Purpose: The primary purpose of this study was to validate common respiratory calibration methods for estimating lung volume in children. Method: Respiratory kinematic data were collected via inductive plethysmography from 81 typically developing children and nine children with neuromotor disorders. Correction factors for the rib cage and abdomen…

Psycholinguistic research aims to understand how people make sense of language in their everyday lives. However, most of this research studies language under experimental conditions in which people are instructed to specifically monitor (and indicate) when there is a breakdown in their understanding. Moreover, there is an assumption that people…

Factor score regression (FSR) is widely used as a convenient alternative to traditional structural equation modeling (SEM) for assessing structural relations between latent variables. But when latent variables are simply replaced by factor scores, biases in the structural parameter estimates often have to be corrected, due to the measurement error…

The goal of the present study was to address the analytical complexity of incorporating responses and response times through applying the Jeon and De Boeck mixture item response theory model in Mplus 8.7. Using both simulated and real data, we attempt to identify subgroups of responders that are rapid guessers or engage knowledge retrieval…

Given that the usage and complexity of spreadsheets in the accounting profession are expected to increase, it is more important than ever to ensure that accounting graduates are aware of the dangers of spreadsheet errors and are equipped with design skills to minimize those errors. Although spreadsheet mechanics are prevalent in accounting…

In this article, an overview is given of four methods to perform factor score regression (FSR), namely regression FSR, Bartlett FSR, the bias avoiding method of Skrondal and Laake, and the bias correcting method of Croon. The bias correcting method is extended to include a reliable standard error. The four methods are compared with each other and…

Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…