Background/purpose: This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods: The researchers depended on the measurement accuracy indicators, which express the absolute difference between the estimated and actual values of the…

This study utilizes an analysis of diminishing returns to examine the relationship between sample size and item parameter estimation precision when utilizing the Masters' Partial Credit Model for polytomous items. Item data from the standardization of the Batelle Developmental Inventory, 3rd Edition were used. Each item was scored with a…

In applications of item response theory (IRT) models, it is known that empirical violations of the local independence (LI) assumption can significantly bias parameter estimates. To address this issue, we propose a threshold-autoregressive item response theory (TAR-IRT) model that additionally accounts for order dependence among the item responses…

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.…

The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…

In recent years, the interest in measuring growth in student ability in various subjects between different grades in school has increased. Therefore, good precision in the estimated growth is of importance. This paper aims to compare estimation methods and test designs when it comes to precision and bias of the estimated growth of mean ability…

New MAP® Growth™ assessments are being developed that administer items more closely matched to the grade level of the student. However, MAP Growth items are calibrated with samples that typically consist of students from a variety of grades, including the target grade to which an item is aligned. While this choice of calibration sample is…

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…

This study investigated the effectiveness of statistical adjustments applied to rater bias in many-facet Rasch analysis. Some changes were first made in the dataset that did not include "rater × examinee" bias to cause to have "rater × examinee" bias. Later, bias adjustment was applied to rater bias included in the data file,…

When constructing multiple test forms, the number of items and the total test difficulty are often equivalent. Not all test developers match the number of items and/or average item difficulty within subcontent areas. In this simulation study, six test forms were constructed having an equal number of items and average item difficulty overall.…

The aim of this simulation study, determine the relationship between true latent scores and estimated latent scores by including various control variables and different statistical models. The study also aimed to compare the statistical models and determine the effects of different distribution types, response formats and sample sizes on latent…

This article describes an approach to test scoring, referred to as "delta scoring" (D-scoring), for tests with dichotomously scored items. The D-scoring uses information from item response theory (IRT) calibration to facilitate computations and interpretations in the context of large-scale assessments. The D-score is computed from the…

This study compares the performance of two estimation algorithms of new usage, the Metropolis-Hastings Robins-Monro (MHRM) and the Hamiltonian MCMC (HMC), with two consolidated algorithms in the psychometric literature, the marginal likelihood via EM algorithm (MML-EM) and the Markov chain Monte Carlo (MCMC), in the estimation of multidimensional…

This inquiry is an investigation of item response theory (IRT) proficiency estimators' accuracy under multistage testing (MST). We chose a two-stage MST design that includes four modules (one at Stage 1, three at Stage 2) and three difficulty paths (low, middle, high). We assembled various two-stage MST panels (i.e., forms) by manipulating two…

Unmotivated test takers using rapid guessing in item responses can affect validity studies and teacher and institution performance evaluation negatively, making it critical to identify these test takers. The authors propose a new nonparametric method for finding response-time thresholds for flagging item responses that result from rapid-guessing…