Item Response Theory: The Three-Parameter Logistic Model

Author(s):  
Ronald K. Hambleton
2015 ◽  
Vol 58 (3) ◽  
pp. 865-877 ◽  
Author(s):  
Gerasimos Fergadiotis ◽  
Stacey Kellough ◽  
William D. Hula

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


1991 ◽  
Vol 8 (4) ◽  
pp. 317-332 ◽  
Author(s):  
Emily Cole ◽  
Terry M. Wood ◽  
John M. Dunn

Tests constructed using item response theory (IRT) produce invariant item and test parameters, making it possible to construct tests and test items useful over many populations. This paper heuristically and empirically compares the utility of classical test theory (CTT) and IRT using psychomotor skill data. Data from the Test of Gross Motor Development (TGMD) (Ulrich, 1985) were used to assess the feasibility of fitting existing IRT models to dichotomously scored psychomotor skill data. As expected, CTT and IRT analyses yielded parallel interpretations of item and subtest difficulty and discrimination. However, IRT provided significant additional analysis of the error associated with estimating examinee ability. The IRT two-parameter logistic model provided a superior model fit to the one-parameter logistic model. Although both TGMD subtests estimated ability for examinees of low to average ability, the object control subtest estimated examinee ability more precisely at higher difficulty levels than the locomotor subtest. The results suggest that IRT is particularly well suited to construct tests that can meet the challenging measurement demands of adapted physical education.


Assessment ◽  
2016 ◽  
Vol 25 (2) ◽  
pp. 235-246
Author(s):  
Rapson Gomez ◽  
Alasdair Vance

There is evidence that the major anxiety and depressive disorders could reflect a single underlying internalization factor. For a group of 1,031 clinic-referred children, the study examined support for this factor, and used the two-parameter logistic model to examine the item response theory properties of the disorders in this factor. For the set of anxiety and depressive disorders, confirmatory factor analysis supported a one-factor model. The two-parameter logistic model analysis indicated that all the internalizing disorders in this factor were strong discriminators of the internalizing dimension. Also, they measured more of the internalizing dimension and with more precision in the upper half of the trait continuum. There was also support for the convergent validity of the internalizing dimension, in that it had large-to-medium effect size correlations with internalizing scores of other measures. The implications of the findings for clinical practice and clinical classification are discussed.


2020 ◽  
Vol 6 (2) ◽  
pp. 178
Author(s):  
Ilham Falani ◽  
Makruf Akbar ◽  
Dali Santun Naga

This study aims to determine the item response theory model which is more accurate in estimating students' mathematical abilities. The models compared in this study are Multiple Choice Model and Three-Parameter Logistic Model. Data used in this study are the responses of a mathematical test of 1704 eighth-grade junior high school students from six schools in the Depok City, West Java. The Sampling is done by using a purposive random sampling technique. The mathematics test used for research data collection consisted of 30 multiple choice format items. After the data is obtained, Research hypotheses were tested using the variance test method (F-test) to find out which model is more accurate in estimating ability parameters. The results showed that Fvalue is obtained 1.089, and  Ftable is 1.087, the value of Fvalue > Ftable, so it concluded that Ho rejected. That means Multiple Choice Model is more accurate than Three-Parameter Logistic Model in estimating the parameters of students' mathematical abilities. This makes the Multiple-Choice Model a recommended model for estimating mathematical ability in MC item format tests, especially in the field of mathematics and other fields that have similar characteristics.


2020 ◽  
Vol 78 (4) ◽  
pp. 576-594
Author(s):  
Bing Jia ◽  
Dan He ◽  
Zhemin Zhu

The quality of multiple-choice questions (MCQs) as well as the student's solve behavior in MCQs are educational concerns. MCQs cover wide educational content and can be immediately and accurately scored. However, many studies have found some flawed items in this exam type, thereby possibly resulting in misleading insights into students’ performance and affecting important decisions. This research sought to determine the characteristics of MCQs and factors that may affect the quality of MCQs by using item response theory (IRT) to evaluate data. For this, four samples of different sizes from US and China in secondary and higher education were chosen. Item difficulty and discrimination were determined using item response theory statistical item analysis models. Results were as follows. First, only a few guessing behaviors are included in MCQ exams because all data fit the two-parameter logistic model better than the three-parameter logistic model. Second, the quality of MCQs depended more on the degree of training of examiners and less on middle or higher education levels. Lastly, MCQs must be evaluated to ensure that high-quality items can be used as bases of inference in middle and higher education. Keywords: higher education, item evaluation, item response theory, multiple-choice test, secondary education


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