Pairwise likelihood estimation for factor analysis models with ordinal data

TL;DR: In this paper, the authors develop a theory of how management can develop and promote the learning capabilities of targeted customer-supplier relationships, which suggests that a supplier and a customer can improve their joint learning activities by facilitating information exchange, developing common learning arenas, and updating their behavior accordingly.

TL;DR: In this article, the authors reviewed ten years of studies containing exploratory factor analysis and compared them with new methodological options, focusing on four major issues: an adequate sample size, the extraction method, the rotation method and the factor retention criterion determining the number of factors.

TL;DR: A family of Root Mean Square Error of Approximation statistics is proposed for assessing the goodness of approximation in discrete multivariate analysis with applications to item response theory (IRT) models, and a strong linear relationship between the RMSEA2 and the Standardized Root Mean Squared Residual goodness-of-fit index is found.

TL;DR: In this article, the authors provide an overview of goodness-of-fit assessment methods for item response theory (IRT) models, including root mean squared error of approximation (RMSEA), which makes it possible to test whether the model misfit is below a specific cutoff value.

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TL;DR: In this article, the authors considered the problem of estimating latent ability using the entire response pattern of free-response items, first in the general case and then in the case where the items are scored in a graded way, especially when the thinking process required for solving each item is assumed to be homogeneous.

TL;DR: The Em procedure is shown to apply to general item-response models lacking simple sufficient statistics for ability, including models with more than one latent dimension, when computing procedures based on an EM algorithm are used.

TL;DR: In this paper, a structural equation model with a generalized measurement part was proposed for dichotomous and ordered categorical variables (indicators) in addition to continuous ones, and a computationally feasible three-stage estimator is proposed for any combination of observed variable types.