most of the local dependence concerned items about "information provided" in each domain. A major deviation of unidimensionality was found in the nurses' domain. CTT showed good psychometric properties of the OUT-PATSAT35. However, the Rasch analysis revealed some misfitting and redundant items. Taking the above problems into consideration, it could be interesting to refine the questionnaire in a future study.

Testing whether the DSM-5 personality disorder trait model can be measured with a reduced set of items: An item response theory investigation of the Personality Inventory for DSM-5.

PubMed

Maples, Jessica L; Carter, Nathan T; Few, Lauren R; Crego, Cristina; Gore, Whitney L; Samuel, Douglas B; Williamson, Rachel L; Lynam, Donald R; Widiger, Thomas A; Markon, Kristian E; Krueger, Robert F; Miller, Joshua D

2015-12-01

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes an alternative model of personality disorders (PDs) in Section III, consisting in part of a pathological personality trait model. To date, the 220-item Personality Inventory for DSM-5 (PID-5; Krueger, Derringer, Markon, Watson, & Skodol, 2012) is the only extant self-report instrument explicitly developed to measure this pathological trait model. The present study used item response theory-based analyses in a large sample (n = 1,417) to investigate whether a reduced set of 100 items could be identified from the PID-5 that could measure the 25 traits and 5 domains. This reduced set of PID-5 items was then tested in a community sample of adults currently receiving psychological treatment (n = 109). Across a wide range of criterion variables including NEO PI-R domains and facets, DSM-5 Section II PD scores, and externalizing and internalizing outcomes, the correlational profiles of the original and reduced versions of the PID-5 were nearly identical (rICC = .995). These results provide strong support for the hypothesis that an abbreviated set of PID-5 items can be used to reliably, validly, and efficiently assess these personality disorder traits. The ability to assess the DSM-5 Section III traits using only 100 items has important implications in that it suggests these traits could still be measured in settings in which assessment-related resources (e.g., time, compensation) are limited. (c) 2015 APA, all rights reserved).

Response latencies are alive and well for identifying fakers on a self-report personality inventory: A reconsideration of van Hooft and Born (2012).

PubMed

Holden, Ronald R; Lambert, Christine E

2015-12-01

Van Hooft and Born (Journal of Applied Psychology 97:301-316, 2012) presented data challenging both the correctness of a congruence model of faking on personality test items and the relative merit (i.e., effect size) of response latencies for identifying fakers. We suggest that their analysis of response times was suboptimal, and that it followed neither from a congruence model of faking nor from published protocols on appropriately filtering the noise in personality test item answering times. Using new data and following recommended analytic procedures, we confirmed the relative utility of response times for identifying personality test fakers, and our obtained results, again, reinforce a congruence model of faking.

Differential Item Functioning Assessment in Cognitive Diagnostic Modeling: Application of the Wald Test to Investigate DIF in the DINA Model

ERIC Educational Resources Information Center

Hou, Likun; de la Torre, Jimmy; Nandakumar, Ratna

2014-01-01

Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study…

Using item response theory to investigate the structure of anticipated affect: do self-reports about future affective reactions conform to typical or maximal models?

PubMed

Zampetakis, Leonidas A; Lerakis, Manolis; Kafetsios, Konstantinos; Moustakis, Vassilis

2015-01-01

In the present research, we used item response theory (IRT) to examine whether effective predictions (anticipated affect) conforms to a typical (i.e., what people usually do) or a maximal behavior process (i.e., what people can do). The former, correspond to non-monotonic ideal point IRT models, whereas the latter correspond to monotonic dominance IRT models. A convenience, cross-sectional student sample (N = 1624) was used. Participants were asked to report on anticipated positive and negative affect around a hypothetical event (emotions surrounding the start of a new business). We carried out analysis comparing graded response model (GRM), a dominance IRT model, against generalized graded unfolding model, an unfolding IRT model. We found that the GRM provided a better fit to the data. Findings suggest that the self-report responses to anticipated affect conform to dominance response process (i.e., maximal behavior). The paper also discusses implications for a growing literature on anticipated affect.

Using item response theory to investigate the structure of anticipated affect: do self-reports about future affective reactions conform to typical or maximal models?

PubMed Central

Zampetakis, Leonidas A.; Lerakis, Manolis; Kafetsios, Konstantinos; Moustakis, Vassilis

2015-01-01

In the present research, we used item response theory (IRT) to examine whether effective predictions (anticipated affect) conforms to a typical (i.e., what people usually do) or a maximal behavior process (i.e., what people can do). The former, correspond to non-monotonic ideal point IRT models, whereas the latter correspond to monotonic dominance IRT models. A convenience, cross-sectional student sample (N = 1624) was used. Participants were asked to report on anticipated positive and negative affect around a hypothetical event (emotions surrounding the start of a new business). We carried out analysis comparing graded response model (GRM), a dominance IRT model, against generalized graded unfolding model, an unfolding IRT model. We found that the GRM provided a better fit to the data. Findings suggest that the self-report responses to anticipated affect conform to dominance response process (i.e., maximal behavior). The paper also discusses implications for a growing literature on anticipated affect. PMID:26441806

The Probability of Exceedance as a Nonparametric Person-Fit Statistic for Tests of Moderate Length

ERIC Educational Resources Information Center

Tendeiro, Jorge N.; Meijer, Rob R.

2013-01-01

To classify an item score pattern as not fitting a nonparametric item response theory (NIRT) model, the probability of exceedance (PE) of an observed response vector x can be determined as the sum of the probabilities of all response vectors that are, at most, as likely as x, conditional on the test's total score. Vector x is to be considered…

Translation, adaptation and validation of the American short form Patient Activation Measure (PAM13) in a Danish version.

PubMed

Maindal, Helle Terkildsen; Sokolowski, Ineta; Vedsted, Peter

2009-06-29

The Patient Activation Measure (PAM) is a measure that assesses patient knowledge, skill, and confidence for self-management. This study validates the Danish translation of the 13-item Patient Activation Measure (PAM13) in a Danish population with dysglycaemia. 358 people with screen-detected dysglycaemia participating in a primary care health education study responded to PAM13. The PAM13 was translated into Danish by a standardised forward-backward translation. Data quality was assessed by mean, median, item response, missing values, floor and ceiling effects, internal consistency (Cronbach's alpha and average inter-item correlation) and item-rest correlations. Scale properties were assessed by Rasch Rating Scale models. The item response was high with a small number of missing values (0.8-4.2%). Floor effect was small (range 0.6-3.6%), but the ceiling effect was above 15% for all items (range 18.6-62.7%). The alpha-coefficient was 0.89 and the average inter-item correlation 0.38. The Danish version formed a unidimensional, probabilistic Guttman-like scale explaining 43.2% of the variance. We did however, find a different item sequence compared to the original scale. A Danish version of PAM13 with acceptable validity and reliability is now available. Further development should focus on single items, response categories in relation to ceiling effects and further validation of reproducibility and responsiveness.

Cluster Analysis for Cognitive Diagnosis: Theory and Applications

ERIC Educational Resources Information Center

Chiu, Chia-Yi; Douglas, Jeffrey A.; Li, Xiaodong

2009-01-01

Latent class models for cognitive diagnosis often begin with specification of a matrix that indicates which attributes or skills are needed for each item. Then by imposing restrictions that take this into account, along with a theory governing how subjects interact with items, parametric formulations of item response functions are derived and…

Examining Differential Math Performance by Gender and Opportunity to Learn

ERIC Educational Resources Information Center

Albano, Anthony D.; Rodriguez, Michael C.

2013-01-01

Although a substantial amount of research has been conducted on differential item functioning in testing, studies have focused on detecting differential item functioning rather than on explaining how or why it may occur. Some recent work has explored sources of differential functioning using explanatory and multilevel item response models. This…

A Feedback Control Strategy for Enhancing Item Selection Efficiency in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Weissman, Alexander

2006-01-01

A computerized adaptive test (CAT) may be modeled as a closed-loop system, where item selection is influenced by trait level ([theta]) estimation and vice versa. When discrepancies exist between an examinee's estimated and true [theta] levels, nonoptimal item selection is a likely result. Nevertheless, examinee response behavior consistent with…

A Multidimensional Scaling Approach to Dimensionality Assessment for Measurement Instruments Modeled by Multidimensional Item Response Theory

ERIC Educational Resources Information Center

Toro, Maritsa

2011-01-01

The statistical assessment of dimensionality provides evidence of the underlying constructs measured by a survey or test instrument. This study focuses on educational measurement, specifically tests comprised of items described as multidimensional. That is, items that require examinee proficiency in multiple content areas and/or multiple cognitive…

Development and Validation of a Computer Adaptive EFL Test

ERIC Educational Resources Information Center

He, Lianzhen; Min, Shangchao

2017-01-01

The first aim of this study was to develop a computer adaptive EFL test (CALT) that assesses test takers' listening and reading proficiency in English with dichotomous items and polytomous testlets. We reported in detail on the development of the CALT, including item banking, determination of suitable item response theory (IRT) models for item…

Modeling Unproductive Behavior in Online Homework in Terms of Latent Student Traits: An Approach Based on Item Response Theory

NASA Astrophysics Data System (ADS)

Gönülateş, Emre; Kortemeyer, Gerd

2017-04-01

Homework is an important component of most physics courses. One of the functions it serves is to provide meaningful formative assessment in preparation for examinations. However, correlations between homework and examination scores tend to be low, likely due to unproductive student behavior such as copying and random guessing of answers. In this study, we attempt to model these two counterproductive learner behaviors within the framework of Item Response Theory in order to provide an ability measurement that strongly correlates with examination scores. We find that introducing additional item parameters leads to worse predictions of examination grades, while introducing additional learner traits is a more promising approach.

Item Response Theory with Estimation of the Latent Population Distribution Using Spline-Based Densities

ERIC Educational Resources Information Center

Woods, Carol M.; Thissen, David

2006-01-01

The purpose of this paper is to introduce a new method for fitting item response theory models with the latent population distribution estimated from the data using splines. A spline-based density estimation system provides a flexible alternative to existing procedures that use a normal distribution, or a different functional form, for the…

Score Equating and Item Response Theory: Some Practical Considerations.

ERIC Educational Resources Information Center

Cook, Linda L.; Eignor, Daniel R.

The purposes of this paper are five-fold to discuss: (1) when item response theory (IRT) equating methods should provide better results than traditional methods; (2) which IRT model, the three-parameter logistic or the one-parameter logistic (Rasch), is the most reasonable to use; (3) what unique contributions IRT methods can offer the equating…

A Comparative Study of Test Data Dimensionality Assessment Procedures Under Nonparametric IRT Models

ERIC Educational Resources Information Center

van Abswoude, Alexandra A. H.; van der Ark, L. Andries; Sijtsma, Klaas

2004-01-01

In this article, an overview of nonparametric item response theory methods for determining the dimensionality of item response data is provided. Four methods were considered: MSP, DETECT, HCA/CCPROX, and DIMTEST. First, the methods were compared theoretically. Second, a simulation study was done to compare the effectiveness of MSP, DETECT, and…

Differential item functional analysis on pedagogic and content knowledge (PCK) questionnaire for Indonesian teachers using RASCH model

NASA Astrophysics Data System (ADS)

Rahmani, B. D.

2018-01-01

The purpose of this paper is to evaluate Indonesian senior high school teacher’s pedagogical content knowledge also their perception toward curriculum changing in West Java Indonesia. The data used in this study were derived from a questionnaire survey conducted among teachers in Bandung, West Java. A total of 61 usable responses were collected. The Differential Item Functioning (DIFF) was used to analyze the data whether the item had a difference or not toward gender, education background also on school location. However, the result showed that there was no any significant difference on gender and school location toward the item response but educational background. As a conclusion, the teacher’s educational background influence on giving the response to the questionnaire. Therefore, it is suggested in the future to construct the items on the questionnaire which is coped the differences of the participant particularly the educational background.

Item response analysis of the Positive and Negative Syndrome Scale

PubMed Central

Santor, Darcy A; Ascher-Svanum, Haya; Lindenmayer, Jean-Pierre; Obenchain, Robert L

2007-01-01

Background Statistical models based on item response theory were used to examine (a) the performance of individual Positive and Negative Syndrome Scale (PANSS) items and their options, (b) the effectiveness of various subscales to discriminate among individual differences in symptom severity, and (c) the appropriateness of cutoff scores recently recommended by Andreasen and her colleagues (2005) to establish symptom remission. Methods Option characteristic curves were estimated using a nonparametric item response model to examine the probability of endorsing each of 7 options within each of 30 PANSS items as a function of standardized, overall symptom severity. Our data were baseline PANSS scores from 9205 patients with schizophrenia or schizoaffective disorder who were enrolled between 1995 and 2003 in either a large, naturalistic, observational study or else in 1 of 12 randomized, double-blind, clinical trials comparing olanzapine to other antipsychotic drugs. Results Our analyses show that the majority of items forming the Positive and Negative subscales of the PANSS perform very well. We also identified key areas for improvement or revision in items and options within the General Psychopathology subscale. The Positive and Negative subscale scores are not only more discriminating of individual differences in symptom severity than the General Psychopathology subscale score, but are also more efficient on average than the 30-item total score. Of the 8 items recently recommended to establish symptom remission, 1 performed markedly different from the 7 others and should either be deleted or rescored requiring that patients achieve a lower score of 2 (rather than 3) to signal remission. Conclusion This first item response analysis of the PANSS supports its sound psychometric properties; most PANSS items were either very good or good at assessing overall severity of illness. These analyses did identify some items which might be further improved for measuring individual severity differences or for defining remission thresholds. Findings also suggest that the Positive and Negative subscales are more sensitive to change than the PANSS total score and, thus, may constitute a "mini PANSS" that may be more reliable, require shorter administration and training time, and possibly reduce sample sizes needed for future research. PMID:18005449

Integrating competing dimensional models of personality: linking the SNAP, TCI, and NEO using Item Response Theory.

PubMed

Stepp, Stephanie D; Yu, Lan; Miller, Joshua D; Hallquist, Michael N; Trull, Timothy J; Pilkonis, Paul A

2012-04-01

Mounting evidence suggests that several inventories assessing both normal personality and personality disorders measure common dimensional personality traits (i.e., Antagonism, Constraint, Emotional Instability, Extraversion, and Unconventionality), albeit providing unique information along the underlying trait continuum. We used Widiger and Simonsen's (2005) pantheoretical integrative model of dimensional personality assessment as a guide to create item pools. We then used Item Response Theory (IRT) to compare the assessment of these five personality traits across three established dimensional measures of personality: the Schedule for Nonadaptive and Adaptive Personality (SNAP), the Temperament and Character Inventory (TCI), and the Revised NEO Personality Inventory (NEO PI-R). We found that items from each inventory map onto these five common personality traits in predictable ways. The IRT analyses, however, documented considerable variability in the item and test information derived from each inventory. Our findings support the notion that the integration of multiple perspectives will provide greater information about personality while minimizing the weaknesses of any single instrument.

Integrating Competing Dimensional Models of Personality: Linking the SNAP, TCI, and NEO Using Item Response Theory

PubMed Central

Stepp, Stephanie D.; Yu, Lan; Miller, Joshua D.; Hallquist, Michael N.; Trull, Timothy J.; Pilkonis, Paul A.

2013-01-01

Mounting evidence suggests that several inventories assessing both normal personality and personality disorders measure common dimensional personality traits (i.e., Antagonism, Constraint, Emotional Instability, Extraversion, and Unconventionality), albeit providing unique information along the underlying trait continuum. We used Widiger and Simonsen’s (2005) pantheoretical integrative model of dimensional personality assessment as a guide to create item pools. We then used Item Response Theory (IRT) to compare the assessment of these five personality traits across three established dimensional measures of personality: the Schedule for Nonadaptive and Adaptive Personality (SNAP), the Temperament and Character Inventory (TCI), and the Revised NEO Personality Inventory (NEO PI-R). We found that items from each inventory map onto these five common personality traits in predictable ways. The IRT analyses, however, documented considerable variability in the item and test information derived from each inventory. Our findings support the notion that the integration of multiple perspectives will provide greater information about personality while minimizing the weaknesses of any single instrument. PMID:22452759

Comparing Vertical Scales Derived from Dichotomous and Polytomous IRT Models for a Test Composed of Testlets.

ERIC Educational Resources Information Center

Bishop, N. Scott; Omar, Md Hafidz

Previous research has shown that testlet structures often violate important assumptions of dichotomous item response theory (D-IRT) models, applied to item-level scores, that can in turn affect the results of many measurement applications. In this situation, polytomous IRT (P-IRT) models, applied to testlet-level scores, have been used as an…

Strategic trade-offs between quantity and quality in working memory.

PubMed

Fougnie, Daryl; Cormiea, Sarah M; Kanabar, Anish; Alvarez, George A

2016-08-01

Is working memory capacity determined by an immutable limit-for example, 4 memory storage slots? The fact that performance is typically unaffected by task instructions has been taken as support for such structural models of memory. Here, we modified a standard working memory task to incentivize participants to remember more items. Participants were asked to remember a set of colors over a short retention interval. In 1 condition, participants reported a random item's color using a color wheel. In the modified task, participants responded to all items and their response was only considered correct if all responses were on the correct half of the color wheel. We looked for a trade-off between quantity and quality-participants storing more items, but less precisely, when required to report them all. This trade-off was observed when tasks were blocked and when task-type was cued after encoding, but not when task-type was cued during the response, suggesting that task differences changed how items were actively encoded and maintained. This strategic control over the contents of working memory challenges models that assume inflexible limits on memory storage. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Rasch measure of teachers' views of teacher-student relationships in the primary school.

PubMed

Leitao, Natalie; Waugh, Russell F

2012-01-01

This study investigated teacher-student relationships from the teachers' point of view at Perth metropolitan schools in Western Australia. The study identified three key social and emotional aspects that affect teacher-student relationships, namely, Connectedness, Availability and Communication. Data were collected by questionnaire (N = 139) with stem-items answered in three perspectives: (1) Idealistic: this is what I would like to happen; (2) Capability: this is what I am capable of; and (3) Behaviour: this is what actually happens, using four ordered response categories: not at all (score 1), some of the time (score 2), most of the time (score 3), and almost always (score 4). Data were analysed with a Rasch measurement model and a uni-dimensional, linear scale with 24 items, ordered from easy to hard, was created. The data were shown to be highly reliable, so that valid inferences could be made from the scale. The Person Separation Index (akin to a reliability index) was 0.93; there was good global teacher and item fit to the measurement model; there was good item fit; the targeting of the item difficulties against the teacher measures was good, and the response categories were answered consistently and logically. Teachers said that the ideal items were all easier than their corresponding capability items which were in turn easier than the behaviour items (where the items fitted the model), as conceptualized. The easiest ideal items were: I like this child and This child and I get along well together. The hardest ideal item (but still easy) was: I am available for this child. The easiest behaviour item (but still hard) was: This child and I get along well together. The hardest behaviour item (and very hard) was: I am interested to learn about this child's personal thoughts, feelings and experiences. The difficulties of the items supported the conceptual structure of the variable.

Modeling the World Health Organization Disability Assessment Schedule II using non-parametric item response models.

PubMed

Galindo-Garre, Francisca; Hidalgo, María Dolores; Guilera, Georgina; Pino, Oscar; Rojo, J Emilio; Gómez-Benito, Juana

2015-03-01

The World Health Organization Disability Assessment Schedule II (WHO-DAS II) is a multidimensional instrument developed for measuring disability. It comprises six domains (getting around, self-care, getting along with others, life activities and participation in society). The main purpose of this paper is the evaluation of the psychometric properties for each domain of the WHO-DAS II with parametric and non-parametric Item Response Theory (IRT) models. A secondary objective is to assess whether the WHO-DAS II items within each domain form a hierarchy of invariantly ordered severity indicators of disability. A sample of 352 patients with a schizophrenia spectrum disorder is used in this study. The 36 items WHO-DAS II was administered during the consultation. Partial Credit and Mokken scale models are used to study the psychometric properties of the questionnaire. The psychometric properties of the WHO-DAS II scale are satisfactory for all the domains. However, we identify a few items that do not discriminate satisfactorily between different levels of disability and cannot be invariantly ordered in the scale. In conclusion the WHO-DAS II can be used to assess overall disability in patients with schizophrenia, but some domains are too general to assess functionality in these patients because they contain items that are not applicable to this pathology. Copyright © 2014 John Wiley & Sons, Ltd.

Item response modeling: a psychometric assessment of the children's fruit, vegetable, water, and physical activity self-efficacy scales among Chinese children.

PubMed

Wang, Jing-Jing; Chen, Tzu-An; Baranowski, Tom; Lau, Patrick W C

2017-09-16

This study aimed to evaluate the psychometric properties of four self-efficacy scales (i.e., self-efficacy for fruit (FSE), vegetable (VSE), and water (WSE) intakes, and physical activity (PASE)) and to investigate their differences in item functioning across sex, age, and body weight status groups using item response modeling (IRM) and differential item functioning (DIF). Four self-efficacy scales were administrated to 763 Hong Kong Chinese children (55.2% boys) aged 8-13 years. Classical test theory (CTT) was used to examine the reliability and factorial validity of scales. IRM was conducted and DIF analyses were performed to assess the characteristics of item parameter estimates on the basis of children's sex, age and body weight status. All self-efficacy scales demonstrated adequate to excellent internal consistency reliability (Cronbach's α: 0.79-0.91). One FSE misfit item and one PASE misfit item were detected. Small DIF were found for all the scale items across children's age groups. Items with medium to large DIF were detected in different sex and body weight status groups, which will require modification. A Wright map revealed that items covered the range of the distribution of participants' self-efficacy for each scale except VSE. Several self-efficacy scales' items functioned differently by children's sex and body weight status. Additional research is required to modify the four self-efficacy scales to minimize these moderating influences for application.

Guessing and the Rasch Model

ERIC Educational Resources Information Center

Holster, Trevor A.; Lake, J.

2016-01-01

Stewart questioned Beglar's use of Rasch analysis of the Vocabulary Size Test (VST) and advocated the use of 3-parameter logistic item response theory (3PLIRT) on the basis that it models a non-zero lower asymptote for items, often called a "guessing" parameter. In support of this theory, Stewart presented fit statistics derived from…

Observed-Score Equating as a Test Assembly Problem.

ERIC Educational Resources Information Center

van der Linden, Wim J.; Luecht, Richard M.

1998-01-01

Derives a set of linear conditions of item-response functions that guarantees identical observed-score distributions on two test forms. The conditions can be added as constraints to a linear programming model for test assembly. An example illustrates the use of the model for an item pool from the Law School Admissions Test (LSAT). (SLD)

Aging and Confidence Judgments in Item Recognition

ERIC Educational Resources Information Center

Voskuilen, Chelsea; Ratcliff, Roger; McKoon, Gail

2018-01-01

We examined the effects of aging on performance in an item-recognition experiment with confidence judgments. A model for confidence judgments and response time (RTs; Ratcliff & Starns, 2013) was used to fit a large amount of data from a new sample of older adults and a previously reported sample of younger adults. This model of confidence…

Using a MaxEnt Classifier for the Automatic Content Scoring of Free-Text Responses

NASA Astrophysics Data System (ADS)

Sukkarieh, Jana Z.

2011-03-01

Criticisms against multiple-choice item assessments in the USA have prompted researchers and organizations to move towards constructed-response (free-text) items. Constructed-response (CR) items pose many challenges to the education community—one of which is that they are expensive to score by humans. At the same time, there has been widespread movement towards computer-based assessment and hence, assessment organizations are competing to develop automatic content scoring engines for such items types—which we view as a textual entailment task. This paper describes how MaxEnt Modeling is used to help solve the task. MaxEnt has been used in many natural language tasks but this is the first application of the MaxEnt approach to textual entailment and automatic content scoring.

Maximum Marginal Likelihood Estimation of a Monotonic Polynomial Generalized Partial Credit Model with Applications to Multiple Group Analysis.

PubMed

Falk, Carl F; Cai, Li

2016-06-01

We present a semi-parametric approach to estimating item response functions (IRF) useful when the true IRF does not strictly follow commonly used functions. Our approach replaces the linear predictor of the generalized partial credit model with a monotonic polynomial. The model includes the regular generalized partial credit model at the lowest order polynomial. Our approach extends Liang's (A semi-parametric approach to estimate IRFs, Unpublished doctoral dissertation, 2007) method for dichotomous item responses to the case of polytomous data. Furthermore, item parameter estimation is implemented with maximum marginal likelihood using the Bock-Aitkin EM algorithm, thereby facilitating multiple group analyses useful in operational settings. Our approach is demonstrated on both educational and psychological data. We present simulation results comparing our approach to more standard IRF estimation approaches and other non-parametric and semi-parametric alternatives.

Item Banks for Substance Use from the Patient-Reported Outcomes Measurement Information System (PROMIS®): Severity of Use and Positive Appeal of Use*

PubMed Central

Pilkonis, Paul A.; Yu, Lan; Dodds, Nathan E.; Johnston, Kelly L.; Lawrence, Suzanne; Hilton, Thomas F.; Daley, Dennis C.; Patkar, Ashwin A.; McCarty, Dennis

2015-01-01

Background Two item banks for substance use were developed as part of the Patient-Reported Outcomes Measurement Information System (PROMIS®): severity of substance use and positive appeal of substance use. Methods Qualitative item analysis (including focus groups, cognitive interviewing, expert review, and item revision) reduced an initial pool of more than 5,300 items for substance use to 119 items included in field testing. Items were written in a first-person, past-tense format, with 5 response options reflecting frequency or severity. Both 30-day and 3-month time frames were tested. The calibration sample of 1,336 respondents included 875 individuals from the general population (ascertained through an internet panel) and 461patients from addiction treatment centers participating in the National Drug Abuse Treatment Clinical Trials Network. Results Final banks of 37 and 18 items were calibrated for severity of substance use and positive appeal of substance use, respectively, using the two-parameter graded response model from item response theory (IRT). Initial calibrations were similar for the 30-day and 3-month time frames, and final calibrations used data combined across the time frames, making the items applicable with either interval. Seven-item static short forms were also developed from each item bank. Conclusions Test information curves showed that the PROMIS item banks provided substantial information in a broad range of severity, making them suitable for treatment, observational, and epidemiological research in both clinical and community settings. PMID:26423364

An item response theory evaluation of the young mania rating scale and the montgomery-asberg depression rating scale in the systematic treatment enhancement program for bipolar disorder (STEP-BD).

PubMed

Prisciandaro, James J; Tolliver, Bryan K

2016-11-15

The Young Mania Rating Scale (YMRS) and Montgomery-Asberg Depression Rating Scale (MADRS) are among the most widely used outcome measures for clinical trials of medications for Bipolar Disorder (BD). Nonetheless, very few studies have examined the measurement characteristics of the YMRS and MADRS in individuals with BD using modern psychometric methods. The present study evaluated the YMRS and MADRS in the Systematic Treatment Enhancement Program for BD (STEP-BD) study using Item Response Theory (IRT). Baseline data from 3716 STEP-BD participants were available for the present analysis. The Graded Response Model (GRM) was fit separately to YMRS and MADRS item responses. Differential item functioning (DIF) was examined by regressing a variety of clinically relevant covariates (e.g., sex, substance dependence) on all test items and on the latent symptom severity dimension, within each scale. Both scales: 1) contained several items that provided little or no psychometric information, 2) were inefficient, in that the majority of item response categories did not provide incremental psychometric information, 3) poorly measured participants outside of a narrow band of severity, 4) evidenced DIF for nearly all items, suggesting that item responses were, in part, determined by factors other than symptom severity. Limited to outpatients; DIF analysis only sensitive to certain forms of DIF. The present study provides evidence for significant measurement problems involving the YMRS and MADRS. More work is needed to refine these measures and/or develop suitable alternative measures of BD symptomatology for clinical trials research. Copyright © 2016 Elsevier B.V. All rights reserved.

Incorporating Response Times in Item Response Theory Models of Reading Comprehension Fluency

ERIC Educational Resources Information Center

Su, Shiyang

2017-01-01

With the online assessment becoming mainstream and the recording of response times becoming straightforward, the importance of response times as a measure of psychological constructs has been recognized and the literature of modeling times has been growing during the last few decades. Previous studies have tried to formulate models and theories to…

Person-Fit Statistics for Joint Models for Accuracy and Speed

ERIC Educational Resources Information Center

Fox, Jean-Paul; Marianti, Sukaesi

2017-01-01

Response accuracy and response time data can be analyzed with a joint model to measure ability and speed of working, while accounting for relationships between item and person characteristics. In this study, person-fit statistics are proposed for joint models to detect aberrant response accuracy and/or response time patterns. The person-fit tests…

The Effects of Aging and IQ on Item and Associative Memory

PubMed Central

Ratcliff, Roger; Thapar, Anjali; McKoon, Gail

2011-01-01

The effects of aging and IQ on performance were examined in four memory tasks: item recognition, associative recognition, cued recall, and free recall. For item and associative recognition, accuracy and the response time distributions for correct and error responses were explained by Ratcliff’s (1978) diffusion model, at the level of individual participants. The values of the components of processing identified by the model for the recognition tasks, as well as accuracy for cued and free recall, were compared across levels of IQ ranging from 85 to 140 and age (college-age, 60-74 year olds, and 75-90 year olds). IQ had large effects on the quality of the evidence from memory on which decisions were based in the recognition tasks and accuracy in the recall tasks, except for the oldest participants for whom some of the measures were near floor values. Drift rates in the recognition tasks, accuracy in the recall tasks, and IQ all correlated strongly with each other. However, there was a small decline in drift rates for item recognition and a large decline for associative recognition and accuracy in cued recall (about 70 percent). In contrast, there were large age effects on boundary separation and nondecision time (which correlated across tasks), but little effect of IQ. The implications of these results for single- and dual- process models of item recognition are discussed and it is concluded that models that deal with both RTs and accuracy are subject to many more constraints than models that deal with only one of these measures. Overall, the results of the study show a complicated but interpretable pattern of interactions that present important targets for response time and memory models. PMID:21707207

Development and psychometric characteristics of the SCI-QOL Pressure Ulcers scale and short form

PubMed Central

Kisala, Pamela A.; Tulsky, David S.; Choi, Seung W.; Kirshblum, Steven C.

2015-01-01

Objective To develop a self-reported measure of the subjective impact of pressure ulcers on health-related quality of life (HRQOL) in individuals with spinal cord injury (SCI) as part of the SCI quality of life (SCI-QOL) measurement system. Design Grounded-theory based qualitative item development methods, large-scale item calibration testing, confirmatory factor analysis (CFA), and item response theory-based psychometric analysis. Setting Five SCI Model System centers and one Department of Veterans Affairs medical center in the United States. Participants Adults with traumatic SCI. Main Outcome Measures SCI-QOL Pressure Ulcers scale. Results 189 individuals with traumatic SCI who experienced a pressure ulcer within the past 7 days completed 30 items related to pressure ulcers. CFA confirmed a unidimensional pool of items. IRT analyses were conducted. A constrained Graded Response Model with a constant slope parameter was used to estimate item thresholds for the 12 retained items. Conclusions The 12-item SCI-QOL Pressure Ulcers scale is unique in that it is specifically targeted to individuals with spinal cord injury and at every stage of development has included input from individuals with SCI. Furthermore, use of CFA and IRT methods provide flexibility and precision of measurement. The scale may be administered in its entirety or as a 7-item “short form” and is available for both research and clinical practice. PMID:26010965

An Empirical Comparison of DDF Detection Methods for Understanding the Causes of DIF in Multiple-Choice Items

ERIC Educational Resources Information Center

Suh, Youngsuk; Talley, Anna E.

2015-01-01

This study compared and illustrated four differential distractor functioning (DDF) detection methods for analyzing multiple-choice items. The log-linear approach, two item response theory-model-based approaches with likelihood ratio tests, and the odds ratio approach were compared to examine the congruence among the four DDF detection methods.…

On Maximizing Item Information and Matching Difficulty with Ability.

ERIC Educational Resources Information Center

Bickel, Peter; Buyske, Steven; Chang, Huahua; Ying, Zhiliang

2001-01-01

Examined the assumption that matching difficulty levels of test items with an examinee's ability makes a test more efficient and challenged this assumption through a class of one-parameter item response theory models. Found the validity of the fundamental assumption to be closely related to the van Zwet tail ordering of symmetric distributions (W.…

Stability of Rasch Scales over Time

ERIC Educational Resources Information Center

Taylor, Catherine S.; Lee, Yoonsun

2010-01-01

Item response theory (IRT) methods are generally used to create score scales for large-scale tests. Research has shown that IRT scales are stable across groups and over time. Most studies have focused on items that are dichotomously scored. Now Rasch and other IRT models are used to create scales for tests that include polytomously scored items.…

An Analysis of the Individual Effects of Sex Bias.

ERIC Educational Resources Information Center

Smith, Richard M.

Most attempts to correct for the presence of biased test items in a measurement instrument have been either to remove the items or to adjust the scores to correct for the bias. Using the Rasch Dichotomous Response Model and the independent ability estimates derived from three sets of items, those which favor females, those which favor males, and…

Item Analysis and Differential Item Functioning of a Brief Conduct Problem Screen

ERIC Educational Resources Information Center

Wu, Johnny; King, Kevin M.; Witkiewitz, Katie; Racz, Sarah Jensen; McMahon, Robert J.

2012-01-01

Research has shown that boys display higher levels of childhood conduct problems than girls, and Black children display higher levels than White children, but few studies have tested for scalar equivalence of conduct problems across gender and race. The authors conducted a 2-parameter item response theory (IRT) model to examine item…

The Construction of a Long Variable of Conceptual Development in Social Education.

ERIC Educational Resources Information Center

Doig, Brian

This paper demonstrates a method for constructing long variables using items that elicit partically correct responses across ages. Long variables may be defined by students at different ages (year levels) attempting common items within a test containing other items considered to be appropriate for each age or year level. A developmental model of…

Using Rasch Analysis to Evaluate the Reliability and Validity of the Swallowing Quality of Life Questionnaire: An Item Response Theory Approach.

PubMed

Cordier, Reinie; Speyer, Renée; Schindler, Antonio; Michou, Emilia; Heijnen, Bas Joris; Baijens, Laura; Karaduman, Ayşe; Swan, Katina; Clavé, Pere; Joosten, Annette Veronica

2018-02-01

The Swallowing Quality of Life questionnaire (SWAL-QOL) is widely used clinically and in research to evaluate quality of life related to swallowing difficulties. It has been described as a valid and reliable tool, but was developed and tested using classic test theory. This study describes the reliability and validity of the SWAL-QOL using item response theory (IRT; Rasch analysis). SWAL-QOL data were gathered from 507 participants at risk of oropharyngeal dysphagia (OD) across four European countries. OD was confirmed in 75.7% of participants via videofluoroscopy and/or fiberoptic endoscopic evaluation, or a clinical diagnosis based on meeting selected criteria. Patients with esophageal dysphagia were excluded. Data were analysed using Rasch analysis. Item and person reliability was good for all the items combined. However, person reliability was poor for 8 subscales and item reliability was poor for one subscale. Eight subscales exhibited poor person separation and two exhibited poor item separation. Overall item and person fit statistics were acceptable. However, at an individual item fit level results indicated unpredictable item responses for 28 items, and item redundancy for 10 items. The item-person dimensionality map confirmed these findings. Results from the overall Rasch model fit and Principal Component Analysis were suggestive of a second dimension. For all the items combined, none of the item categories were 'category', 'threshold' or 'step' disordered; however, all subscales demonstrated category disordered functioning. Findings suggest an urgent need to further investigate the underlying structure of the SWAL-QOL and its psychometric characteristics using IRT.

Psychometric properties of the SDM-Q-9 questionnaire for shared decision-making in multiple sclerosis: item response theory modelling and confirmatory factor analysis.

PubMed

Ballesteros, Javier; Moral, Ester; Brieva, Luis; Ruiz-Beato, Elena; Prefasi, Daniel; Maurino, Jorge

2017-04-22

Shared decision-making is a cornerstone of patient-centred care. The 9-item Shared Decision-Making Questionnaire (SDM-Q-9) is a brief self-assessment tool for measuring patients' perceived level of involvement in decision-making related to their own treatment and care. Information related to the psychometric properties of the SDM-Q-9 for multiple sclerosis (MS) patients is limited. The objective of this study was to assess the performance of the items composing the SDM-Q-9 and its dimensional structure in patients with relapsing-remitting MS. A non-interventional, cross-sectional study in adult patients with relapsing-remitting MS was conducted in 17 MS units throughout Spain. A nonparametric item response theory (IRT) analysis was used to assess the latent construct and dimensional structure underlying the observed responses. A parametric IRT model, General Partial Credit Model, was fitted to obtain estimates of the relationship between the latent construct and item characteristics. The unidimensionality of the SDM-Q-9 instrument was assessed by confirmatory factor analysis. A total of 221 patients were studied (mean age = 42.1 ± 9.9 years, 68.3% female). Median Expanded Disability Status Scale score was 2.5 ± 1.5. Most patients reported taking part in each step of the decision-making process. Internal reliability of the instrument was high (Cronbach's α = 0.91) and the overall scale scalability score was 0.57, indicative of a strong scale. All items, except for the item 1, showed scalability indices higher than 0.30. Four items (items 6 through to 9) conveyed more than half of the SDM-Q-9 overall information (67.3%). The SDM-Q-9 was a good fit for a unidimensional latent structure (comparative fit index = 0.98, root-mean-square error of approximation = 0.07). All freely estimated parameters were statistically significant (P < 0.001). All items presented standardized parameter estimates with salient loadings (>0.40) with the exception of item 1 which presented the lowest loading (0.26). Items 6 through to 8 were the most relevant items for shared decision-making. The SDM-Q-9 presents appropriate psychometric properties and is therefore useful for assessing different aspects of shared decision-making in patients with multiple sclerosis.

An Investigation of the Accuracy of Alternative Methods of True Score Estimation in High-Stakes Mixed-Format Examinations.

ERIC Educational Resources Information Center

Klinger, Don A.; Rogers, W. Todd

2003-01-01

The estimation accuracy of procedures based on classical test score theory and item response theory (generalized partial credit model) were compared for examinations consisting of multiple-choice and extended-response items. Analysis of British Columbia Scholarship Examination results found an error rate of about 10 percent for both methods, with…

The Shortened Raven Standard Progressive Matrices: Item Response Theory-Based Psychometric Analyses and Normative Data

ERIC Educational Resources Information Center

Van der Elst, Wim; Ouwehand, Carolijn; van Rijn, Peter; Lee, Nikki; Van Boxtel, Martin; Jolles, Jelle

2013-01-01

The purpose of the present study was to evaluate the psychometric properties of a shortened version of the Raven Standard Progressive Matrices (SPM) under an item response theory framework (the one- and two-parameter logistic models). The shortened Raven SPM was administered to N = 453 cognitively healthy adults aged between 24 and 83 years. The…

Using the Bayes Factors to Evaluate Person Fit in the Item Response Theory

ERIC Educational Resources Information Center

Pan, Tianshu; Yin, Yue

2017-01-01

In this article, we propose using the Bayes factors (BF) to evaluate person fit in item response theory models under the framework of Bayesian evaluation of an informative diagnostic hypothesis. We first discuss the theoretical foundation for this application and how to analyze person fit using BF. To demonstrate the feasibility of this approach,…

Pattern analysis of total item score and item response of the Kessler Screening Scale for Psychological Distress (K6) in a nationally representative sample of US adults

PubMed Central

Kawasaki, Yohei; Ide, Kazuki; Akutagawa, Maiko; Yamada, Hiroshi; Yutaka, Ono; Furukawa, Toshiaki A.

2017-01-01

Background Several recent studies have shown that total scores on depressive symptom measures in a general population approximate an exponential pattern except for the lower end of the distribution. Furthermore, we confirmed that the exponential pattern is present for the individual item responses on the Center for Epidemiologic Studies Depression Scale (CES-D). To confirm the reproducibility of such findings, we investigated the total score distribution and item responses of the Kessler Screening Scale for Psychological Distress (K6) in a nationally representative study. Methods Data were drawn from the National Survey of Midlife Development in the United States (MIDUS), which comprises four subsamples: (1) a national random digit dialing (RDD) sample, (2) oversamples from five metropolitan areas, (3) siblings of individuals from the RDD sample, and (4) a national RDD sample of twin pairs. K6 items are scored using a 5-point scale: “none of the time,” “a little of the time,” “some of the time,” “most of the time,” and “all of the time.” The pattern of total score distribution and item responses were analyzed using graphical analysis and exponential regression model. Results The total score distributions of the four subsamples exhibited an exponential pattern with similar rate parameters. The item responses of the K6 approximated a linear pattern from “a little of the time” to “all of the time” on log-normal scales, while “none of the time” response was not related to this exponential pattern. Discussion The total score distribution and item responses of the K6 showed exponential patterns, consistent with other depressive symptom scales. PMID:28289560