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Edwards, Ashley A.; Joyner, Keanan J.; Schatschneider, Christopher – Educational and Psychological Measurement, 2021
The accuracy of certain internal consistency estimators have been questioned in recent years. The present study tests the accuracy of six reliability estimators (Cronbach's alpha, omega, omega hierarchical, Revelle's omega, and greatest lower bound) in 140 simulated conditions of unidimensional continuous data with uncorrelated errors with varying…
Descriptors: Reliability, Computation, Accuracy, Sample Size
Chenchen Ma; Jing Ouyang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
Survey instruments and assessments are frequently used in many domains of social science. When the constructs that these assessments try to measure become multifaceted, multidimensional item response theory (MIRT) provides a unified framework and convenient statistical tool for item analysis, calibration, and scoring. However, the computational…
Descriptors: Algorithms, Item Response Theory, Scoring, Accuracy
Kim, Hyung Jin; Lee, Won-Chan – Journal of Educational Measurement, 2022
Orlando and Thissen (2000) introduced the "S - X[superscript 2]" item-fit index for testing goodness-of-fit with dichotomous item response theory (IRT) models. This study considers and evaluates an alternative approach for computing "S - X[superscript 2]" values and other factors associated with collapsing tables of observed…
Descriptors: Goodness of Fit, Test Items, Item Response Theory, Computation
Derek Sauder – ProQuest LLC, 2020
The Rasch model is commonly used to calibrate multiple choice items. However, the sample sizes needed to estimate the Rasch model can be difficult to attain (e.g., consider a small testing company trying to pretest new items). With small sample sizes, auxiliary information besides the item responses may improve estimation of the item parameters.…
Descriptors: Item Response Theory, Sample Size, Computation, Test Length
Baris Pekmezci, Fulya; Sengul Avsar, Asiye – International Journal of Assessment Tools in Education, 2021
There is a great deal of research about item response theory (IRT) conducted by simulations. Item and ability parameters are estimated with varying numbers of replications under different test conditions. However, it is not clear what the appropriate number of replications should be. The aim of the current study is to develop guidelines for the…
Descriptors: Item Response Theory, Computation, Accuracy, Monte Carlo Methods
Zhou, Sherry; Huggins-Manley, Anne Corinne – Educational and Psychological Measurement, 2020
The semi-generalized partial credit model (Semi-GPCM) has been proposed as a unidimensional modeling method for handling not applicable scale responses and neutral scale responses, and it has been suggested that the model may be of use in handling missing data in scale items. The purpose of this study is to evaluate the ability of the…
Descriptors: Models, Statistical Analysis, Response Style (Tests), Test Items
Kilic, Abdullah Faruk; Uysal, Ibrahim; Atar, Burcu – International Journal of Assessment Tools in Education, 2020
This Monte Carlo simulation study aimed to investigate confirmatory factor analysis (CFA) estimation methods under different conditions, such as sample size, distribution of indicators, test length, average factor loading, and factor structure. Binary data were generated to compare the performance of maximum likelihood (ML), mean and variance…
Descriptors: Factor Analysis, Computation, Methods, Sample Size
Kilic, Abdullah Faruk; Dogan, Nuri – International Journal of Assessment Tools in Education, 2021
Weighted least squares (WLS), weighted least squares mean-and-variance-adjusted (WLSMV), unweighted least squares mean-and-variance-adjusted (ULSMV), maximum likelihood (ML), robust maximum likelihood (MLR) and Bayesian estimation methods were compared in mixed item response type data via Monte Carlo simulation. The percentage of polytomous items,…
Descriptors: Factor Analysis, Computation, Least Squares Statistics, Maximum Likelihood Statistics
Yavuz, Guler; Hambleton, Ronald K. – Educational and Psychological Measurement, 2017
Application of MIRT modeling procedures is dependent on the quality of parameter estimates provided by the estimation software and techniques used. This study investigated model parameter recovery of two popular MIRT packages, BMIRT and flexMIRT, under some common measurement conditions. These packages were specifically selected to investigate the…
Descriptors: Item Response Theory, Models, Comparative Analysis, Computer Software
Huang, Hung-Yu – Educational and Psychological Measurement, 2017
Mixture item response theory (IRT) models have been suggested as an efficient method of detecting the different response patterns derived from latent classes when developing a test. In testing situations, multiple latent traits measured by a battery of tests can exhibit a higher-order structure, and mixtures of latent classes may occur on…
Descriptors: Item Response Theory, Models, Bayesian Statistics, Computation
Paek, Insu – Educational and Psychological Measurement, 2016
The effect of guessing on the point estimate of coefficient alpha has been studied in the literature, but the impact of guessing and its interactions with other test characteristics on the interval estimators for coefficient alpha has not been fully investigated. This study examined the impact of guessing and its interactions with other test…
Descriptors: Guessing (Tests), Computation, Statistical Analysis, Test Length
Lee, Yi-Hsuan; Zhang, Jinming – International Journal of Testing, 2017
Simulations were conducted to examine the effect of differential item functioning (DIF) on measurement consequences such as total scores, item response theory (IRT) ability estimates, and test reliability in terms of the ratio of true-score variance to observed-score variance and the standard error of estimation for the IRT ability parameter. The…
Descriptors: Test Bias, Test Reliability, Performance, Scores
Lathrop, Quinn N.; Cheng, Ying – Applied Psychological Measurement, 2013
Within the framework of item response theory (IRT), there are two recent lines of work on the estimation of classification accuracy (CA) rate. One approach estimates CA when decisions are made based on total sum scores, the other based on latent trait estimates. The former is referred to as the Lee approach, and the latter, the Rudner approach,…
Descriptors: Item Response Theory, Accuracy, Classification, Computation
Lei, Pui-Wa; Zhao, Yu – Applied Psychological Measurement, 2012
Vertical scaling is necessary to facilitate comparison of scores from test forms of different difficulty levels. It is widely used to enable the tracking of student growth in academic performance over time. Most previous studies on vertical scaling methods assume relatively long tests and large samples. Little is known about their performance when…
Descriptors: Scaling, Item Response Theory, Test Length, Sample Size
Wu, Yi-Fang – ProQuest LLC, 2015
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…
Descriptors: Item Response Theory, Test Items, Accuracy, Computation
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