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Silva Diaz, John Alexander; Köhler, Carmen; Hartig, Johannes – Applied Measurement in Education, 2022
Testing item fit is central in item response theory (IRT) modeling, since a good fit is necessary to draw valid inferences from estimated model parameters. "Infit" and "outfit" fit statistics, widespread indices for detecting deviations from the Rasch model, are affected by data factors, such as sample size. Consequently, the…
Descriptors: Intervals, Item Response Theory, Item Analysis, Inferences
Lehrer, Richard – Statistics Education Research Journal, 2017
Grade 6 (modal age 11) students invented and revised models of the variability generated as each measured the perimeter of a table in their classroom. To construct models, students represented variability as a linear composite of true measure (signal) and multiple sources of random error. Students revised models by developing sampling…
Descriptors: Models, Statistics, Statistical Inference, Mathematics Instruction
Tutz, Gerhard; Berger, Moritz – Journal of Educational and Behavioral Statistics, 2016
Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…
Descriptors: Response Style (Tests), Rating Scales, Data Interpretation, Statistical Bias
Stamey, James D.; Beavers, Daniel P.; Sherr, Michael E. – Sociological Methods & Research, 2017
Survey data are often subject to various types of errors such as misclassification. In this article, we consider a model where interest is simultaneously in two correlated response variables and one is potentially subject to misclassification. A motivating example of a recent study of the impact of a sexual education course for adolescents is…
Descriptors: Bayesian Statistics, Classification, Models, Correlation
Two Distinct Exploratory Behaviors in Decisions from Experience: Comment on Gonzalez and Dutt (2011)
Hills, Thomas T.; Hertwig, Ralph – Psychological Review, 2012
Gonzalez and Dutt (2011) recently reported that trends during sampling, prior to a consequential risky decision, reveal a gradual movement from exploration to exploitation. That is, even when search imposes no immediate costs, people adopt the same pattern manifest in costly search: early exploration followed by later exploitation. From this…
Descriptors: Decision Making, Models, Inferences, Sampling
Jia, Fan; Moore, E. Whitney G.; Kinai, Richard; Crowe, Kelly S.; Schoemann, Alexander M.; Little, Todd D. – International Journal of Behavioral Development, 2014
Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This article explores this question by using…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
Li, Tiandong – ProQuest LLC, 2012
In large-scale assessments, such as the National Assessment of Educational Progress (NAEP), plausible values based on Multiple Imputations (MI) have been used to estimate population characteristics for latent constructs under complex sample designs. Mislevy (1991) derived a closed-form analytic solution for a fixed-effect model in creating…
Descriptors: National Competency Tests, Statistical Analysis, Educational Assessment, Test Theory
Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability

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