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Kylie L. Anglin – Annenberg Institute for School Reform at Brown University, 2025
Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…
Descriptors: Validity, Artificial Intelligence, Models, Best Practices
Kylie Anglin – AERA Open, 2024
Given the rapid adoption of machine learning methods by education researchers, and the growing acknowledgment of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing on an integrative literature review and extending a…
Descriptors: Validity, Artificial Intelligence, Models, Best Practices
Parkkinen, Veli-Pekka; Baumgartner, Michael – Sociological Methods & Research, 2023
In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal…
Descriptors: Robustness (Statistics), Comparative Analysis, Causal Models, Models
Manapat, Patrick D.; Edwards, Michael C. – Educational and Psychological Measurement, 2022
When fitting unidimensional item response theory (IRT) models, the population distribution of the latent trait ([theta]) is often assumed to be normally distributed. However, some psychological theories would suggest a nonnormal [theta]. For example, some clinical traits (e.g., alcoholism, depression) are believed to follow a positively skewed…
Descriptors: Robustness (Statistics), Computational Linguistics, Item Response Theory, Psychological Patterns
Jang, Yoonsun; Cohen, Allan S. – Educational and Psychological Measurement, 2020
A nonconverged Markov chain can potentially lead to invalid inferences about model parameters. The purpose of this study was to assess the effect of a nonconverged Markov chain on the estimation of parameters for mixture item response theory models using a Markov chain Monte Carlo algorithm. A simulation study was conducted to investigate the…
Descriptors: Markov Processes, Item Response Theory, Accuracy, Inferences
Marmolejo-Ramos, Fernando; Cousineau, Denis – Educational and Psychological Measurement, 2017
The number of articles showing dissatisfaction with the null hypothesis statistical testing (NHST) framework has been progressively increasing over the years. Alternatives to NHST have been proposed and the Bayesian approach seems to have achieved the highest amount of visibility. In this last part of the special issue, a few alternative…
Descriptors: Hypothesis Testing, Bayesian Statistics, Evaluation Methods, Statistical Inference
Finch, Holmes – Practical Assessment, Research & Evaluation, 2022
Researchers in many disciplines work with ranking data. This data type is unique in that it is often deterministic in nature (the ranks of items "k"-1 determine the rank of item "k"), and the difference in a pair of rank scores separated by "k" units is equivalent regardless of the actual values of the two ranks in…
Descriptors: Data Analysis, Statistical Inference, Models, College Faculty
Grice, James W.; Yepez, Maria; Wilson, Nicole L.; Shoda, Yuichi – Educational and Psychological Measurement, 2017
An alternative to null hypothesis significance testing is presented and discussed. This approach, referred to as observation-oriented modeling, is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. In terms of analysis, this novel approach complements traditional methods…
Descriptors: Hypothesis Testing, Models, Observation, Statistical Inference
Phillips, Lawrence – ProQuest LLC, 2015
Choosing specific implementational details is one of the most important aspects of creating and evaluating a model. In order to properly model cognitive processes, choices for these details must be made based on empirical research. Unfortunately, modelers are often forced to make decisions in the absence of relevant data. My work investigates the…
Descriptors: Role, Inferences, Prediction, Models
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
Lu, Hongjing; Chen, Dawn; Holyoak, Keith J. – Psychological Review, 2012
How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy…
Descriptors: Inferences, Thinking Skills, Comparative Analysis, Models
Martínez, José Felipe; Schweig, Jonathan; Goldschmidt, Pete – Educational Evaluation and Policy Analysis, 2016
A key question facing teacher evaluation systems is how to combine multiple measures of complex constructs into composite indicators of performance. We use data from the Measures of Effective Teaching (MET) study to investigate the measurement properties of composite indicators obtained under various conjunctive, disjunctive (or complementary),…
Descriptors: Teacher Evaluation, Outcome Measures, Evaluation Methods, Educational Policy
Callister Everson, Kimberlee; Feinauer, Erika; Sudweeks, Richard R. – Harvard Educational Review, 2013
In this article, the authors provide a methodological critique of the current standard of value-added modeling forwarded in educational policy contexts as a means of measuring teacher effectiveness. Conventional value-added estimates of teacher quality are attempts to determine to what degree a teacher would theoretically contribute, on average,…
Descriptors: Teacher Evaluation, Teacher Effectiveness, Evaluation Methods, Accountability
Ercikan, Kadriye; Oliveri, María Elena – Applied Measurement in Education, 2016
Assessing complex constructs such as those discussed under the umbrella of 21st century constructs highlights the need for a principled assessment design and validation approach. In our discussion, we made a case for three considerations: (a) taking construct complexity into account across various stages of assessment development such as the…
Descriptors: Evaluation Methods, Test Construction, Design, Scaling
Gelman, Andrew; Hill, Jennifer; Yajima, Masanao – Journal of Research on Educational Effectiveness, 2012
Applied researchers often find themselves making statistical inferences in settings that would seem to require multiple comparisons adjustments. We challenge the Type I error paradigm that underlies these corrections. Moreover we posit that the problem of multiple comparisons can disappear entirely when viewed from a hierarchical Bayesian…
Descriptors: Intervals, Comparative Analysis, Inferences, Error Patterns