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Parian Haghighat; Denisa Gandara; Lulu Kang; Hadis Anahideh – Grantee Submission, 2024
Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and inaccessible for evaluation or modification by researchers and practitioners, limiting their accountability and ethical design. Moreover, predictive models are often opaque…
Descriptors: Prediction, Learning Analytics, Multivariate Analysis, Regression (Statistics)
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Olsson, Ulf – Practical Assessment, Research & Evaluation, 2022
We discuss analysis of 5-grade Likert type data in the two-sample case. Analysis using two-sample "t" tests, nonparametric Wilcoxon tests, and ordinal regression methods, are compared using simulated data based on an ordinal regression paradigm. One thousand pairs of samples of size "n"=10 and "n"=30 were generated,…
Descriptors: Regression (Statistics), Likert Scales, Sampling, Nonparametric Statistics
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Duy Pham; Kirk Vanacore; Adam Sales; Johann Gagnon-Bartsch – Society for Research on Educational Effectiveness, 2024
Background: Education researchers typically estimate average program effects with regression; if they are interested in heterogeneous effects, they include an interaction in the model. Such models quantify and infer the influences of each covariate on the effect via interaction coefficients and their associated p-values or confidence intervals.…
Descriptors: Educational Research, Educational Researchers, Regression (Statistics), Artificial Intelligence
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Elwert, Felix; Pfeffer, Fabian T. – Sociological Methods & Research, 2022
Conventional advice discourages controlling for postoutcome variables in regression analysis. By contrast, we show that controlling for commonly available postoutcome (i.e., future) values of the treatment variable can help detect, reduce, and even remove omitted variable bias (unobserved confounding). The premise is that the same unobserved…
Descriptors: Bias, Regression (Statistics), Evaluation Methods, Research
Enakshi Saha – ProQuest LLC, 2021
We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…
Descriptors: Bayesian Statistics, Probability, Nonparametric Statistics, Data Analysis
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Abulela, Mohammed A. A.; Rios, Joseph A. – Applied Measurement in Education, 2022
When there are no personal consequences associated with test performance for examinees, rapid guessing (RG) is a concern and can differ between subgroups. To date, the impact of differential RG on item-level measurement invariance has received minimal attention. To that end, a simulation study was conducted to examine the robustness of the…
Descriptors: Comparative Analysis, Robustness (Statistics), Nonparametric Statistics, Item Analysis