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Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Eunsook Kim; Diep Nguyen; Siyu Liu; Yan Wang – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Factor mixture modeling (FMM) is generally complex with both unobserved categorical and unobserved continuous variables. We explore the potential of item parceling to reduce the model complexity of FMM and improve convergence and class enumeration accordingly. To this end, we conduct Monte Carlo simulations with three types of data, continuous,…
Descriptors: Structural Equation Models, Factor Analysis, Factor Structure, Monte Carlo Methods
Zachary J. Roman; Patrick Schmidt; Jason M. Miller; Holger Brandt – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Careless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading to erroneous inference. There are multiple approaches to identifying and accounting for C/IER in survey settings, of these approaches the best performing…
Descriptors: Structural Equation Models, Bayesian Statistics, Response Style (Tests), Robustness (Statistics)
Xiaying Zheng; Ji Seung Yang; Jeffrey R. Harring – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Measuring change in an educational or psychological construct over time is often achieved by repeatedly administering the same items to the same examinees over time and fitting a second-order latent growth curve model. However, latent growth modeling with full information maximum likelihood (FIML) estimation becomes computationally challenging…
Descriptors: Longitudinal Studies, Data Analysis, Item Response Theory, Structural Equation Models
Ferrando, Pere J.; Anguiano-Carrasco, Cristina; Demestre, Josep – Structural Equation Modeling: A Multidisciplinary Journal, 2013
This article proposes a model-based procedure, intended for personality measures, for exploiting the auxiliary information provided by the certainty with which individuals answer every item (response certainty). This information is used to (a) obtain more accurate estimates of individual trait levels, and (b) provide a more detailed assessment of…
Descriptors: Structural Equation Models, Item Response Theory, Personality Measures, Goodness of Fit
DeMars, Christine E. – Structural Equation Modeling: A Multidisciplinary Journal, 2012
In structural equation modeling software, either limited-information (bivariate proportions) or full-information item parameter estimation routines could be used for the 2-parameter item response theory (IRT) model. Limited-information methods assume the continuous variable underlying an item response is normally distributed. For skewed and…
Descriptors: Item Response Theory, Structural Equation Models, Computation, Computer Software
Ferrando, Pere J. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
Most personality tests are made up of Likert-type items and analyzed by means of factor analysis (FA). In this type of application, the fit of the model at the level of individual respondents is almost never assessed. This article proposes procedures for assessing individual fit (scalability). The procedures are intended for the analysis of…
Descriptors: Personality, Factor Analysis, Personality Measures, Item Response Theory
Kamata, Akihito; Bauer, Daniel J. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
The relations among several alternative parameterizations of the binary factor analysis model and the 2-parameter item response theory model are discussed. It is pointed out that different parameterizations of factor analysis model parameters can be transformed into item response model theory parameters, and general formulas are provided.…
Descriptors: Factor Analysis, Data Analysis, Item Response Theory, Correlation
Flora, David B.; Curran, Patrick J.; Hussong, Andrea M.; Edwards, Michael C. – Structural Equation Modeling: A Multidisciplinary Journal, 2008
A large literature emphasizes the importance of testing for measurement equivalence in scales that may be used as observed variables in structural equation modeling applications. When the same construct is measured across more than one developmental period, as in a longitudinal study, it can be especially critical to establish measurement…
Descriptors: Structural Equation Models, Item Response Theory, Measurement, Scores
Lanza, Stephanie T.; Collins, Linda M.; Lemmon, David R.; Schafer, Joseph L. – Structural Equation Modeling: A Multidisciplinary Journal, 2007
Latent class analysis (LCA) is a statistical method used to identify a set of discrete, mutually exclusive latent classes of individuals based on their responses to a set of observed categorical variables. In multiple-group LCA, both the measurement part and structural part of the model can vary across groups, and measurement invariance across…
Descriptors: Structural Equation Models, Syntax, Drinking, Statistical Analysis
Lu, Irene R. R.; Thomas, D. Roland – Structural Equation Modeling: A Multidisciplinary Journal, 2008
This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…
Descriptors: Least Squares Statistics, Computation, Item Response Theory, Structural Equation Models
Hancock, Gregory R.; Choi, Jaehwa – Structural Equation Modeling: A Multidisciplinary Journal, 2006
In its most basic form, latent growth modeling (latent curve analysis) allows an assessment of individuals' change in a measured variable X over time. For simple linear models, as with other growth models, parameter estimates associated with the a construct (amount of X at a chosen temporal reference point) and b construct (growth in X per unit…
Descriptors: Structural Equation Models, Item Response Theory, Statistical Analysis, Research Methodology
Byrne, Barbara M.; Stewart, Sunita M. – Structural Equation Modeling: A Multidisciplinary Journal, 2006
The overarching intent of this article is to exemplify strategies associated with tests for measurement invariance that are uncommonly applied and reported in the extant literature. Designed within a pedagogical framework, the primary purposes are 3-fold and illustrate (a) tests for measurement invariance based on the analysis of means and…
Descriptors: Factor Structure, Item Response Theory, Testing, Statistical Analysis
Schweizer, Karl – Structural Equation Modeling: A Multidisciplinary Journal, 2006
A model with fixed relations between manifest and latent variables is presented for investigating choice reaction time data. The numbers for fixation originate from the polynomial function. Two options are considered: the component-based (1 latent variable for each component of the polynomial function) and composite-based options (1 latent…
Descriptors: Reaction Time, Algebra, Mathematical Formulas, Item Response Theory
Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang – Structural Equation Modeling: A Multidisciplinary Journal, 2006
This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…
Descriptors: Structural Equation Models, Path Analysis, Simulation, Equations (Mathematics)
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