A Monte Carlo simulation study was conducted to examine the performance of [alpha], [lambda]2, [lambda][subscript 4], [lambda][subscript 2], [omega][subscript T], GLB[subscript MRFA], and GLB[subscript Algebraic] coefficients. Population reliability, distribution shape, sample size, test length, and number of response categories were varied…

A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's…

This research examined correlation estimates between latent abilities when using the two-dimensional and three-dimensional compensatory and noncompensatory item response theory models. Simulation study results showed that the recovery of the latent correlation was best when the test contained 100% of simple structure items for all models and…

In this study, the purpose is to compare factor retention methods under simulation conditions. For this purpose, simulations conditions with a number of factors (1, 2 [simple]), sample sizes (250, 1.000, and 3.000), number of items (20, 30), average factor loading (0.50, 0.70), and correlation matrix (Pearson Product Moment [PPM] and Tetrachoric)…

Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…

Purpose: This research investigates Tests that include DIF items and which are purified from DIF items. While doing this, the ability estimations and purified DIF items are compared to understand whether there is a correlation between the estimations. Method: The researcher used to R 3.4.1 in order to compare the items and after this situation;…

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…

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…

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…

This study investigated the effect of complex structure on dimensionality assessment in compensatory multidimensional item response models using DETECT- and NOHARM-based methods. The performance was evaluated via the accuracy of identifying the correct number of dimensions and the ability to accurately recover item groupings using a simple…

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…

An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…

Most research on confirmatory factor analysis using information-based fit indices (Akaike information criterion [AIC], Bayesian information criteria [BIC], bias-corrected AIC [AICc], and consistent AIC [CAIC]) has used a structural equation modeling framework. Minimal research has been done concerning application of these indices to item response…

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…

The purpose of this research was to compare the equating performance of various equating procedures for the multidimensional tests. To examine the various equating procedures, simulated data sets were used that were generated based on a multidimensional item response theory (MIRT) framework. Various equating procedures were examined, including…