1 |
C. DeMars, "Group differences based on IRT scores: Does the model matter?," Educ. Psychol. Meas., vol. 61, no. 1, pp. 60-70, 2001.
DOI
|
2 |
J. Chen and J. Choi, "A comparison of maximum likelihood and expected a posteriori estimation for polychoric correlation using Monte Carlo simulation," J. Mod. Appl. Stat. Methods, vol. 8, no. 1, p. 32, 2009.
|
3 |
D. Almaleki, "Examinee Characteristics and their Impact on the Psychometric Properties of a Multiple Choice Test According to the Item Response Theory (IRT)," Eng. Technol. Appl. Sci. Res., vol. 11, no. 2, pp. 6889-6901, 2021.
DOI
|
4 |
D. Almaleki, "Empirical Evaluation of Different Features of Design in Confirmatory Factor Analysis," 2016.
|
5 |
M. Wu and R. Adams, Applying the Rasch model to psychosocial measurement: A practical approach. Educational Measurement Solutions Melbourne, 2007.
|
6 |
D. R. Divgi, "A minimum chi-square method for developing a common metric in item response theory," Appl. Psychol. Meas., vol. 9, no. 4, pp. 413-415, 1985.
DOI
|
7 |
F. M. Lord, "Maximum likelihood and Bayesian parameter estimation in item response theory," J. Educ. Meas., pp. 157-162, 1986.
|
8 |
B. Zhuang, S. Wang, S. Zhao, and M. Lu, "Computed tomography angiography-derived fractional flow reserve (CT-FFR) for the detection of myocardial ischemia with invasive fractional flow reserve as reference: systematic review and meta-analysis," Eur. Radiol., vol. 30, no. 2, pp. 712-725, 2020.
DOI
|
9 |
C. E. Cantrell, "Item Response Theory: Understanding the One-Parameter Rasch Model.," 1997.
|
10 |
R. K. Hambleton and H. J. Rogers, "Detecting potentially biased test items: Comparison of IRT area and Mantel-Haenszel methods," Appl. Meas. Educ., vol. 2, no. 4, pp. 313-334, 1989.
DOI
|
11 |
C. Magno, "Demonstrating the difference between classical test theory and item response theory using derived test data," Int. J. Educ. Psychol. Assess., vol. 1, no. 1, pp. 1-11, 2009.
|
12 |
T. Strachan et al., "Using a Projection IRT Method for Vertical Scaling When Construct Shift Is Present," J. Educ. Meas., 2020.
|
13 |
W.-C. Lee, S. Y. Kim, J. Choi, and Y. Kang, "IRT Approaches to Modeling Scores on Mixed-Format Tests," J. Educ. Meas., vol. 57, no. 2, pp. 230-254, 2020.
DOI
|
14 |
D. R. Crisan, J. N. Tendeiro, and R. R. Meijer, "Investigating the practical consequences of model misfit in unidimensional IRT models," Appl. Psychol. Meas., vol. 41, no. 6, pp. 439-455, 2017.
DOI
|
15 |
R. G. Lim and F. Drasgow, "Evaluation of two methods for estimating item response theory parameters when assessing differential item functioning.," J. Appl. Psychol., vol. 75, no. 2, p. 164, 1990.
DOI
|
16 |
C. J. Maas and J. J. Hox, "Sufficient sample sizes for multilevel modeling," Methodology, vol. 1, no. 3, pp. 86-92, 2005.
DOI
|
17 |
K. M. Marcoulides, N. Foldnes, and S. Gronneberg, "Assessing model fit in structural equation modeling using appropriate test statistics," Struct. Equ. Model. Multidiscip. J., vol. 27, no. 3, pp. 369-379, 2020.
DOI
|
18 |
L. R. Bonetto, J. S. Crespo, R. Guegan, V. I. Esteves, and M. Giovanela, "Removal of methylene blue from aqueous solutions using a solid residue of the apple juice industry: full factorial design, equilibrium, thermodynamics and kinetics aspects," J. Mol. Struct., vol. 1224, p. 129296, 2021.
DOI
|
19 |
M. N. Morshed, M. N. Pervez, N. Behary, N. Bouazizi, J. Guan, and V. A. Nierstrasz, "Statistical modeling and optimization of heterogeneous Fenton-like removal of organic pollutant using fibrous catalysts: a full factorial design," Sci. Rep., vol. 10, no. 1, pp. 1-14, 2020.
DOI
|
20 |
H. Swaminathan, R. K. Hambleton, and J. Algina, "Reliability of criterion-referenced tests: A decision-theoretic formulation," J. Educ. Meas., vol. 11, no. 4, pp. 263-267, 1974.
DOI
|
21 |
H. Swaminathan, R. K. Hambleton, and H. J. Rogers, "21 Assessing the Fit of Item Response Theory Models," Handb. Stat., vol. 26, pp. 683-718, 2006.
DOI
|
22 |
G. J. Mellenbergh, "Item bias and item response theory," Int. J. Educ. Res., vol. 13, no. 2, pp. 127-143, 1989.
DOI
|
23 |
G. H. Fischer and I. W. Molenaar, Rasch models: Foundations, recent developments, and applications. Springer Science & Business Media, 2012.
|
24 |
D. A. Almaleki, W. W. Khayat, T. F. Yally, and A. A. Alhajjaji, "The Effectiveness of the Use of DistanceEvaluation Tools and Methods among Students with Learning-Difficulties from the Teachers' Point of View," Int. J. Comput. Sci. Netw. Secur., vol. 21, no. 5, pp. 243-255, May 2021, doi: 10.22937/IJCSNS.2021.21.5.34.
DOI
|
25 |
R. K. Hambleton, W. J. van der Linden, and C. S. Wells, "IRT models for the analysis of polytomously scored data," Handb. Polytomous Item Response Theory Models, pp. 21-42, 2010.
|
26 |
S.-S. Lee and J. Kim, "An Exploratory study on Student-Intelligent Robot Teacher relationship recognized by Middle School Students," J. Digit. Converg., vol. 18, no. 4, pp. 37-44, 2020.
DOI
|
27 |
S. Tibi, A. A. Edwards, C. Schatschneider, L. J. Lombardino, J. R. Kirby, and S. H. Salha, "IRT analyses of Arabic letter knowledge in Kindergarten," Read. Writ., pp. 1-26, 2020.
|
28 |
F. M. Lord, Applications of item response theory to practical testing problems. Routledge, 2012.
|
29 |
M. L. Stocking and F. M. Lord, "Developing a common metric in item response theory," Appl. Psychol. Meas., vol. 7, no. 2, pp. 201-210, 1983.
DOI
|
30 |
H. Kishino, T. Miyata, and M. Hasegawa, "Maximum likelihood inference of protein phylogeny and the origin of chloroplasts," J. Mol. Evol., vol. 31, no. 2, pp. 151-160, 1990.
DOI
|
31 |
G. J. Mellenbergh, "Item bias and item response theory," Int. J. Educ. Res., vol. 13, no. 2, pp. 127-143, 1989.
DOI
|
32 |
H. Kishino and M. Hasegawa, "Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea," J. Mol. Evol., vol. 29, no. 2, pp. 170-179, 1989.
DOI
|
33 |
C. S. Wardley, E. B. Applegate, A. D. Almaleki, and J. A. Van Rhee, "A comparison of Students' perceptions of stress in parallel problem-based and lecture-based curricula," J. Physician Assist. Educ., vol. 27, no. 1, pp. 7-16, 2016.
DOI
|
34 |
H. Swaminathan, R. K. Hambleton, S. G. Sireci, D. Xing, and S. M. Rizavi, "Small sample estimation in dichotomous item response models: Effect of priors based on judgmental information on the accuracy of item parameter estimates," Appl. Psychol. Meas., vol. 27, no. 1, pp. 27-51, 2003.
DOI
|
35 |
R. K. Hambleton, H. Swaminathan, and H. J. Rogers, Fundamentals of item response theory, vol. 2. Sage, 1991.
|
36 |
D. Almaleki, "Stability of the Data-Model Fit over Increasing Levels of Factorial Invariance for Different Features of Design in Factor Analysis," Eng. Technol. Appl. Sci. Res., vol. 11, no. 2, pp. 6849-6856, 2021.
DOI
|
37 |
D. Almaleki, "The Precision of the Overall Data-Model Fit for Different Design Features in Confirmatory Factor Analysis," Eng. Technol. Appl. Sci. Res., vol. 11, no. 1, pp. 6766-6774, 2021.
DOI
|
38 |
J. Y. Park, F. Cornillie, H. L. van der Maas, and W. Van Den Noortgate, "A multidimensional IRT approach for dynamically monitoring ability growth in computerized practice environments," Front. Psychol., vol. 10, p. 620, 2019.
DOI
|
39 |
R. K. Hambleton and A. Kanjee, "Increasing the validity of cross-cultural assessments: Use of improved methods for test adaptations," Eur. J. Psychol. Assess., vol. 11, no. 3, pp. 147-157, 1995.
DOI
|
40 |
D. A. Almaleki, R. A. Alhajaji, and M. A. Alharbi, "Measuring Students' Interaction in Distance Learning Through the Electronic Platform and its Impact on their Motivation to Learn During Covid-19 Crisis," Int. J. Comput. Sci. Netw. Secur., vol. 21, no. 5, pp. 98-112, May 2021, doi: 10.22937/IJCSNS.2021.21.5.16.
DOI
|
41 |
E.-Y. Mun, Y. Huo, H. R. White, S. Suzuki, and J. de la Torre, "Multivariate higher-order IRT model and MCMC algorithm for linking individual participant data from multiple studies," Front. Psychol., vol. 10, p. 1328, 2019.
DOI
|
42 |
A. Preti, M. Vellante, and D. R. Petretto, "The psychometric properties of the 'Reading the Mind in the Eyes' Test: an item response theory (IRT) analysis," Cognit. Neuropsychiatry, vol. 22, no. 3, pp. 233-253, 2017.
DOI
|
43 |
C. S. Wardley, E. B. Applegate, A. D. Almaleki, and J. A. Van Rhee, "Is Student Stress Related to Personality or Learning Environment in a Physician Assistant Program?," J. Physician Assist. Educ., vol. 30, no. 1, pp. 9-19, 2019.
DOI
|
44 |
R. K. Hambleton and W. J. Van der Linden, Advances in item response theory and applications: An introduction. Sage Publications Sage CA: Thousand Oaks, CA, 1982.
|
45 |
G. C. Foster, H. Min, and M. J. Zickar, "Review of item response theory practices in organizational research: Lessons learned and paths forward," Organ. Res. Methods, vol. 20, no. 3, pp. 465-486, 2017.
DOI
|
46 |
G. Rajlic, "Violations of unidimensionality and local independence in measures intended as unidimensional: assessing levels of violations and the accuracy in unidimensional IRT model estimates," PhD Thesis, University of British Columbia, 2019.
|
47 |
R. Liu, A. C. Huggins-Manley, and O. Bulut, "Retrofitting diagnostic classification models to responses from IRT-based assessment forms," Educ. Psychol. Meas., vol. 78, no. 3, pp. 357-383, 2018.
DOI
|
48 |
M. A. Tanner and W. H. Wong, "The calculation of posterior distributions by data augmentation," J. Am. Stat. Assoc., vol. 82, no. 398, pp. 528-540, 1987.
DOI
|
49 |
S.-K. Chen, L. Hou, and B. G. Dodd, "A comparison of maximum likelihood estimation and expected a posteriori estimation in CAT using the partial credit model," Educ. Psychol. Meas., vol. 58, no. 4, pp. 569-595, 1998.
DOI
|
50 |
W. Ma, N. Minchen, and J. de la Torre, "Choosing between CDM and unidimensional IRT: The proportional reasoning test case," Meas. Interdiscip. Res. Perspect., vol. 18, no. 2, pp. 87-96, 2020.
DOI
|
51 |
C. L. Azevedo, D. F. Andrade, and J.-P. Fox, "A Bayesian generalized multiple group IRT model with model-fit assessment tools," Comput. Stat. Data Anal., vol. 56, no. 12, pp. 4399-4412, 2012.
DOI
|
52 |
I. Paek, M. Cui, N. Ozturk Gubes, and Y. Yang, "Estimation of an IRT model by Mplus for dichotomously scored responses under different estimation methods," Educ. Psychol. Meas., vol. 78, no. 4, pp. 569-588, 2018.
DOI
|
53 |
K. Matlock Cole and I. Paek, "PROC IRT: A SAS procedure for item response theory," Appl. Psychol. Meas., vol. 41, no. 4, pp. 311-320, 2017.
DOI
|
54 |
K. K. Tatsuoka, "Rule space: An approach for dealing with misconceptions based on item response theory," J. Educ. Meas., pp. 345-354, 1983.
|
55 |
G. L. Candell and F. Drasgow, "An iterative procedure for linking metrics and assessing item bias in item response theory," Appl. Psychol. Meas., vol. 12, no. 3, pp. 253-260, 1988.
DOI
|
56 |
I. W. Molenaar, "Some background for item response theory and the Rasch model," in Rasch models, Springer, 1995, pp. 3-14.
|
57 |
S. E. Embretson and S. P. Reise, Item response theory. Psychology Press, 2013.
|
58 |
T. Strachan, E. Ip, Y. Fu, T. Ackerman, S.-H. Chen, and J. Willse, "Robustness of projective IRT to misspecification of the underlying multidimensional model," Appl. Psychol. Meas., vol. 44, no. 5, pp. 362-375, 2020.
DOI
|
59 |
D. A. Almaleki, "Challenges Experienced Use of Distance-Learning by High School Teachers Responses to Students with Depression," Int. J. Comput. Sci. Netw. Secur., vol. 21, no. 5, pp. 192-198, May 2021, doi: 10.22937/IJCSNS.2021.21.5.27.
DOI
|
60 |
D. A. Almaleki, "The Psychometric Properties of Distance-Digital Subjective Happiness Scale," Int. J. Comput. Sci. Netw. Secur., vol. 21, no. 5, pp. 211-216, May 2021, doi: 10.22937/IJCSNS.2021.21.5.29.
DOI
|
61 |
J. J. Hox, C. J. Maas, and M. J. Brinkhuis, "The effect of estimation method and sample size in multilevel structural equation modeling," Stat. Neerlandica, vol. 64, no. 2, pp. 157-170, 2010.
DOI
|
62 |
R. K. Hambleton and R. W. Jones, "Comparison of classical test theory and item response theory and their applications to test development," Educ. Meas. Issues Pract., vol. 12, no. 3, pp. 38-47, 1993.
|