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Showing 1 to 15 of 84 results Save | Export
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Silva, Hernán A.; Quezada, Luis E.; Oddershede, A. M.; Palominos, Pedro I.; O'Brien, Christopher – Journal of College Student Retention: Research, Theory & Practice, 2023
The objective of this paper is the design of a predictive model of students' desertion in Educational Institutions based on the Analytic Hierarchy Process (AHP). The proposed model is based on a weighted sum of individual probabilities of desertion associated with various factors (explanatory variables) by experts in the combined use of the AHP…
Descriptors: Foreign Countries, Prediction, Models, Probability
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Myoung-jae Lee; Goeun Lee; Jin-young Choi – Sociological Methods & Research, 2025
A linear model is often used to find the effect of a binary treatment D on a noncontinuous outcome Y with covariates X. Particularly, a binary Y gives the popular "linear probability model (LPM)," but the linear model is untenable if X contains a continuous regressor. This raises the question: what kind of treatment effect does the…
Descriptors: Probability, Least Squares Statistics, Regression (Statistics), Causal Models
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Long, J. Scott; Mustillo, Sarah A. – Sociological Methods & Research, 2021
Methods for group comparisons using predicted probabilities and marginal effects on probabilities are developed for regression models for binary outcomes. Unlike approaches based on the comparison of regression coefficients across groups, the methods we propose are unaffected by the scalar identification of the coefficients and are expressed in…
Descriptors: Regression (Statistics), Comparative Analysis, Probability, Groups
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Breen, Richard; Bernt Karlson, Kristian; Holm, Anders – Sociological Methods & Research, 2021
The Karlson-Holm-Breen (KHB) method has rapidly become popular as a way of separating the impact of confounding from rescaling when comparing conditional and unconditional parameter estimates in nonlinear probability models such as the logit and probit. In this note, we show that the same estimates can be obtained in a somewhat different way to…
Descriptors: Probability, Models, Computation, Comparative Analysis
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Pang, Bo; Nijkamp, Erik; Wu, Ying Nian – Journal of Educational and Behavioral Statistics, 2020
This review covers the core concepts and design decisions of TensorFlow. TensorFlow, originally created by researchers at Google, is the most popular one among the plethora of deep learning libraries. In the field of deep learning, neural networks have achieved tremendous success and gained wide popularity in various areas. This family of models…
Descriptors: Artificial Intelligence, Regression (Statistics), Models, Classification
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Gurkan, Gulsah; Benjamini, Yoav; Braun, Henry – Large-scale Assessments in Education, 2021
Employing nested sequences of models is a common practice when exploring the extent to which one set of variables mediates the impact of another set. Such an analysis in the context of logistic regression models confronts two challenges: (1) direct comparisons of coefficients across models are generally biased due to the changes in scale that…
Descriptors: Statistical Inference, Regression (Statistics), Adults, Models
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Sun, Yan; Beriswill, Joanne; Allen, Maresha E. – International Journal of Distance Education Technologies, 2022
This study represented dimensions from the diffusion of innovations theory and the community of inquiry model to explore the adoption of web-conferencing. It used logistic regression to model the likelihood of adopting web-conferencing in online teaching with data collected from 66 college online instructors. In the logistic regression analyses,…
Descriptors: Teleconferencing, Web Based Instruction, Online Courses, Technology Integration
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McNeish, Daniel – Journal of Experimental Education, 2018
Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…
Descriptors: Measures (Individuals), Nonparametric Statistics, Item Response Theory, Regression (Statistics)
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Chatterjee, Ayona; Marachi, Christine; Natekar, Shruti; Rai, Chinki; Yeung, Fanny – College Student Journal, 2018
Improving graduation rates is one of the biggest missions in many universities across the country and it is surely the case on the campus of this institution. The work here presents a statistical tool box to use early academic performance as a predictor for graduation with logistic regression and machine learning techniques. The methods described…
Descriptors: Regression (Statistics), Student Characteristics, Graduation, Probability
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Leech, Kathryn A.; Ratner, Nan Bernstein; Brown, Barbara; Weber, Christine M. – Journal of Speech, Language, and Hearing Research, 2017
Purpose: Childhood stuttering is common but is often outgrown. Children whose stuttering persists experience significant life impacts, calling for a better understanding of what factors may underlie eventual recovery. In previous research, language ability has been shown to differentiate children who stutter (CWS) from children who do not stutter,…
Descriptors: Stuttering, Children, Predictor Variables, Probability
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Desjardins, Christopher David – Journal of Experimental Education, 2016
The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative…
Descriptors: Suspension, Statistical Analysis, Models, Data
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Stevens, Jon Scott; Gleitman, Lila R.; Trueswell, John C.; Yang, Charles – Cognitive Science, 2017
We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed "Pursuit," uses an associative…
Descriptors: Semantics, Associative Learning, Probability, Computational Linguistics
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Jenkins, Andrew – British Journal of Educational Studies, 2018
This paper investigates why people return to study in their 30s and beyond and upgrade to a higher level qualifications. Some previous research has argued that attitudes formed in childhood, via family background and schooling, continue to shape a person's engagement in learning throughout the adult lifecourse. Psychologists distinguish extrinsic…
Descriptors: Adults, Adult Learning, Adult Education, Higher Education
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Buis, Maarten L. – Sociological Methods & Research, 2017
This article deals with a model for describing a sequence of events, for example, education is typically attained by a set of transitions from one level of education to the next. In particular, this article tries to reconcile measures describing the effect of a variable on each of these transitions, with measures describing the effect of this…
Descriptors: Models, Measurement Techniques, Regression (Statistics), Sequential Approach
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Denby, Thomas; Schecter, Jeffrey; Arn, Sean; Dimov, Svetlin; Goldrick, Matthew – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Phonotactics--constraints on the position and combination of speech sounds within syllables--are subject to statistical differences that gradiently affect speaker and listener behavior (e.g., Vitevitch & Luce, 1999). What statistical properties drive the acquisition of such constraints? Because they are naturally highly correlated, previous…
Descriptors: Phonology, Probability, Learning Processes, Syllables
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